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Vol.21, Number 4, 465-568
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Vol. 21
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Chemical Industry & Chemical Engineering
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No. 4
CONTENTS
Jun Tan, Xiaoyan Wei, Yuxia Ouyang, Rui Liu, Ping Sun,
Juhong Fan, Evaluation of insoluble xanthate and
crosslinked
starch-graft-polyacrylamide-co-sodium
xanthate for the adsorption of Cu(II) in aqueous
solutions ............................................................................. 465
Ogbemudia Joseph Ogbebor, Felix Ebhodaghe Okieimen,
David Ehioghilen Ogbeifun, Uzoma Ndubuisi Okwu,
Organomodified kaolin as filler for natural rubber .............. 477
Vesna M. Pavelkić, Tanja P. Brdarić, Marija P. Petrović,
Gavrilo M. Šekularac, Milica G. Košević, Lato L. Pezo,
Marija A. Ilić, Application of Peleg model on mass
transfer kinetics during osmotic dehydratation of pear
cubes in sucrose solution ................................................... 485
Rongyan Shen, Fang Liu, Te Li, Xia Xu, Yuting Liang,
Xingqing Zhao, Wenyi Zhang, Treatment of 2-diazo-4,6-dinitrophenol
wastewater
using
TiO2/SiO2
composite film in a photocatalytic reactor .......................... 493
Milutin M. Milosavljević, Ivan M. Vukićević, Veis Šerifi, Jasmina S. Markovski, Ivana Stojiljković, Dušan Ž. Mijin,
Aleksandar D. Marinković, Optimization of the synthesis of N-alkyl and N,N-dialkyl thioureas from waste
water containing ammonium thiocyanate ........................... 501
Sheng Fang, Li-Ping Wang, Ting Wu, Mathematical modeling
and effect of blanching pretreatment on the drying
kinetics of Chinese Yam (Dioscorea opposita) .................. 511
Zorana Arsenijević, Tatjana Kaluđerović Radoičić, Mihal
Đuriš, Željko Grbavčić, Experimental investigation of
heat transfer in three-phase fluidized bed cooling
column ................................................................................ 519
Vesna S. Cvetković, Luka J. Bjelica, Nataša M. Vukićević,
Jovan N. Jovićević, Alloy formation by Mg underpotential deposition on Al from nitrate melts ...................... 527
Rajamohan Natarajan, Jamila Al-Sinani, Saravanan Viswanathan, Performance evaluation and kinetic studies on
removal of benzene in up-flow tree bark based biofilter....... 537
D. Tiroutchelvame, V. Sivakumar, J. Prakash Maran, Mass
transfer kinetics during osmotic dehydration of Amla
(Emblica officinalis L.) cubes in sugar solution .................. 547
Contents: Vol. 21, Issues 1–4, 2015 .............................................. 561
Author Index, Vol. 21, 2015 .......................................................... 565
Activities of the Association of Chemical Engineers of Serbia in 2015 are supported by:
- Ministry of Education, Science and Technological Development, Republic of Serbia
- Hemofarm Koncern AD, Vršac, Serbia
- Faculty of Technology and Metallurgy, University of Belgrade, Belgrade, Serbia
- Faculty of Technology, University of Novi Sad, Novi Sad, Serbia
- Faculty of Technology, University of Niš, Leskovac, Serbia
- Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Serbia
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
JUN TAN1,2
XIAOYAN WEI1
YUXIA OUYANG1
RUI LIU2
PING SUN1,2
JUHONG FAN3
1
Department of Chemical and
Textile Engineering of Nanhu
College, Jiaxing University,
Jiaxing, Zhejiang Province, China
2
College of Biological and
Chemical Engineering, Jiaxing
University, Jiaxing, Zhejiang
Province, China
3
Zhejiang Provincial Key
Laboratory of Water Science and
Technology, Department of
Environment, Yangtze Delta
Region Institute of Zhejiang,
Jiaxing, Zhejiang Province, China
SCIENTIFIC PAPER
UDC 547.815:678.745.8:544.723:66
DOI 10.2298/CICEQ141102002T
CI&CEQ
EVALUATION OF INSOLUBLE XANTHATE
AND CROSSLINKED STARCH-GRAFT-POLYACRYLAMIDE-CO-SODIUM XANTHATE
FOR THE ADSORPTION OF Cu(II) IN
AQUEOUS SOLUTIONS
Article Highlights
• The adsorption capacity of CSAX for Cu(II) was higher than that of ISX
• The removal efficiency of ISX for Cu(II) was better than that of CSAX
• For CSAX, more N or S do not mean higher removal efficiency or higher adsorption
capacity
• The adsorption mechanism of CSAX for Cu(II) is the physical adsorption and ion
exchange
• CSAX was an alternative to ISX when treating heavy metal wastewater with turbidity
Abstract
The effectiveness of insoluble xanthate (ISX) and crosslinked starch-graftpolyacrylamide-co-sodium xanthate (CSAX) for Cu(II) removal from wastewater was evaluated. The two types of xanthates were characterized by SEM,
XRD, FTIR and elemental analysis. Also, the factors influencing adsorption
behaviors of copper ions from aqueous solutions were investigated. The
results indicated CSAX had higher absorption capacity for Cu(II) than ISX
because it contained more N and S. While as far as the removal efficiency was
concerned, ISX was better than CSAX for its strong ligand–CSS– groups. The
removal efficiency of Cu(II) onto CSAX and ISX increased with the increase in
pH. The mechanism for Cu(II) adsorption was ionic exchange for ISX whereas
both ion exchange and physical adsorption contributed to adsorption by CSAX.
The adsorption kinetics of ISX and CSAX for Cu(II) were favorably described
by the pseudo-second-order kinetic model, and the adsorption isotherms were
described well with the Freundlich isotherm model. The study with synthetic
wastewater showed CSAX was a worthwhile alternative to the traditional ISX
only when the wastewater contained both Cu(II) and turbidity.
Keywords: insoluble starch xanthate, crosslinked starch-graft-polyacrylamide-co-sodium xanthate, Cu(II) removal, adsorption kinetics, adsorption isotherm.
Water pollution caused by heavy metals has
been a worldwide concern due to their hazardous and
toxic effects on the environment, human beings, and
animals. In the past few years, the removal of heavy
metal ions from sewage and industrial wastewater
has been given lots of attention, particularly in China
Correspondence: X. Wei, Department of Chemical and Textile
Engineering of Nanhu College, Jiaxing University, Jiaxing
314001, Zhejiang Province, China.
E-mail: weixiaoyan1974@126.com
Paper received: 2 November, 2014
Paper revised: 9 January, 2015
Paper accepted: 20 January, 2015
where soil and water have been seriously polluted by
heavy metals [1-3]. Conventional methods for the
removal of heavy-metal ions from wastewater including reduction precipitation, ion exchange and adsorption, electrochemical reduction, evaporation, reverse osmosis, and direct precipitation [4,5]. Among
these methods, adsorption is generally preferred
because of its high efficiency, easy management, relatively low cost, and especially availability of different
adsorbents [6]. Therefore, the search for new highly
effective, environmental-friendly and economic-viable
adsorbents has become the focus of many studies [7].
465
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
In this respect, many natural polysaccharides
and their derivatives containing various functional
groups (chitin and its derivatives, modified cellulose,
and modified starch, etc.) have gained great interest
[8-11]. Starch is the most abundant biopolymer after
cellulose and chitosan. In contrast to cellulose, starch
is water-soluble, making it easy to be modified to
incorporate active functional groups to improve its
applications [12-15]. In 1970s, Wing et al. reported
that insoluble starch xanthate (ISX) prepared by xanthation of a highly crosslinked starch, was effective for
removing various heavy metal ions in the aqueous
medium [16-19]. The manufacture process of this
derivative as xanthation is a relatively simple, and
starch itself is a cheap biopolymer; thus it is manufactured and widely applied. Recently, Chang et al.
have synthesized a novel crosslinked starch-graftpolyacrylamide-co-sodium xanthate (CSAX) by cross-linking, grafting copolymerization and xanthation
reaction, and stated that the CSAX is more effective
than ISX in removing heavy metal ions [20-22].
A comparative study of ISX vs CSAX for the
removal of heavy metals would greatly facilitate the
choice of the more efficient adsorbent (ISX or CSAX).
Cu(II) is a common and highly toxic heavy metal pollutant because it is widely used in paints and pigments, paper and pulp, fertilizer manufacturing, wood
preservatives, and metal cleaning. Excessive intake
of Cu(II) can be accumulated in the livers of human
and animals, which leads to damage of liver and kidney, anemia, immunotoxicity, etc. [23]. The U.S. Environmental Protection Agency (U.S. EPA) requires that
copper in drinking water does not exceed 1.3 mg/L.
Therefore, in the present work, efforts were made to
study the adsorption characteristics of Cu(II) in aqueous solutions onto ISX and CSAX. The two adsorbents were characterized by SEM, XRD, FTIR and
elemental analysis. The influence of the element content, adsorbent dosage, solution pH, and contact time
on the absorption performance was investigated. In
addition, their absorption mechanism, isotherm and
kinetics were also studied, which have not been
reported in the previous literature.
EXPERIMENTAL
Materials
The cornstarch used was food grade (Tianjin
DingFeng Factory, China). Epichloro-hydrin (EPI),
acrylamide (AM), and ceric ammonium nitrate (CAN)
(AR, Shanghai Chemical Reagent Factory, China)
were used as the cross-linking reagent, graft monomer and initiator, respectively. Analytical grade ace-
466
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
tone, potassium hydroxide, hydrochloric acid and
ethanol were supplied by Hangzhou Chemical
Reagent Factory, China. The stock solution of 300
mg/L Cu(II) was prepared using CuSO4·5H2O (AR,
Shanghai Chemical Reagent Factory, China) and
then diluted to appropriate concentrations for each
test. Distilled water was used in the polymerization
and preparation of the buffer solutions.
Preparation of ISX and CSAX
The synthesis procedure and the chemicals used
for the preparation of ISX are described in Wing’s
study [17].
Step 1: Preparation of crosslinked starch. 50 g
of corn starch was added into 75 mL 1% NaCl solution in a beaker and heated to 30 °C in a water bath.
20 mL 15 mass% KOH solution was added to this
slurry, then 3.5 mL epichlorohydrin was added in
dropwise. The reaction was kept for 16 h to obtain the
crosslinked starch. The product was washed with
deionized water and ethanol, then filtered by vacuum
and dried at 133 °C for 2 h.
Step 2: Xanthation of crosslinked starch. Prepared slurry with 5 g crosslinked starch and 20 mL
distilled water, then heated at 30 °C in a water bath. A
mixture of 4 mL H2O containing 1 g NaOH and a certain amount of CS2 were added in the above liquid
and stirred for 2 h. The precipitate was washed with
distilled water, ethanol, acetone, and dry in vacuum
oven at 27 °C to a constant weight.
Three different ISXs were prepared and designated as ISX1, ISX2, and ISX3. The sulfur content in
the three different ISXs was controlled by the addition
of CS2 at 0.3 g, 0.7 g, and 1.25 g with 5.0 g crosslinked starch in the xanthation step, respectively.
The synthesis of CSAX was conducted in
accordance with the procedure described in Chang’s
study [20].
Step 1 was to prepare cross-linked starch, which
was the same as step 1 of ISX.
Step 2 was the preparation of cross-linked
starch-grafted polyacrylamide (CSA).
3.0 g of crosslinked starch was mixed with 50
mL of distilled water to prepare starch slurry at 80 °C
in a water bath. Then, 6.0 g of AM monomer and 10
mL CAN (which was used as radicals intiator) solution
(6 mmol L−1) were added to the slurry. The experiments were conducted under a nitrogen atmosphere
with constant stirring at 35 °C for 3 h (the grafting
efficiency reached the maximum value of 72.7% and
the molecular weight of graft PAM pendant chain
reached 2.67×107). Then the graft copolymer was
washed with acetone to remove the unreacted mono-
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
mer. Afterward, it was filtered and dried at 50 °C in a
vacuum oven.
Step 3 was the preparation of CSAX.
CSA (1 g) was xanthated by dropwise addition
of 3 mol/L NaOH and a certain amount of CS2 into the
sealed conical flask and stirring magnetically at 30 °C
in a water bath for 3 h until it turned saffron yellow.
The precipitate was washed with acetone (50%) three
times, pure acetone one time, filtered and dried at 27
°C to a constant weigh.
As for CSAXs, three different amounts of CS2
(0.8, 1.7 and 3.5 g) were added with 1.0 g crosslinked
starch-graft-polyacrylamide in the process of xanthation to prepare CSAX1, CSAX2 and CSAX3.
Characterization methods
X-ray diffraction (XRD) patterns of ISX and CSAX
were obtained using a DX-2600 X-ray diffractometer
(Dandong Fangyuan Instrument Company, China)
operating at 40 kV and 40 mA. The surface morphology of ISX and CSAX was examined using a
S-4800 scanning electron microscope (Hitachi, Japan).
The FT-IR spectra of ISX and CSAX were recorded
on the NEXUS470 (Nicole Instrument Corporation,
USA) using the KBr dispersion method. Elemental
analysis of dry samples was performed on a Flash
EA-1112 elemental analyzer (Thermo Fingnigan Corporation, Italy), and carbon, hydrogen, nitrogen and
sulfur contents were determined.
Adsorption experiments
In general, batch adsorption experiments were
conducted in 250 mL conical flasks containing 100
mL of Cu(II) solution with the initial concentration of
30 mg/L (unless otherwise stated) and a certain
amount of adsorbent. The mixtures were shaken at
180 rpm in a thermostatic water-bath shaker with controlled adsorption time and temperature. After adsorption equilibrium was reached, the solution was filtered
and residual Cu(II) and Na+ concentrations in the filtrate was analyzed by an AA800 atomic absorption
spectrometer (PerkinElmer, USA).
The effect of solution pH on the Cu(II) adsorption was studied in the pH range from 2 to 7 at 298 K.
The pH was adjusted using 0.1 M NaOH or 0.1 M HCl
solutions. The adsorption isotherm was studied at different initial copper concentrations ranging 30-300
mg/L at 298 K at an initial pH value of 5.3. All our
experimental data were the average of triplicate
determinations. The relative standard errors of the
data were less than 5%.
The amount of Cu(II) adsorbed on the adsorbent
(Q in mg/g) was calculated using Eq. (1):
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
Q=
(c 0 − ct )V
(1)
W
where C0 and Ct (mg/L) are the initial and final concentrations of Cu(II) at time t, respectively; V is the
total volume of the aqueous solution (L); W is the
mass of adsorbent (g). The removal efficiency of
Cu(II) was calculated using Eq. (2):
Removal efficiency (%) = 100
c0 − ce
c0
(2)
RESULTS AND DISCUSSION
Characterizations of the two adsorbents
Scanning electron microscopy (SEM) was used
to study the granular morphology of starch, ISX and
CSAX.
Figure 1 shows that native starch granules
appeared dispersedly with a smooth, oval, regular
surface, and had particle diameter with about 10 μm.
While the granules of ISX possessed obvious deformations because the cross linking and xanthation
reactions led to an altered uneven surface, creating
pores and adhension of small particles on the surface, but the particle diameter did not change obviously. CSAX showed a rougher surface, and the particles were conglomerated closely. Inaddition, the granules became significantly bigger than starch or ISX
due to graft copolymerization, and particle diameter
increased to over 100 μm.
The XRD patterns of starch, ISX and CSAX are
shown in Figure 2. The original starch shows scattering at 2θ 15.18, 17.15 and 23.19°, representing the
diffraction peaks of the hydroxyl group, which are
characteristic peaks of starch, However, the XRD
curves of ISX express traditional “A” style, and only
have a wide amorphous diffraction peak at 20.38°,
which means that the crystallinity of ISX3 decreased
remarkably than natural starch [24]. The diffraction
spectrum of CSAX becomes much weaker than ISX,
which indicates that its crystallinity was further reduced. It is attributed to the fact that the aggregation
phase of original starch was changed from a semicrystalline state to an amorphous aggregation state
during the cross-linking and graft polymerization.
The chemical structures of starch, ISX and
CSAX were indentified with FTIR spectroscopy (Figure not shown). For CSAX, a broad absorption band
at 3418 cm−1 is due to the –NH stretching of the –NH2
group (overlapped by –OH of starch). A smaller peak
at 2931 cm−1 is assigned to the –CH stretching vibrations. Absorption peaks at 1658 and 1563 cm−1 are
–C=O and –C=O (hydrogen bonded) stretching vib-
467
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
CI&CEQ 21 (4) 465−476 (2015)
Relative Intensity(%)
Figure 1. SEM images of starch (a,b), ISX (c,d) and CSAX (e,f).
starch
ISX
CSAX
10
20
30
40
Two-Theta(deg)
50
60
Figure 2. XRD patterns of starch, ISX, and CSAX.
ration of the –CONH2 groups, and the peaks at 1750
cm−1 is for –COO– stretching. The absorption peak at
2450 cm−1 corresponds to the –SH stretching vibration
of the xanthate unit. The –CSSH groups’ spectra are
displayed in the ranges of 1240–1200 cm−1, 1140–
468
–1110 cm−1, and 1070–1029 cm−1. The peak at 883
cm−1 may be attributed to the deformation of –CSS–
[20]. Therefore, it is suggested that CSAX was synthesized successfully. For ISX, there were strong
characteristic peaks at 1512 cm-1 for –C=S and 853
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
cm-1 for the –CSS– deformation [17], indicating xanthate groups were induced on the starch molecular
chain.
Elemental analysis of the dry samples shows
the different element content of ISXs and CSAXs, and
the results are shown in Table 1.
ISX1, respectively. With 200 mg/L dosage, the removal efficiency for Cu(II) was 99.91, 99.15 and 98.68%
for the three ISXs, respectively. It is evident that the
difference in Cu(II) removal efficiency of the three
ISXs was more significant at low adsorbent dosage,
and the removal efficiency was almost the same at
high adsorbent dosage. For ISXs, the optimum removal efficiency of 99.89% was obtained at an dosage
level of 150 mg/L. Therefore a dosage of ISX, ISX3
with 150 mg/L was used in the following adsorption
experiments.
In Figure 3b, Cu(II) removal efficiency did not
increase with the increase of the sulfur content in
CSAX. However, it increased gradually with the increase of S content from 3.95 to 5.03% and N content
from 4.17 to 3.65%, and it declined with the further
increase of S content from 5.03 to 8.32% and increase of N content from 3.65 to 3.09%. The Cu(II)
removal efficiency may relate to the ratio of N content
to S content. When the N content was high (4.17%), it
induced a high molecular weight of polymers and segmental overlapping of some grafted chains; when the
S content was too low, there were not enough xanthate groups. It was not favorable for the adsorption in
both cases. However, the Cu(II) removal was not
optimal when the N content was low (3.09%) and S
content was high (8.32%). It seems that a balance
would exist between the two elemental contents [25],
and only CSAX2 (N: 3.65% and S: 5.03%) exhibited
the maximum Cu(II) removal efficiency of 94.17% at
the dosage of 50 mg/L. For CSAX1 and CSAX3, their
maximum removal efficiency of Cu(II) was 83.1 and
88.07%, which was always lower than CSAX2 even at
Table 1. Elemental analysis of CSAXs (mass%)
Sample
C
H
N
S
ISX1
25.70
4.72
0.00
0.71
ISX2
26.04
4.35
0.00
1.98
ISX3
26.87
4.11
0.00
2.46
CSAX1
29.81
5.07
3.09
8.32
CSAX2
30.29
5.26
3.65
5.03
CSAX3
32.62
5.58
4.17
3.95
Effect of adsorbent dosage and element contents on
Cu(II) removal
The effects of the sulfur content and adsorbent
dosage on the adsorption of Cu(II) on ISXs and
CSAXs are shown in Figure 3. It shows that an increase in the adsorbent dosage resulted in an increase
in removal efficiency of Cu(II), then the removal efficiency leveled off in all cases. This was due to the
availability of more binding sites initially when the
adsorbent dosage increased, and then the adsorption
equilibrium was reached after a certain dosage.
In Figure 3a, Cu(II) removal efficiency was increased with the increase of sulfur contents in ISXs
with the order of: ISX3 > ISX2 > ISX1. At 50 mg/L of
adsorbent dosage removal of Cu(II) was found to be
92.29% for ISX3, 82.69% for ISX2 and 78.27% for
95
95
90
85
ISX3(S%=2.46)
ISX2(S%=1.98)
ISX1(S%=0.71)
80
75
0
100 200 300 400
The dosage of ISX(mg/L)
(a)
Removal efficiency(%)
100
Removal efficiency(%)
100
90
85
CSAX2(S%=5.03)
CSAX3(S%=8.32)
CSAX1(S%=3.95)
80
75
0
100 200 300 400 500
The dosage of CSAX(mg/L)
(b)
Figure 3. Effect of ISXs’ (a) and CSAXs’ (b) sulfur content and dosage on the removal of Cu(II).
469
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
Effects of pH on Cu(II) removal
The influence of the initial pH on the adsorption
of Cu(II) onto ISX and CSAX was examined in the pH
range of 2.0–7.0 (Figure 4). Copper is present in
aqueous solution in the forms of Cu2+, Cu(OH)+ or
Cu(OH)2. At pH ≤ 5, Cu(II) ions are the main species
in the solution[28]. In Figure 4, it can be seen that the
removal efficiency of Cu(II) of ISX or CSAX attained
45–55% even at pH 2; this was because the pKa value
for the xanthate-xanthic acid dissociation was reported to be 1.70 [29]. The xanthate groups existed in
470
the form of CSS– at pH 2, which could bind Cu(II)
through electrostatic attraction. When pH increased,
more xanthogenic acid groups of absorbents could
ionize to negative xanthogenic acid radical groups, so
that the chelation between xanthogenic acid radicals
and Cu2+ increased, leading to high removal efficiency
of Cu(II). When pH exceeded 4.0, the capacity of
CSAX increased still while that of ISX kept constant.
100
Removal efficiency (%)
high dosages. Hence, the following experiments on
CSAX adsorption were carried out at the adsorbent
dosage of 50 mg/L using CSAX2 as the absorbent.
The removal efficiency and adsorption capacity
are the two main characteristics for evaluating the
adsorption ability of an adsorbent. The adsorption
capacity is related to the quantity of effective functional groups, and the removal efficiency is depended
on the binding affinity between effective functional
groups and metal ions, so a high adsorption capacity
does not mean high removal efficiency. For CSAX,
there were many grafted pendant chain polyacrylamides [26], the amide groups can bind Cu(II), and
the removal efficiency of crosslinked starch-grafted
polyacrylamide(CSA) for Cu(II) was 76%. In CSAX,
there were not only amide groups but also xanthate
groups, and the append –CSS– groups increased the
removal efficiency to be above 90%. The adsorption
capacity was 567.42 mg/g for CSAX2, which was
much higher than that of 199.78 mg/g for ISX3 at their
optimal adsorbent dosages. This was attributed to
more functional groups in CSAX2，which included
amide groups on the pendant chain and xanthate
groups on the starch main chain. However, CSAX2
showed a lower removal efficiency for copper ion than
ISX3 although CSAX2 (S: 5.03%) had a much higher
surfur content than that of ISX3 (S: 2.46%). The
reasons may be: first, the binding affinity of amide
group for Cu(II) was weaker than the strong ligand
-CSS- groups, because the bond atom in –CSS–
groups was S, the chelate complex formed between
metal ions and S was very stable, and the solubility
product (Ksp) values of metal sulfides are the lowest in
all insoluble metal salts and metal hydroxides [27];
second, the steric hinderance effect of polyacrylamide
pendant chains in CSAX inhibited the chelation of
Cu(II) and –CSS– groups, and greatly reduced the
utilization of –CSS– groups, which was much lower
than that of ISX. That’s also the reason that the removal efficiency for Cu(II) reached 99.91% at high
dosages of ISX3 with only –CSS– groups.
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
90
80
70
60
CSAX
ISX
50
40
2
3
4
pH
5
6
7
Figure 4. Effect of pH on the removal of Cu(II) by
CSAX and ISX.
The effect of pH can be explained by pHpzc
values. The pHpzc of ISX and CSAX are 7.16 and
7.93, respectively. When pHs of solutions were lower
than pHpzc of ISX or CSAX, the surface of the adsorbents was positively charged and unfavorable for
binding Cu2+. Generally, the net positive charge decreased with increasing pH value and leaded to decrease in the repulsion between the sorbent surface
and metal ions, thus the adsorption capacity was
enhanced. The removal efficiency of Cu(II) of ISX or
CSAX attained 45–55% even at pH 2, indicating that
initial pH has much smaller influence on ISX or CSAX
because of the presence of strong acid xantate
groups that are difficult to be protonated. These negative groups have high affinity for the binding of positive charged metal ions, even at a relatively low pH,
probably by means of the ion exchange [30].
In order to study the probable mechanisms for
Cu(II) interaction with ISX and CSAX, concentrations
of Cu(II) and sodium were detected before and after
the absorption. When copper concentration was removed from 30 to 1.64 ppm (decreased by 0.443 mmol)
with 50 mg/L CSAX at pH 5, the simultaneous release
of sodium into the filtrate was increased from 0 to
5.89 ppm (increased by 0.256 mmol). The mole ratio
(Cu:Na) corresponding to the changes was 1:0.58,
and ionic exchanges between Cu and Na did not
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
occur in the theoretical ratio of 1:2. This can be explained as follows: the amide groups on the PAM pendant chains of CSAX can bind Cu(II) as mentioned
before, so chemical absorption also contributed to the
reaction between Cu ions and CSAX. Moreover,
some of the free metal ions possibly remained inside
the granule due to the porous and layered structure of
CSAX, interacting electrostatically with the starch
chains. Therefore chemical interactions and the physical entrapments of Cu(II) could be two additional
mechanisms for Cu(II) removal by CSAX. For ISX,
Cu(II) concentration was decreased from 30 to 0.58
ppm and meanwhile sodium concentration was increased from 0 to 9.89 ppm in the filtrate with 150 mg/L
ISX at pH 5; the mole ratio between Cu adsorbed and
Na desorbed was 1:1.9, nearly to the theoretical ratio
of 1:2, so the adsorption mechanism for Cu(II) xanthate was mainly ionic exchange.
Adsorption kinetics
The removal efficiency of Cu(II) adsorbed on
ISX and CSAX at different time are presented in
Figure 5.
Removal efficiency (%)
100
95
90
85
80
CSAX
ISX
75
70
65
0
10
20
30
t(min)
40
50
60
Figure 5. Effect of contract time of Cu(II) ions adsorption onto
ISX and CSAX.
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
The removal efficiency of Cu(II) on ISX and
CSAX increased rapidly in the initial stage, and ISX
reached equilibrium rapidly at 10 min while it was 60
min for CSAX. This indicates that Cu(II) can rapidly
chelate with the xanthate groups of ISX, and the adsorption time of CSAX was relatively long because of
the steric effect of graft macromolecules. Pseudo-first-order (Eq.(3)) and pseudo-second-order (Eq.(4))
kinetic models were applied to determine kinetic parameters and explain the mechanism of Cu(II) on ISX
and CSAX [31,32]:
Qt = Q e [1 − exp( −k 1t )]
Qt =
(3)
k 2Q e2t
1 + k 2Q et
(4)
where Qe and Qt (all in mg/g) are the adsorption
amounts of Cu(II) on the adsorbent at equilibrium and
at any time t, respectively; k1 is the rate constant of
the pseudo-first-order adsorption; and k2 is the rate
constant of the pseudo-second-order kinetics. The
experimental data before adsorption equilibrium was
used to assess the adsorption kinetics, and the calculated kinetic parameters are tabulated in Table 2.
It is clear that the correlation coefficient (R2) of
the pseudo-second-order kinetic model (0.9999 and
0.9997 for ISX and CSAX) is much higher than that of
the pseudo-first-order kinetic model (0.9768 and
0.9038 for ISX and CSAX). Besides, the adsorption
capacities calculated (Qe (cal.)) with the pseudo-second-order model (200.249 and 556.237 mg/g for ISX
and CSAX) are close to the experimental results (Qe
(exp.)) (199.124 and 558.010 mg/g for ISX and
CSAX). Therefore, the adsorption process of Cu(II)
onto ISX and CSAX followed the pseudo-second-order kinetic model for the whole adsorption process.
The similar observations were reported on the adsorption of Cu(II) from aqueous solution using adsorbents with active groups，such as phosphate group
[24], amino group [33], and hydroxyl group [34].
Table 2. Kinetic parameters for Cu(II) adsorption onto ISX and CSAX
Model
Pseudo-first-order
Pseudo-second-order
Intraparticle
Parameter
k1 / min
ISX
–1
CSAX
1.67134
0.65511
Qe / mg g–1
198.51239
527.29175
R2
0.72932
0.78051
k2 / g mg–1 min–1
0.0599
0.002337
Qe / mg g–1
200.24925
556.23766
R2
0.99721
0.9869
0.95922
20.42736
194.00207
423.7052
0.5263
0.68039
–1
ki / mg g min
C
2
R
–1/2
471
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
The adsorption capacity of CSAX was higher
than ISX, mainly due to its higher molecular mass and
more active groups on its surface as discussed
above. However, the values of k2 for ISX were much
higher than those of CSAX, indicating that the adsorption rate of ISX was faster than that of CSAX. A
reasonable explanation of that is an easier access of
the functional groups bound to Cu(II) for ISX than
CSAX.
In general, the adsorption process may be described in three steps: mass transfer from fluid phase
to the particle surface across the boundary layer, diffusion within the porous particle, and adsorption itself
onto the surface. Considering the pseudo secondorder model cannot identify the diffusion mechanism,
the intraparticle diffusion model was then tested as:
[35]:
1
Qt = k it 2 + C
(5)
where ki is the intraparticle diffusion rate constant (mg
g−1 min−1/2) and C is the intercept. The intraparticle
diffusion model was utilized to determine the ratelimiting step of the sorption process. If the regression
of qt versus t1/2 is linear and passes through the origin
(C = 0), then intraparticle diffusion is the sole ratelimiting step. In the present study, neither of plots
passed through the origin and present multilinearity,
indicating that three steps take place (figure of Qt
versus t1/2 not shown), the first, sharper portion may
be considered as an external surface adsorption or
faster adsorption stage. The second portion describes
the gradual adsorption stage, where intraparticle diffusion is rate-controlled. The third portion is attributed
to the final equilibrium stage, where intra-particle diffusion starts to slow down due to the extremely low
adsorbate concentrations in the solution [30]. The
values of R2, obtained from the plots of intra-particle
diffusion kinetics are lower than that of the pseudosecond-order model (Table 2) but this model indicates
that the adsorption of Cu(II) onto ISX and CSAX may
be followed by an intra-particle diffusion model up to
10 min. This indicates that although intraparticle diffusion was involved in the adsorption process, it was
not the rate-controlling step.
Ce
C
1
=
+ e
Q e Qmb Qm
(6)
The Freundlich isotherm model, which is valid
for multilayer adsorption on a heterogeneous adsorbent surface with sites that have different energies
of adsorption, is expressed as follows [37]:
lgQ e = lg K f +
1
n
lgC e
(7)
where Qm is the maximum adsorption amounts of
Cu(II) in aqueous solutions at equilibrium (mg/g), b is
the Langmuir constant (L/mg), and Kf (mg/g) and n
are the Freundlich constants.
The parameters of the isotherm models determined from experimental data are summarized in
Table 3. The relatively high correlation coefficients
(R2 in range 0.995-0.999) indicate that the experimental data fitted with the Freundlich isotherm model
better than the Langmuir isotherm under the studied
concentration range. The value of 1/n was less than
1, indicating favorable adsorption of Cu(II) onto ISX
and CSAX. The Freundlich constant Kf of CSAX was
higher than that of ISX, indicating that the adsorption
capacity of CSAX for Cu(II) ions was higher.
Table 3. Langmuir, Freundlich and D–R parameters for Cu(II)
adsorption onto ISX and CSAX
Model
Parameter
ISX
CSAX
Langmuir
Qm / mg g–1
466.877
2229.856
b / L mg–1
1.8243
0.0615
R2
0.9765
0.9599
Kf
222.844
240.552
1/n
0.2633
0.5183
Freundlich
2
D–R
R
0.9995
0.9978
Qm / mg g–1
130.564
12268.832
KD / mol2 Kj–2
0.00204
0.00615
15.66
9.01
0.9792
0.9802
E / kJ mol
2
R
–1
The D–R isotherm model can be applied to
distinguish between physical and chemical adsorption. The linearized D–R isotherm model can be
written as [38]:
Adsorption isotherm
lnQ e = lnQm − K Dε 2
In this study, Langmuir, Freundlich and D–R isotherm models were applied to analyze the experimental data.
The Langmuir isotherm model, which is valid for
monolayer adsorption onto a surface with finite number of homogenous sites, is expressed as follows [36]:
where KD is the constant related to adsorption energy
(mol2/kJ2); ε is the Polanyi potential, which is equal to
RTln(1+1/Ce); R is the universal gas constant (kJ/(mol
K)); T is the temperature (K). The values of Qm and KD
which were determined from the slope and intercept
of the ln Qe versus ε2 plots (figure not shown) are
472
(8)
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
listed in Table 3. The relatively high correlation
coefficients (R2 in range 0.979–0.980) reflect that the
experimental data agreed well with the D–R isotherm
model. The mean free energy of adsorption (Ea in
kJ/mol), defined as the free energy change when 1
mol of ion is transferred to the surface of the solid
from infinity in solution, can be calculated as follows:
E a = (2K D )−1/ 2
(9)
It is known that the magnitude of Ea is useful for
estimating the type of adsorption. If this value is
below 8 kJ/mol, the adsorption type can be explained
by physical adsorption; if it is between 8 and 16
kJ/mol, the adsorption type can be explained by ionic
exchange; if it is between 20 and 40 kJ/mol, it can by
explained by chemical adsorption [29]. In this study,
the value of Ea for ISX was found to be 15.66 kJ/mol,
suggesting that the adsorption of Cu(II) onto ISX was
typically an ionic exchange process; the values of Ea
for CSAX was 9.01 kJ/mol, which is near to the limit
value with 8 kJ/mol of ionic exchange and physical
adsorption, implying that the adsorption of onto CSAX
involved both ion exchange and physical adsorption.
These conclusions was in agreement with the above
analysis of the concentration changes of Cu and Na.
Through the above analysis, CSAX had the advantages of the low adsorbent dosage and high adsorption capacity while ISX had a higher removal efficiency and faster adsorption rate even though the
optimum dosage of ISX was three times as much as
that of CSAX. It should be noted that the production
cost of CSAX was relatively high due to the grafting
copolymerization and its post-processing treatment,
so ISX seemsto be a much better adsorbent compared to CSAX as far as the removal of Cu(II) was
concerned.
Treatment of water containing both turbidity and
copper ions
The original concentration of Cu(II) in copper
solution was 30 mg/L, and the adsorption experiment
was carried out at room temperature and pH with 5.3.
A certain dosage of kaolin suspension was added in
the test solution with the turbidity of 100 NTU. Different dosages of ISX and CSAX were added in the testing solutions, respectively, and the results are shown
in Figure 6. TR is defined as the turbidity removal
when water sample contains only turbidity (100 NTU);
CRt is defined as the copper ions removal when water
sample contains both turbidity (100 NTU) and copper
ions (30 mg/L); CR is defined as the copper ions removal when water sample contains only copper ions
(30 mg/L).
It was favorable for Cu(II) removal in the presence of kaolin suspension, and the effect was improved evidently with the increase of CSAX’s dosage.
The removal efficiency of Cu(II) was up to 96.98%
and turbidity removal was 98.28% at the dosage of 50
mg/L. Copper removal efficiency was much higher
than the efficiency of 94% for the sample which only
contained copper ions.
The major mechanisms of flocculation by polymers are charge neutralization and bridging. For neutral or anionic flocculants, flocculation is caused
mainly by polymer bridging [39-41]. The suspended
particulates of kaolin in the testing solution were flocculated by PAM chains on the CSAX polymer due to a
large amount of –CONH2 groups in CSAX, and the floc
had the “sweep” function for the insoluble colloidal
chelate compounds of copper with CSAX and had the
weak adsorption function for soluble copper ions.
Moreover, some of its groups would be adsorbed at
the particle surface when a CSAX polymer came into
contact with a colloidal particle, and the remainder of
Removal rate(%)
100
95
CR with CSAX
TR with CSAX
CRt with CSAX
CR with ISX
TR with ISX
CRt with ISX
90
85
80
75
0
50
100
150 200
dosage (mg/L)
250
300
Figure 6. Treatment of water samples containing both turbidity and Cu(II) with ISX and CSAX.
473
J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
the molecule (some xanthate groups) stretched into
the solution. Adsorption can occur if residual Cu(II) in
the solution contacted these extended segments by
forming a particle–polymer–chelate compound complex [42]. Furthermore, kaolin itself can work as adsorbent and can remove partially the Cu2+ from water
medium even without the addition of polymer [43].
Therefore, CSAX had good flocculation performance,
and the flocculation greatly improved the removal performance of Cu(II).
ISX’s removal efficiency of Cu(II) did not change
obviously when both turbidity and copper ions contained in water sample. The maximum removal efficiency was still 99.5% and the maximum removal
turbidity efficiency was 86% when the dosage was
150 mg/L, as same as that of the water sample which
contained only Cu(II). This was much lower than that
of CSAX. Because ISX only had starch chain as the
bridging unit, it was less effective than PAM chains for
removing turbidity.
CSAX was much more effective than ISX for
removing turbidity and little less effective than ISX for
removing Cu(II) when water sample contains turbidity
and Cu(II). Therefore, CSAX has some certain advantages in treating toxic metals effluent which contains
both heavy metals and turbidity.
Table 4. Comparison of maximum sorption capacity of other
xanthated sorbents
Adsorbent
Qmax / mg g-1
Reference
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
onto CSAX was determined by the contents of N and
S while that of ISX was only related with the content
of S. The absorption capacity of CSAX was much
bigger than that of ISX while the removal efficiency of
ISX was higher than CSAX.
2) The adsorption efficiency of Cu(II) onto CSAX
and ISX increased with the increased dosage. Their
adsorption kinetic process was well predicted by the
pseudo-second-order model. Their equilibrium adsorption data fitted well with the Freundlich and D–R
isotherm models, and the 1/n value for Freundlich
isotherm showed that Cu(II) were favorably adsorbed
by the CSAX or ISX.
3) The physical process and ions exchange process both contributed to the adsorption of Cu(II) onto
CSAX, whereas the adsorption mechanism of Cu(II)
for ISX was mainly the ion exchange.
4) Turbidity was favorable for the Cu(II) removal
by CSAX. CSAX seems to be a worthwhile alternative
to the traditional ISX in the process of treating
wastewater containing both copper ions and turbidity.
Acknowledgements
This work was financially supported by the Science and Technology Plan Projects of Jiaxing City,
China (NO.2014AY21008), the Hi-Tech Research and
Development Program of China (No. 2012AA06A304),
the Platform Funds from Zhejiang Province (No.
2012F10028), the Research Project for Application of
Public Technology of Zhejiang Province of China (No.
2012C31028), and the research funds from Nanhu
College of Jiaxing University (No. N41472001-3).
Orange peel xanthate
77.60
[44]
Xanthated sugarcane bagasse
2.91
[45]
Xanthate-modified magnetic
chitosan
34.5
[46]
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J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE…
JUN TAN1,2
XIAOYAN WEI1
1
YUXIA OUYANG
2
RUI LIU
1,2
PING SUN
JUHONG FAN3
1
Department of Chemical and Textile
Engineering of Nanhu College, Jiaxing
University, Jiaxing, Zhejiang Province,
China
2
College of Biological and Chemical
Engineering, Jiaxing University,
Jiaxing, Zhejiang Province, China
3
Zhejiang Provincial Key Laboratory of
Water Science and Technology,
Department of Environment, Yangtze
Delta Region Institute of Zhejiang,
Jiaxing, Zhejiang Province, China
NAUČNI RAD
Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)
EVALUACIJA NERASTVORNOG KSANTATA I
UMREŽENOG SKROBA SA KALEMLJENIM
KOPOLIMEROM POLIAKRILAMIDA I NATRIJUM-KSANTATA ZA ADSORPCIJU Cu(II) U VODENIM
RASTVORIMA
U ovom radu je procenjena efikasnost nerastvornog ksantata (ISX) i umreženog skroba sa
kalemljenim kopolimerom poliakrilamida i natrijum-ksantata (CSAX) za uklanjanje Cu(II)
jona iz otpadnih voda. Dve vrste ksantata su okarakterisane elementarnom mikroanalizom,
kao i SEM, XRD i FTIR metodama. Analizirani su i faktori koji utiču na adsorpcione karakteristike jona bakra iz vodenog rastvora. Rezultati su pokazali da CSAX poseduje bolji
adsorpcioni kapacitet za Cu(II) od ISX, s obzirom na to da sadrži više azota i sumpora. S
druge strane, što se tiče efikasnosti izdvajanja Cu(II) jona, ISX je bolji od CSAX zbog
sadržaja jakih –CSS grupa. Uklanjanje jona bakra kod obe vrste ksantata se povećava sa
povećanjem pH rastvora. Mehanizam Cu(II) adsorpcije na ISX je jonska izmena, dok su
jonska izmena i fizička adsorpcija odgovorne za adsorpciju kod CSAX. Kinetika adsorpcije
kod oba adsorbenta odgovara modelu pseudo-drugog reda, a asdorpcione izoterme odgovaraju Freundlich izotermama. Ispitivanje sa sintetičkim otpadnim vodama ukazuje na
CSAX kao korisnu alternativu tradicionalnom ISX u slučaju kada otpadna voda sadrži i
Cu(II) jone i zamućenje.
Ključne reči: nerastvorni skrobni ksantat, umreženog skroba sa kalemljenim
kopolimerom poliakrilamida i natrijum-ksantata, uklanjanje Cu(II), kinetika adsorpcije, adsorpciona izoterma.
476
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
OGBEMUDIA JOSEPH
OGBEBOR1
FELIX EBHODAGHE
OKIEIMEN2
DAVID EHIOGHILEN
OGBEIFUN2
UZOMA NDUBUISI OKWU1
1
Research Support Services
Department, Rubber & Gum
Tech./Quality Control Division,
Rubber Research Institute of
Nigeria, Benin City, Nigeria
2
University of Benin, Department of
Chemistry, Center for Biomaterials
Research, Benin City, Nigeria
SCIENTIFIC PAPER
UDC 666.321.09:678.4:544
DOI 10.2298/CICEQ140221003O
CI&CEQ
ORGANOMODIFIED KAOLIN AS FILLER FOR
NATURAL RUBBER
Article Highlights
• Increased interlayer spacings
• ts2, t90, ML and MH were affected
• High acceleration of cure at 2 and 4 phr loading
• M300, TS and elongation at break improved
• Abrasion resistance and IRHD showed similar trends like tensile properties
Abstract
Organokaolin samples, through the incorporation of cationic hexadecyltrimethylammonium bromide in various concentrations (50, 100 and 200% cation
exchange capacity, CEC) into kaolin clay’s interlayer spaces have been prepared. The samples were characterized using XRD and FTIR to get information on structural composition and characteristic bonds on modification.
These clays were further used as fillers in natural rubber compounds with a
semi-ultra-delayed action accelerator scheme. The X-ray diffraction analysis
showed marginal increase in basal (d(001)) spacing of kaolin platelets from 4.01
to 4.90 nm. Changes in the clay’s molecular environment induced by ion-exchange process were followed by FTIR measurements revealing various
CTAB+ influenced absorption peaks as modification progressed. Cure characteristics, scorch (ts2) and cure (t90) time of the organokaolin filled natural rubber composites were observed to be better than those of the 40 phr bulk kaolin
across the CEC organophilization concentrations and filler loadings studied.
Vulcanizate properties showed considerable increase in M100, M200, M300,
TS and elongation at break (%) indicating its potential as an organomodified
filler. Hardness (IRHD) and abrasion resistance showed similar trend as tensile
properties, with the incorporation of organoclay.
Keywords: organokaolin, hexadecyltrimethylammonium bromide, organophilization, X-ray diffraction, cure properties, vulcanisate properties.
Clays are important raw materials, with estimated consumption of over 1,600,000 t consumed as
fillers [1]. They have found uses in the polymer, paint,
paper, etc. industries as non-black fillers [1,2]. Clays
are natural minerals comprising of certain groups of
hydrous aluminum, magnesium and iron silicates that
may contain sodium, calcium, potassium, and other
ions. These silicates are called the clay minerals, the
major clay mineral groups are kaolins, smectites, illites, chlorites and hormites. Kaolins are used to greatCorrespondence: O.J. Ogbebor, Research Support Services
Department, Rubber & Gum Tech./Quality Control Division,
Rubber Research Institute of Nigeria, Benin City, Nigeria.
E-mail: ojo0001@yahoo.com
Paper received: 21 February, 2014
Paper revised: 9 January, 2015
Paper accepted: 27 January, 2015
est extent (54%) when compared to other non-black
fillers. They are used as non-black fillers in polymers
to cheapen and modify processing by reducing nerve
in shaping operations and ensuring dimensional stability in unvulcanized stocks at high loadings > 40 wt.%
[3]. Kaolins have also been used to aid smooth plastic
surface, improve electrical resistance in wire and
cable coatings and helps control flow properties in
polishing compounds [4]. Recently, organomodified
clays emerged as novel class of reinforcing fillers for
the reinforcement of polymers. A unique feature of
these materials is their ability to impart a rare combination of properties to the base polymer at low loadings < 10 wt. % [4,5]. This means that superior performance can be realized with significant weight
savings. These composites are developed through
477
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
either in situ polymerization, direct solution intercalation of the organically modified layered silicate, or
melting intercalation into the polymer matrix.
Organic modification intercalates are formed
when clay is put in aqueous surfactant solutions, for
example quaternary ammonium surfactants having
long hydrocarbon chain, e.g., hexadecyltrimethylammonium bromide, CTAB, etc. This leads to an increase in interlayer spacing, which can be estimated
by X-ray diffraction (XRD) [5-10]. Also, the extent of
swelling of clay is said to be dependent on the length
of the alkyl chain and the cation exchange capacity
(CEC) [12]; hence, the choice of surfactant could
facilitate the level of modification of kaolin clay material. A review of literature on organomodified fillerpolymer composites showed that montmorillonite
(bentonite) has been studied extensively [5–13]. But
as the natural deposits of montmorillonite minerals
are rather limited and the demand for bentonites ever
increasing, there has been considerable interest in
finding substitute mineral. In this context, only limited
information is available with the relatively less expensive and abundantly available mineral like kaolin
[14,15]. Kaolin consists chiefly of the mineral kaolinite
and is abundantly available. Its low cost encourages
its industrial utility.
Kaolinite [Al4Si4O10(OH)8] is a dioctahedral aluminosilicate, 1:1 layered clay mineral, built with a
tetrahedral SiO4 sheet and an octahedral AlO4(OH)2
sheet linked together by oxygen atoms. The crystal
consists of several of these layers extending in a twodimensional array, which are stacked along the c-axis
and held together essentially by: i) hydrogen bonds
between the external hydroxyls of the octahedral
sheet and the basal oxygen of the adjacent layer
tetrahedral sheet, ii) van der Waals attractive forces,
and iii) electrostatic interactions due to net fractional
charges of opposite sign on each basal surface.
Although, the surface silicate sheet of kaolinite is not
usually amenable to covalent attachment, the relatively reactive aluminol surface is similar to that in the
case of montmorillonopkites and has the potential to
be functionalized via Al–O–R bonds. Organoclays are
particularly explored as matrix-reinforcing components for their high aspect ratio, plate morphology,
natural availability and low cost to develop [14]. There
is however, a dearth of information in the literature on
organic modification intercalates developed from kaolin in clay-aqueous surfactant solutions unlike montmorillonite. In view of the foregoing, this study examines 50, 100 and 200% CEC modification of hexadecyltrimethylammonium bromide on the basal spacing of kaolin using X-ray diffraction (XRD), its effects
478
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
on composition, structure, characteristic bonds on the
clay’s molecular environment observed using Fourier
Transform Infrared Spectroscopy (FTIR). The
modified clays were then applied as fillers in natural
rubber compounds in a semi-ultra-delayed action
accelerator, and filler (2, 4, and 8 phr) effects on cure
and mechanical properties of the natural rubber
compounds were evaluated.
EXPERIMENTAL
Clay samples were collected from exposed
faces of deposit situated on long. 06°39'5.3" E and
lat. 6°13'39.2" N, purified by water washing through
75 µm mesh size and its composition (by weight was:
SiO2 32.11%, Al2O3 21.40%, TiO2 4.30%, Fe2O3
1.72%, K2O 0.64%, MgO 6.48%, CaO 15.20%, Na2O
0.56%. The modification of clay with hexadecyltrimethylammonium bromide (CTAB) was carried out
using the procedure: 1.5 g of purified clay dispersed
in 94 ml of distilled water, stirred with magnetic stirrer
for about 3 hrs at 80 °C. 0.5 g of hexadecyltrimethylammonium bromide (C4H9N+ (CH2CH2OH)2Br) was
dissolved in a mixture of distilled water and concentrated hydrochloric acid (35%) at 80 °C with 1 h of
stirring. The pre-dissolved intercalating agent was
then added to the clay suspension at 80 °C. The
concentrations of the intercalating agent were in 50,
100 and 200% CEC of the clay. The reaction mixtures
were stirred vigorously for 1 h at 80 °C. This was then
washed copiously with water until filtrate was about
pH 7, and dried at 70 °C for 24 h and ground in a
mortar and stored in vacuum desiccators for five days
before analysis [6]. XRD of samples was carried in a
monochromatic MD 10 mini-diffractometer, with
Ni-filter CuKα radiation in the 2θ region of glancing
angle 15-75° and automatic silt. All recordings were
taken at room temperature. The spacing was calculated using Bragg’s Wulf equation, nλ = 2d sinθ,
where λ is the wavelength of monochromatic X-ray
source, d is the spacing between two similar planes, θ
is the angle at which X-ray falls on the sample, and n
is the order of reflection. IR spectroscopy is used in
order to give information as far as composition of a
sample, its structure and its characteristic bonds are
concerned. In addition, IR spectroscopy is applied on
clay minerals in order to study the nature of isomorphic substitutions of cations in octahedral and tetrahedral sheet of the lattice and the degree of crystallinity. IR was carried out on the clay samples using
an FTIR machine in a universal demountable cell and
scanned at a range of 350–4000 cm-1 using the Spectrum BX system (Perkin–Elmer, England).
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
Preparation of compounds
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
RESULTS AND DISCUSSION
Mixes were prepared as in a laboratory two roll
mill (Banbury-Pullen, model, 35100). The mill opening
was set at 1.4 mm, and the initial temperature was set
at 80±5 °C. The mixing involved two stages of operation. The first step features an initial banding of natural rubber on the front roll of the two-roll mill, followed by ¾ cuts on both sides of the band, followed
by adding half content of organokaolin, then zinc
oxide, stearic acid, paraffin oil and wax, allowed to
mix properly for 5 min. This was followed by the
incorporation of the remaining ingredients and 6PPD
for a further 3.5 min. In the final step, the addition of
accelerator and vulcanizing agents (CBS and sulphur)
for 2.0 min was done after the stock was allowed to
cool to 70 °C, as shown in Table 1. The rheological
behavior of the rubber compounds was determined
on Alpha oscillating disc rheometer (ODR 2000) using
a 1° rotor oscillating amplitude and frequency 50 Hz
[16]. The cure rate index (CRI) and other parameters
of cure were estimated from the obtained rheographs.
Tensile specimens were cut from the moulded sheets,
according to BS 903, Part A2 (DIN 53504) [17]. Tensile properties: M100, M200, M300, tensile strength
and elongation at break (%) were determined at room
temperature on a Zwick/Roell Z005 testing machine
with crosshead speed of 200 mm/min. The abrasion
test was carried out in accordance to BS 903, Part A9
[18], consisting of a trial run, a running-in period and
five test runs. Absolute value of abrasion was the
mean value calculated from the five test runs expressed in mg per 1000 revolutions of the abrasive wheel.
Hardness tests of the rubber vulcanizate were determined in accordance to BS 903 (ISO 7619) [19], with
an international rubber hardness tester.
X-ray diffraction was used to observe the clay
materials before and after modification with CTAB.
The XRD of bulk clay and modified clays are depicted
in Figure 1. The interaction between kaolin clay and
CTAB organic compound resulted in a shift of the dspacing d(001) towards lower 2θ values of the kaolin
clay material implying the expansion of the interlayer
spaces due to the surfactant. Table 2 shows the various glancing angles 2θ and d(001) spacing of the
unmodified kaolin and the modified kaolin at 50, 100
and 200% CEC, respectively. While unmodified kaolin
is 4.01 nm, those modified show increased d-spacing
as modification progressed, hence 4.37, 4.46 and
4.90 nm for 50, 100 and 200% CEC modifications.
The interaction between the clay and the surfactant
led to the observed changes in the d-spacing, implying the expansion of the interlayer space due to the
alkylammonium intercalation. Basal spacings reflect
the proportion of the interlayer occupied by the
amphiphilic substances. For this reason, the gallery
spacing gradually increases, depending on the amount
of CTAB interacted with the layered silicate [20]. Also,
depending on the alkylammonium packing density
and alkyl chain length (CTAB+), the carbon chain can
Table 1. Formulations for investigated organokaolin filled natural rubber compounds; 6PPD: N-(1,3-dimethylbutyl)–N’-phenylp-phenylenediamine; CBS: N-cyclohexyl-2-benzothiazole sulfonamide
Compound component
Parts hundred rubber (phr)
Natural rubber
100
100
100
100
100
Paraffin oil
10
10
10
10
10
Organomodified kaolin
0
2
4
8
-
Bulk kaolin
-
-
-
-
40
Zinc oxide
10
10
10
10
10
Stearic acid
2
2
2
2
2
6PPD
1.5
1.5
1.5
1.5
1.5
Wax
1.5
1.5
1.5
1.5
1.5
CBS
0.6
0.6
0.6
0.6
0.6
Sulphur
2.8
2.8
2.8
2.8
2.8
Figure 1. XRD diffractograms showing: A – bulk kaolin, B – 50%
CEC-CTAB kaolin, C – 100% CEC-CTAB kaolin and D – 200%
CEC-CTAB kaolin.
479
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
be arranged in the kaolin interlayer spaces, forming
either monolayers or bilayers parallel to the clay surface [11]. These changes in arrangements are
detected in the clay basal spacing.
Table 2. Glancing angles (2θ) and interplanar spacings, d, of
X-rays reflections from lattices of organokaolin
Kaolin
Organokaolin
50%
100%
200%
2θ / °
d / nm
2θ / °
d / nm
2θ / °
d / nm
2θ / °
d / nm
36.06
4.01
25.21
4.37
19.87
4.46
18.09
4.90
43.45
3.48
26.44
3.35
20.37
3.36
18.87
4.70
45.57
3.27
26.97
3.30
25.27
3.52
19.73
4.50
49.95
2.49
36.95
2.43
26.38
3.37
22.45
3.95
55.33
2.32
38.44
2.34
27.04
3.29
23.30
3.81
57.81
1.83
38.87
2.31
36.45
2.46
25.06
3.55
62.92
1.66
39.55
2.27
38.79
2.32
33.33
2.68
63.42
1.48
39.80
2.26
39.58
2.27
35.06
2.55
FTIR spectra of bulk and modified clay are
shown in Figure 2. Table 3 shows the absorption
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
peaks in cm-1 of these clay materials. Knowledge of
organoclay characteristics is essential to optimizing
the applications of the materials. Especially in the
case of polymer-clay composites, the mechanism that
controls the clay dispersibility into the polymer matrix
is related to these characteristics and is of fundamental importance in the design of materials with
desired properties [21]. These spectra reveals that as
modification with CTAB+ progressed the absorption
peaks increased with accompanied broadening and
shift of absorption positions, changes in band contours associated with changes in the isomorphic substitutions of the cations in the octahedral and tetrahedral sheet of the clay lattice. Furthermore, matching
the absorption peaks with infrared spectroscopy correlation table [22,23], the changes in the clay molecular environment lead to peaks of 1652 cm-1 of the
bulk clay to absorption peaks 3434, 3457 and 3667
cm-1 for the 100 and 200% CEC-CTAB modifications,
indicating a growing presence of amide (CONH2),
amine (NH2C, CNHC and CNCC), etc. groups with
Figure 2. FTIR Spectra of: A – bulk kaolin, B – 50% CEC-CTAB kaolin, C – 100% CEC-CTAB kaolin, D – 200% CEC-CTAB kaolin.
Table 3. FTIR absorption peaks (cm-1) of organokaolin samples
Bulk kaolin
1652, 1036, 925, 683, 547, 458
50 % CEC-CTAB kaolin
1646, 1038, 928, 680, 548, 458
100% CEC-CTAB kaolin
3667, 3457, 2348, 1638, 1032, 925, 677, 539, 444
200% CEC-CTAB kaolin
3667, 3434, 2931, 2348, 1934, 1823, 1638, 1475, 1037, 925, 669, 542, 432
480
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
pronounced multiple broad peaks, which are associated with ammonium ion absorption because of N–H
stretching vibrations. The 2348 cm-1 characteristic of
strong NH3+ stretching band was observed in the 100
and 200% CEC-CTAB clay, with an additional 2931
cm-1 strong absorption NH3+ stretching band in 200%
CEC-CTAB clay. The overlap aliphatic amine of 1032
cm-1 and conjugation C=O effects 1638 cm-1 absorption were also noticed in the 100% CEC-CTAB clay,
whereas the 1823cm-1 absorption peak for acyl halide
(C–Br), 1638cm-1 (C=O effects), 1475 cm-1; strong primary amine (N–H), and 1037 cm-1 (overlap aliphatic
amine) were noticed in the 200% CEC-CTAB clay
spectrum. The 539, 542 and 677 cm-1 absorption
peaks were indicative of the presence of bromoalkanes (C–Br) whereas the 925 cm-1 of 200% CEC-CTAB
clay was C=CH, vinyl bond type presence. However,
the 1934 cm-1 of 200% CEC-CTAB clay was not available in the spectroscopy tables used (this will be investigated in subsequent studies).
In design of rubber products formulation, two of
the most critical properties of rubber and rubber compounds are processibility and vulcanization. These
characteristics are vitally important because they
define the operating window available for converting
uncured rubber compound into a usable product. The
processibility of stock can be followed by monitoring
cure properties of rubber compounds. Cure properties
of natural rubber compounds containing unmodified
and modified clay material are given in Table 4.
Scorch time, ts2, increased from 2.9, through 3.7 and
3.8 min at 2 phr filler of the 50, 100 and 200% CEC
level of modification. The 4 phr indicates 2.8 min, 3.3
min, and 3.3 min at 50, 100 and 200% modifications
respectively. At 8 phr loadings, it was 3.7, 3.2 and 3.0
min for the 50, 100 and 200% CEC modifications.
Scorch is a valuable assessment of the compounding
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
recipe as it indicates compounds processing safety.
The various organokaolin composites show better
scorch time when compared to that of the control bulk
clay at loading of 40 phr, which indicated 2.2 min.
Cure time (t90) as depicted in Table 4 on the other
hand is the time required during the vulcanization for
crosslinking to occur, yielding the desired level of properties can be seen to be generally better for most of
the organokaolin composites across the CEC concentrations than that of the 40phr bulk clay (control filler
level). This acceleration of cure as a result of the
increased presence and interaction of the organokaolin with natural rubber polymer was also observed
in the study of Lopez-Manchado et al. [11] on substituting carbon black with organomontmorillonite in
NR compounds and Teh et al. [24] on natural rubber/organoclay nanocomposites compatibilized with
epoxidized natural rubber. The absolute torque level,
Tmax, increased as the organokaolin loading increased
with modification % increase, indicating a gradual increase of crosslinking (resulting in the compound
changing from a soft plastic to a tough elastic material
required for its end use) as organokaolin increased.
The torque maximum (MH) increased across the filler
levels 2, 4, and 8 phr and the 50, 100 and 200%
CEC-CTAB modifications. This increase in viscosity
could have been encourage by heat, which led to
exfoliation of the polymer in the presence of the organokaolin as a result of the growing presence of the
CTAB+ in the clay platelets, thereby improving interactions of the rubber molecules with clay leading to
improved properties. It is known that the amount of
bound rubber on reinforcement increases due to
mechanical breakdown of polymer chain molecules
and results in free radicals formation at newly formed
chain ends; these becomes reactive sites for the filler
surface and these free radicals from the polymer
Table 4. Cure properties at 150 ºC of organokaolin filled natural rubber compounds; Tmax: absolute torque level (T90+ML), ML: torque
minimum, MH: torque maximum, CRI: cure rate index, 100/(t90–ts2)
Filler loading, phr
0
Parameter
2
2
2
4
4
4
8
8
8
40
CEC-CTAB level, %
0
50
100
200
50
100
200
50
100
200
-
ts1 / min
2.3
2.4
3.5
3.7
2.7
3.2
3.3
3.0
3.0
3.5
2.2
ts2 / min
2.5
2.9
3.7
3.8
2.8
3.3
3.3
3.7
3.2
3.0
2.6
t90 / min
4.4
4.6
5.0
5.6
4.3
5.7
5.5
5.2
5.8
6.0
4.6
Tmax
6.5
6.7
6.9
8.0
6.6
8.2
8.3
7.4
8.1
8.8
14.5
CRI
52
56
63
53
51
45
46
59
79
89
56
ML / kg cm3
2.1
2.1
1.9
2.4
2.3
2.5
2.8
2.2
2.3
2.8
10.1
MH / kg cm
MH-ML
3
27
30
31
32
32
34
36
34
36
40
36.4
24.8
27.9
29.2
30
29.8
31.5
33
31.8
33.4
36.7
26.4
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O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
result in bound rubber. Since there are many sites on
a filler particle, it then acts as a giant crosslink. This
bound rubber, when considered as part of the volume
occupied by the filler, influences the hydrodynamic
properties such as viscosity of the rubber.
Table 5 gives the tensile properties; M100,
M300, tensile strength and elongations at break of the
various investigated organokaolin in natural rubber
compounds. As expected M100, M300 and tensile
strength, TS in MPa indicated reasonable increase as
the filler level (2, 4 and 8 phr) and CEC-CTAB (50,
100 and 200%) modifications were compared to the
unfilled compound and the 40 phr natural rubber compounds respectively. At 2 phr the M100 were 50%;
1.4 MPa, 100%; 1.8 MPa and 200%; 3.3 MPa as
against the 0.9 MPa of the unfilled and 1.3MPa of 40
phr bulk clay in natural rubber compounds. Similar
increase was also observed at loadings of 4 phr: 50%;
1.7 MPa, 100%; 1.9 MPa, 200%; 3.6 MPa and 8 phr:
50%; 2.2 MPa, 100%; 2.8 MPa and 200%; 4.1 MPa.
The increase in tensile modulus may be considered
as a direct indication of the reinforcing effect of organokaolin filler. This can be taken as the dispersibility
effect of the organokaolin in the NR matrix. Organoclay platelets have been reported to possess high
aspect ratios [24] and thus act as good reinforcing
elements, taking into cognizance a good filler-rubber
interaction. The ammonium intercalant hexadecyltrimethylammonium bromide of the organoclay likely
facilitates the disintegration of the layered clay particles. The resulting exfoliations improved mechanical
properties. Similarly, increase in tensile modulus has
been reported for different NR hybrids containing low
dosages of organomodified montmorillonite clays
[8,11,14,24]. At M300, which is 300% strain and a
measure of stiffness of rubber composites were at 2
phr: 50, 100 and 200% – 3.6, 4.2 and 5.1 MPa, and 4
phr: 50, 100 and 200% – 3.2, 4.4 and 5.4 MPa and 8
phr: 50, 100 and 200% – 3.9, 4.9 and 6.8 MPa, indicating an increase with filler content and polymer
exfoliation. Elongation at break (%) of the natural
rubber composites were observed to become low as
filler levels and modification concentrations increased
across the studied compounds when compared to the
unfilled and 40 phr of bulk clay. This is believed to be
due to the exfoliation of the polymer with the organokaolin that causes higher crosslinking of the rubber in
the neighborhood of the organoclay platelets [25].
The increment in crosslinking resulted in a reduction
in elongation at break. The reduction in elongation is
believed to be caused by an increasing tendency for
clay agglomeration as filler loading increase [8]. Hardness (IRHD) increased as the tensile properties increased. Abrasion (mg/1000 rev.) also increased as
the loading level and the CEC-CTAB modification
concentrations increased. This increase is also analogous to that reported for NR organocomposites containing onium ion modified montmorillonite [24] and
montmorillonite modified with octadecylamine [26].
The reinforcement effect of CTAB modified kaolin clay
as evidenced by the increase in tensile modulus, tensile strength, hardness and abrasion may be explained by the possible formation of structure between
organokaolin and NR. It is quite possible that there
are interactions between the cations and silanol hydroxyl groups of kaolin and the ammonium (NH4+) of
CTAB resulting in sufficient intercalation of the additive between the clay platelets. This, in turn, could
increase the hydrophobicity of kaolin leading to
further polymer (natural rubber) exfoliating effect that
could result in the observed reinforcing effect in the
natural rubber compounds studied.
Table 5. Mechano-physical properties of organokaolin filled natural compounds; EB: elongation at break; IRHD: international rubber
hardness degrees
Filler loading, phr
Parameter
0
2
2
2
4
4
4
8
8
8
40
CEC-CTAB level, %
0
50
100
200
50
100
200
50
100
200
-
M100 / MPa
0.9
1.4
1.8
3.3
1.7
1.9
3.6
2.2
2.8
4.1
1.3
M300 / MPa
2.3
3.6
4.2
5.1
3.2
4.4
5.4
3.9
4.9
6.8
1.8
TS / MPa
14.2
22.4
26.4
32.2
23.3
28.5
37.4
28.4
34.8
42.4
18.2
EB / %
321
256
229
233
201
196
185
270
245
178
265
IRHD
41
43
44
46
47
48
49
51
54
56
55
Abrasion, mg/1000 rev.
0.29
0.34
0.35
0.37
0.45
0.46
0.48
0.40
0.45
0.52
1.52
M100 / MPa
0.9
1.4
1.8
3.3
1.7
1.9
3.6
2.2
2.8
4.1
1.3
M300 / MPa
2.3
3.6
4.2
5.1
3.2
4.4
5.4
3.9
4.9
6.8
1.8
482
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
CONCLUSION
[8]
R. Alex, C. Nah. J. Appl. Polym. Sci. 102 (2006) 3277-3285
Kaolin clay has been modified using hexadecyltrimethylammonium bromide (cationic surfactant) at
50, 100 and 200% CEC concentrations, resulting in
organokaolin. From the study, XRD reveals there was
an increase in basal spacing between the clay layers
because of intercalation. FTIR spectra show increasing absorption peaks arising from the effects of
the CTAB+ on the kaolin clay platelets. Rheological
analysis shows that kaolin has potential in the organomodification quest, as CTAB-kaolin imparted
reasonably on the cure properties of natural rubber
composites studied. The organokaolin gave rise to
higher degree of crosslinking as a result of polymer
chain exfoliation, thereby resulting in the considerable
increase in mechano-physical properties, which were
observed across the CEC concentrations. The results
above have shown that the surfactant treatment of the
kaolinitic silicate allows the dispersion of silicate
layers into the matrix of NR and improves the filler-matrix compatibility and hence improved natural rubber compound properties.
[9]
H. Yang, X. Zheng, W. Huang, K. Wu, Biointerfaces 65
(2008) 281-284
[10]
L. Zhou, H. Chen, X. Jiang, F. Lu, Y. Zhou, W. Yin, X. Ji,
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[11]
M.A. López-Manchado, M. Arroyo B. Herrero, Polymer 44
(2003) 2447-2453
[12]
D.R. Paul, Q.H. Zeng, A.B. Yu, G.Q. Lu, J. Colloid
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[13]
S.J. Ahmadi, C. G’sell, Y. Huang, N. Ren, A. Mohaddespour, J. Hiver. Comp. Technol. 60 (2009) 2566-2572
[14]
R. Sukumar, A.R.R. Menon. J. Appl.Polym. Sci. 107
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[15]
L.E. Yahaya, K.O. Adebowale, A.R.R. Menon, B.I. Olu-Owolabi, Am. J. Mat. Sci. 2 (2012) 1-5
[16]
ISO 3417 (2000-E) Rubber – Measurement of Vulcanisation Characteristics Disc Rheometer
[17]
British Standards Institute, BS 903; Part A2: Determination of Tensile Stress-Strain Properties (DIN 53504)
[18]
British Standards Institute, BS 903; Part A9: Determination of Abrasion Resistance
[19]
British Standards Institute, BS 903, Part A57: Determination of Hardness (ISO 7619)
[20]
A. Gürses, M. Ejder-Korucu, and Ç. Doğar, Sci. World J.
(2012) 1-8
[21]
P.C. LeBaron, Z. Wang, T.J. Pinnavaria, Appl. Clay Sci.
15 (1999) 11-18
REFERENCES
[1]
H.H. Murray, Clay Sci. 12 (2006) 106-112
[2]
H.H. Murray, in E. Dominguez, G. Mas, F. Gravers, Eds.,
A Clay Odessey, Elsevier, Amsterdam, 2003, pp. 3-10
[22]
[3]
N.G. McCrum, C.P. Buckley, C.B. Bucknall, Principles of
Polymer Engineering, Oxford Univ. Press, New York,
2010, p. 283
G. Socrates, Infrared and Raman characteristic Group
frequencies: Tables and charts, John Wiley and Sons,
New York, 2004, p. 18
[23]
P. Larkin, Infrared and Raman Spectroscopy: Principles
and Spectral Interpretation. Elsevier, Amsterdam, 2011,
p. 5
[24]
P.L. Teh, Z.A. Mohd Ishak, A.S. Hashim, J. Karger-Kocsis, U.S. Ishiaku. J. Appl. Polym. Sci. 100 (2006)
1083-1092
[4]
H.H. Murray and J.E. Kogel, Appl. Polym. Sci. 29 (2005)
199-206
[5]
A.K. Kulshreshtha, A.K. Maiti, M.S. Choudhary, K.V. Rao,
J. Appl. Polym. Sci. 99 (2006) 1004-1009
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B. Zidelkheir, M. Abdelgoad. J. Therm. Anal., Calorim. 94
(2008) 181-187
[25]
R.S. Peila, G. Lengvinaite, Malucelli, A.Priola, S.
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(2001) 260-266.
483
O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER…
OGBEMUDIA JOSEPH
OGBEBOR1
FELIX EBHODAGHE OKIEIMEN2
DAVID EHIOGHILEN OGBEIFUN2
UZOMA NDUBUISI OKWU1
1
Research Support Services
Department, Rubber & Gum
Tech./Quality Control Division, Rubber
Research Institute of Nigeria, Benin
City, Nigeria
2
University of Benin, Department of
Chemistry, Center for Biomaterials
Research, Benin City, Nigeria
NAUČNI RAD
Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)
ORGANO-MODIFIKOVANI KAOLIN KAO PUNILAC
PRIRODNOG KAUČUKA
U radu je pripremljen organokaolin, postupkom inkorporiranja katjonskog heksadeciltrimetilamonijum-bromida u različitim koncentracijama (sa kapacitetom katjonske izmene 50,
100 i 200%, CEC) u međuslojeve kaolinske gline. Karakterizacija dobijenog kaolina je izvršena korišćenjem XRD i FTIR metoda, da bi se dobila informacija o strukturi uzorka i
karakterističnim vezama koje se formiraju pri modifikaciji. Ovako dobijena glina je dalje
korišćena kao punilac prirodnog kaučuka po šemi odloženog delovanja polu-ultra akceleratora. XRD analiza pokazuje marginalno povećanje u bazalnom (d(001)) razmaku pločica
od 4.01 do 4.90 nm. Promene u molekularnom okruženju gline, uslovljene jonskom izmenom, praćene su FTIR analizom, uz uočavanje velikog broja CTAB+ absorpcionih pikova
kao posledice same modifikacije. Svojstva umrežavanja, vreme pečenja (ts2) i umrežavanja (t90) kompozita prirodnog kaučuka i organokaolina kao punioca su bila bolja od svojstava smeša kaolina i kaučuka (40 phr) u opsegu korišćenih kapaciteta jonske izmene i
količine punioca. Osobine vulkanizata su značajno povećane kod M100, M200, M300, TS i
istezanja kod prekida (%), što ukazuje na njegove značajne osobine kao organo modifikovanog punioca. Inkorporacija organogline utiče na tvrdoću i otpornost na abraziju u
istom trendu kao i na zatezna svojstva.
Ključne reči: organokaolin, heksadeciltrimetilamonium-bromid, organofilizacija,
X-ray difrakcija, svojstva umrežavanja, osobine vulkanizata.
484
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
VESNA M. PAVELKIĆ1
TANJA P. BRDARIĆ2
MARIJA P. PETROVIĆ3
GAVRILO M. ŠEKULARAC1
MILICA G. KOŠEVIĆ1
LATO L. PEZO4
MARIJA A. ILIĆ5
1
Institute of Chemistry, Technology
and Metallurgy, University of
Belgrade, Belgrade, Serbia
2
Vinča Institute of Nuclear
Sciences, University of Belgrade,
Belgrade, Serbia
3
Institute "Kirilo Savić", Belgrade,
Serbia
4
Institute of General and Physical
Chemistry, Belgrade, Serbia
5
Faculty of Mining and Geology,
University of Belgrade, Belgrade,
Serbia
SCIENTIFIC PAPER
UDC 66.093.48:634.13:544.4
DOI 10.2298/CICEQ141014004P
CI&CEQ
APPLICATION OF PELEG MODEL ON MASS
TRANSFER KINETICS DURING OSMOTIC
DEHYDRATATION OF PEAR CUBES IN
SUCROSE SOLUTION
Article Highlights
• Mass transfer kinetics during osmotic dehydration process of pears in sucrose solution
was studied
• Peleg model was applied to the experimental data to describe sorption kinetics curves
• The equilibrium values for moisture and solid content were estimated using Peleg
equation
• Peleg rate constants for WL and SG at all temperatures followed an Arrhenius type
relationship
Abstract
The applicability of Peleg model was investigated for predicting mass transfer
kinetics during the osmotic dehydration (OD) process of pears, at different
concentrations (40, 60 and 70%, w/w) and temperatures (20, 35 and 50 °C) of
sucrose solution. Increase in sucrose solution concentration resulted in higher
water loss (WL) and solid gain (SG) values through the osmotic treatment
period. After 360 min of osmotic treatment of pears, WL ranged from 23.71 to
31.68% at 20 °C, from 24.80 to 40.38% at 35 °C and from 33.30 to 52.07% at
50 °C of initial weight of pears. The increase of dry mass of the samples, SG,
after 360 min of osmotic treatment ranged from 3.02 to 6.68% at 20 °C, from
4.15 to 7.71% at 35 °C and from 5.00 to 8.92% at 50 °C. Peleg’s rate constants, k1WL and k1SG, decreased with increasing temperature, as well as decreased with increasing concentration of osmotic solution at constant temperature. Both capacity constants k2WL and k2SG also exhibited the inverse relationship between capacity constant and temperature, as well as concentration
of the osmotic solution. Peleg’s rate constants for WL and SG at all temperatures followed an Arrhenius type relationship. The predicted equilibrium
values were very close to experimental ones, which was confirmed with high
coefficients of determination and by the residual analysis.
Keywords: osmotic dehydration, pears, kinetics, temperature effect,
Peleg model.
The pear (Pyrus communis L.) is one of the
most traditionally cultivated fruits, particularly in temperate climate zones in Europe. This fruit abounds in
saccharides and dietary fiber as well as in nutritionally
valuable compounds such as antioxidant flavonoids.
The fruit contains high quantities of vitamin C, B-complex vitamins (folates and riboflavin), organic and fatty
Correspondence: V.M. Pavelkić, IHTM, University of Belgrade,
Njegoševa 12, 11000 Belgrade, Serbia.
E-mail: pavelkic@ihtm.bg.ac.rs
Paper received: 14 October, 2014
Paper revised: 21 January, 2015
Paper accepted: 29 January, 2015
acids, volatiles and minerals such as copper, iron,
potassium and magnesium. The chemical composition, the nature and concentrations of pear’s constituents are associated with the organoleptic characteristics of the pear fruits [1-3]. In addition, pear fruit
is one of the very low calorie fruits. Due to these
beneficial features, regular consumption of pears is
highly recommendable in human nutrition [4].
The common fruit processing techniques are
conservation in syrup, juice and drying. Dried fruits
are used for many purposes in bakery products, gravies and compotes. Ready-to-use intermediate mois-
485
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
ture (IM) food for human consumption has received
much attention in recent years. IM products produced
by osmotic dehydration (OD) have a higher content of
nutrients than those produced by any other drying
techniques, because OD has little effect on various
internal components. OD of fruits, as a pre-treatment
for further steps of drying, presents some benefits
such as reducing the damage of heat to the flavor,
color, inhibiting the browning of enzymes and decrease the energy costs [5,6]. OD is a process of partial removal of water by immersing of food (fruit, vegetables, meat and fish) in different types of solutes
such as sucrose, fructose, corn syrup, glucose, salts`,
etc., used as osmotic agents for OD [7].
During the OD process the water and small
amounts of natural solutes (such as pigments,
sugars, organic acids, minerals, vitamins, etc.) diffuse
from fruit to the solution and the solute is transferred
from the osmotic solution to the fruit tissue in a countercurrent mode. It is an efficient form of moisture
removal from solid food, causing no change in phase
of the water [8]. The weight reduction is approximately 50% of the original weight due to the osmotic
dehydration. Mass transfer during osmosis depends
on operating parameters such as concentration and
type of the osmotic solution, temperature and period
of process [9]. According to previous research, temperature and concentration of osmotic solution have
the highest effect on mass transfer kinetics during the
process of osmotic dehydration. In addition, the rate
of WL during osmotic dehydration is affected by the
immersion time, sample to solution ratio and agitation
of the osmotic solution [10-13]. Mass transfer during
osmosis occurs through a semi-permeable cell membrane and consists of two major simultaneous counter-current fluxes of water and solutes – diffusion of
water from food to osmotic solution and diffusion of
solute from solution to the food. Leakage of negligible
amounts of natural solutes present in the cells into
osmotic solution has been considered as third minor
flux [14,15].
Mathematical equations describing mass transfer during the osmotic drying enable better comprehension of dehydrated material composition and operating parameters. In this regard, many theoretical and
empirical models have been presented in literature,
whereas empirical ones have been more popular
given their relatively easy application [16-19]. The
main goal of existing mathematical models of drying
process is prediction of the drying time. The prediction of the drying time is the basic data for the sizing
and the optimization of an industrial plant drying. Drying rate is always related to one specific product and
486
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
one specific operation. In the case of a constant
drying rate period, the phenomenon is in steady state.
The mathematical models usually based on Fick’s
diffusion model for drying studies have been applied
to fit drying data of biological materials [20,21].
Peleg model, an empirical one, has been widely
used to describe sorption and desorption processes
in various foods, i.e., to predict water loss/gain and
sugar/salt gain. It has been used to describe water
desorption of sago starch, papaya, apricot, cherry
tomato, pear, etc. [22-31]. Although it was found that
other mathematical model better predict kinetics of
the pear osmotic dehydration, according to some
authors, Peleg’s equation presents the best fitting for
WL and the best adjustment to experimental data.
Peleg’s equation parameters have been subjected to
analysis of variance and post-hoc Tukey’s HSD test
(at 95% confidence limit) to show statistically significant differences between samples [24,29,32].
With the lack of published experimental data for
OD conducted with “Abate Fetel” pears as model
fruits, our intention was to obtain additional information for practical application in OD process design
and control. The objective of this work was to examine mass transfer kinetics in terms of WL and SG as a
function of concentrations of osmotic solutions, temperatures and time of immersion during osmotic treatment of pears. Furthermore, the evaluation of applicability of Peleg’s equation to experimental data for
determination of equilibrium water and solid contents
for OD at different concentrations and temperatures
as well as the relationship between the Peleg’s specific rate constant and temperature using Arrhenius
equation for determination of the activation energy
(Ea) for WL and SG were done.
MATERIALS AND METHODS
Preparation of pear samples
Abate Fetel pears were purchased daily from
the local market at Belgrade, Serbia. Before experiment, fruits were washed and peeled. The peeled
pears were manually cut into cubes of 1 cm3, gently
blotted with tissue paper to remove the excess of
surface moisture and weighed. Initial moisture content, M0, was 84.92±0.99%. Analytical grade sucrose
was purchased from Merck. The sucrose solution
concentrations were 40, 60 and 70 mass%, and were
checked by a digital refractometer (Cole-Parmer,
USA). Osmotic treatment were carried out at atmospheric pressure, in temperature range from 20 to 50
°C using a circulating water bath (Circulating bath 240
VAC, Cole-Parmer, USA).
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
The pear cubes were immersed in the sucrose
solutions, with a sample to solution ratio of 1:10
(w/w). Samples were stirred every 10 min for purpose
of easier moving of water that had diffused from the
center of the pear cube to its surface and allowing
better homogenization of the osmotic solutions. Processing conditions regarding steering, intensity, duration and frequency of stirring were the same for all
concentrations of osmotic solutions, at all temperatures, so the results could be comparable. Fruits were
removed from the containers after the period of 30,
60, 90, 120, 180, 240, 300 and 360 min, quickly
rinsed with distilled water to remove adhered sugar
solutions to the surface and gently blotted with tissue
paper to remove excess solution from the surface.
After each contact time pear cubes were placed in the
drying oven (Instrumentaria ST01) at 105 °C for 24 h
until constant weight were reached. In order to determine mass change, all samples were weighed before
and after treatment using an analytical balance (Mettler-Toledo, JP 1203C, Switzerland). The solid content of osmotic solutions was determined refractometrically (digital refractometer 300034, SPER Scientific
Ltd., USA). All analyses were carried out in triplicate
and in accordance to AOAC [33].
Kinetic parameters determination
WL and SG of the samples were calculated as
follows:
WL / % = 100
M 0 − Mt
W0
(1)
SG / % = 100
St − S 0
W0
(2)
where M0 (g) is the moisture content in fresh fruit; Mt
(g) is the moisture content at time t of osmotic treatment; S0 (g) is the dry matter of fresh fruit; St (g) is the
dry matter after time t of osmotic treatment; W0 (g) is
the mass of fresh fruit before the osmotic treatment.
Curves of WL and SG as a function of time were
constructed using experimental data.
Peleg’s two-parameter equation [15,21,23,24,34]
was used for describe sorption kinetics curves that
approaches equilibrium asymptotically:
Mt = M 0 ±
t
k 1 + k 2t
(3)
where Mt is moisture or solid content (g) at time t (h),
M0 is initial moisture or solid content (g), k1 is the
Peleg’s rate constant and k2 is the Peleg’s capacity
constant. In Eq. (3), “±” becomes “−” for water loss
and “+” for solid gain [23].
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
The first derivative of Eq. (3) gives the rate of
sorption (R):
R=
dM
k1
=±
2
dt
(k 1+k 2t )
(4)
The Peleg’s rate constant k1 relates to dehydration rate at the beginning, t = t0, and is inversely
proportional to initial rate of dehydration [24]:
dM
1
=±
dt
k1
(5)
The Peleg’s capacity constant k2 relates to
minimum attainable moisture content, so at time t→∞
Eq. (4) gives the relation between equilibrium moisture content (Meq) and k2 [23,31]:
M eq = M 0 ±
1
k2
(6)
Rearrangement and linearization of Eq. (4) give
the possibility for graphical determination of the
Peleg’s kinetics parameters [24]:
t
= k 1 ± k 2t
M − M0
(7)
The plot of Eq. (7) is a straight line, where k1 is
the intercept and k2 is the slope [23].
The quantification of the drying can be made by
the quantification of the energy received by the material that is being dried. This energy is equal to the
energy necessary for the vaporization of the water
removed during the drying. In the decreasing drying
rate period, namely the unsteady state, the behavior
of the material during the drying is due to the domination of internal resistance. The distinctions of these
drying periods are obtained by drying rates calculations from drying curves. In order to find the effect of
temperature on water desorption of pears, an Arrhenius type equation was used for modeling the dependence of Peleg’s rate constant (k1) on temperature
[28].
The linearized Arrhenius equation represents
the temperature dependency of the Peleg’s rate constant:
ln k 1 = ln k 0 −
Ea
RT
(8)
where k1 is the Peleg’s rate constant for WL or SG (h
(g/g dm)-1); k0 is a constant (h(g/g dm)-1); Ea is the
activation energy (kJ/mol), R is the universal gas constant (8.314 J mol-1 K-1) and T is absolute temperature
in K.
487
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
The criterion used to evaluate the best fitting
model was their average relative error, E:
E =
1
ne
ne

i =1
X exp − X p
X exp
(9)
where ne is the number of experimental data, Xexp is
the experimental value for WL or SG, and Xp is the
calculated value for WL or SG.
Statistical analysis
Descriptive statistical analyses for Peleg’s equation parameters were expressed as the mean ±
standard deviation (SD). Post-hoc Tukey’s HSD tests
at 95% confidence limit have been calculated to show
significant differences between observed samples.
These calculations and the residual analysis were
performed using StatSoft Statistica 10 software (Statsoft Inc., Tulsa, OK, USA).
RESULTS AND DISCUSSION
The experiments of osmotic dehydration of
pears were carried out at three different concentrations and three different temperatures. Figures 1 and
2 show the experimental data for WL and SG as a
function of time of osmotic treatment of pear at different concentrations of sucrose solution, at 35 °C (data
obtained of experiments conducted at 20 and 50 °C
not shown). Three-dimensional graphics have been
plotted for regression model (surface plot) comparison, with experimental data visualization (white colored points). As can be seen, WL and SG increased
non-linearly with immersion time at all concentrations
Temperature=35oC
WL (%)
and temperatures. From the observed data presented
in Figures 1 and 2, the trend of the faster mass transfer rate in the initial period of osmotic treatment is
clear, and is followed by slower removal of water and
uptake of sugar from fruit tissue in later stages. This
reduction of the mass transfer rate might be result of
the formation of the solid layers at the surface of the
fruit tissue, which hinders transfer of water and solids
[35]. The WL and SG increase with increasing sucrose concentration at constant temperature, as well
as with increasing temperature of the osmotic solution. An initial increase of WL and SG probably
occurred because of the osmotic driving force difference between the dilute juice of the pear cubes and
the surrounding hypertonic sucrose solution. The increase of WL and SG with the higher solution concentration is due the high concentration difference
between the pear and osmotic solution that increased
the rate of diffusion of solute and water exchange with
osmotic solution [28,35,36]. Higher temperatures of
osmotic solution additionally cause increase in kinetics of mass transfer. Higher temperatures seem to
promote faster water loss through swelling and plasticizing of cell membranes as well as the better water
transfer characteristics on the product surface due to
lower viscosity of the osmotic medium [29,37,38].
This enhanced removal of water and uptake of solids
showed that immersion time and concentration of
sucrose solution were significant factors affecting WL
during osmotic dehydration of followed by temperature [30].
Temperature=35oC
SG (%)
10
8
50
6
6
40
4
30
30
2
20
70
10
60
50
Concentration (%)
10
300 WL (%)
200
100
40 0
4
60
20
70
Time (min)
> 30
< 30
< 20
< 10
Figure 1. Experimental and calculated values of WL during
osmotic dehydration of pears cubes at 35 °C and sucrose
solutions with concentrations: 40, 60 and 70 mass%.
488
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
50
Concentration (%)
2
300
200
100
40 0
Time (min)
SG (%)
>6
<6
<4
<2
Figure 2. Experimental and calculated values of SG during
osmotic dehydration of pears cubes at 35 °C and sucrose
solutions with concentrations: 40, 60 and 70 mass%.
After 360 min of osmotic treatment of pears, WL
ranges from 23.71 to 31.68% at 20 °C, from 24.80 to
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
40.38% at 35 °C and from 33.30 to 52.07% at 50 °C,
of initial weight of pears (Figure 1). The increase of
the dry mass of the samples, SG, after 360 min of
osmotic treatment ranges from 3.02 to 6.68% at 20
°C, from 4.15 to 7.71% at 35 °C and from 5.00 to
8.92% at 50 °C (Figure 2).
The WL/SG ratio is influenced by temperature
and concentration of the sucrose solutions, as well as
with the duration of the osmotic treatment. Higher
values of WL/SG ratio implies the intensive water
removal from the samples followed by minimal SG.
After initial increase of the WL/SG ratio during OD
treatment of pear at first 30 min of process, WL/SG
ratio decreased, depending of experimental conditions. The minimal ratio of 4.47 was obtained at 35
°C, 60% sucrose solutions and after 120 min of OD
treatment duration. The maximal value of 7.85 was
obtained at 50 °C, 40% sucrose solution and after 30
min of OD treatment.
Peleg’s equation and equilibrium values for WL
and SG at different experimental temperatures were
used to calculate Peleg’s rate constant, k1 and
capacity constant k2 for both processes. Peleg’s
equation parameters for WL and SG are shown in
Table 1. Peleg’s rate constants k1WL and k1SG
decreased from 1.12 to 0.51 h (g/g dm)-1 and from
5.48 to 2.17 h (g/g dm)-1 at 20 °C with increasing
concentration of osmotic solution from 40 to 70
mass%, respectively. Rate constant k1WL decreased
from 0.58 to 0.41 h (g/g dm)-1 and from 0.33 to 0.28 h
(g/g dm)-1 at 35 and 50 °C, respectively. In addition,
rate constant k1SG decreased from 4.33 to 1.58 h (g/g
dm)-1 and from 0.33 to 0.28 (g/g dm)-1 at 35 and 50
°C, respectively. The concentration of osmotic solutions, at each experimental temperature, increased
from 40 to 70 mass%. Since the reciprocal value of k1
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
describes the initial mass transfer rate through the
osmotic treatment, observed results indicate an increase of the initial mass transfer rate with increasing
the concentration and temperature of osmotic solution
[35]. The capacity constant, k2 is associated with
equilibrium moisture content and equilibrium solid
content, e.g., the lower the k2, the higher the equilibrium moisture content [10,31,35]. Both capacity constants k2WL and k2SG, also exhibit the same trend, i.e.,
the inverse relationship between capacity constant
and temperature, as well as concentration of the
osmotic solution. The statistical parameter (R2) ranged
from 0.936 to 0.997 for WL and SG, respectively.
The equilibrium point is reached when water
activities of osmotic solutions and dehydrated fruit
product become equal. The experimental equilibrium
point were reached after 360 min of the osmotic
treatment in some of the samples (Table 2), while in
the others experimentally obtained values were very
close to the ones calculated by Peleg’s model.
According to this, it would be reasonable to claim that
360 min is a long enough period to reach equilibrium.
Since both WL and SG influence decrease in water
activity, their relationship is important for the attainment of the equilibrium [10,31,35]. The predicted and
experimental equilibrium values for moisture content
and SG at different experimental temperatures and
concentrations of osmotic solutions are shown in
Table 2. As can be seen, slight differences between
the equilibrium experimental data and predicted
values by the Peleg’s model were observed (Table 2).
Table 2 also shows the residual analysis, which is
performed to check the assumptions of independence, normality, homoscedasticity and zero mean of
errors. The mean of residuals are close to zero, and
the standard deviation of Meq and Seq were 0.11 and
Table 1. Peleg’s equation parameters and goodness of fit for SG and WL during osmotic treatment of pear; a-dvalues with the same letter
within a column are not statistically different at the p < 0.05 level (according to post-hoc Tukey’s HSD test)
t / oC
20
35
50
Conc., %
Water loss
k1WL / h (g/g dm)-1
Solid gain
k2WL / h (g/g dm)-1
1.12±0.23
a
60
0.64±0.10
b
0.51±0.03
70
0.51±0.12
c
40
0.58±0.13
bc
60
0.45±0.09
cd
70
40
40
0.52±0.07
cd
R2
0.962
k1SG / h (g/g dm)-1
5.48±2.87
a
c
0.991
2.89±0.47
0.48±0.03
d
0.984
3.20±0.51
0.62±0.04
a
0.989
4.33±0.58
0.45±0.03
d
0.990
0.41±0.05
0.58±0.13
cd
0.34±0.02
a
0.33±0.08
d
0.54±0.02
c
60
0.15±0.05
e
70
0.28±0.07
d
k2SG / h (g/g dm)-1
5.50±0.84
R2
a
0.936
c
0.984
f
0.986
0.936
cd
3.42±0.25
c
2.17±0.15
b
3.54±0.17
b
0.993
2.46±0.86
cd
1.67±0.14
h
0.980
0.993
1.58±0.35
cd
2.75±0.11
d
0.995
0.994
1.70±0.47
cd
3.65±0.14
b
0.996
2.52±0.10
e
0.995
1.85±0.10
g
0.991
0.49±0.02
d
0.997
1.12±0.36
d
0.32±0.02
e
0.987
0.994
0.97±0.37
d
489
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
Table 2. Experimental and Peleg predicted values for equilibrium values for WL and SG during osmotic dehydration treatment
t / oC
Conc., %
20
35
50
Water loss
Solid gain
Meqexperimental / g/(g dm)
MeqPeleg / g/(g dm)
Residual
Seqexpperimental / g/(g dm) SeqPeleg / g/(g dm) Residual
40
3.845
3.877
0.032
1.068
1.087
60
2.987
3.039
0.052
1.195
1.205
0.01
70
3.627
3.516
-0.111
1.331
1.366
0.035
40
3.539
3.507
-0.032
0.968
1.019
0.051
60
4.637
4.733
0.096
1.404
1.443
0.039
0.019
70
2.077
1.984
-0.093
1.253
1.238
-0.015
40
2.732
2.649
-0.083
1.115
1.073
-0.042
60
2.403
2.648
0.245
1.276
1.191
-0.085
70
1.096
1.036
-0.06
1.236
1.279
0.043
Residual analysis
Mean
Min.
Max.
Variance
Std. dev.
Std. err.
Skewness
Kurtosis
Meq
0.01
-0.11
0.25
0.01
0.11
0.04
1.19
1.22
Seq
0.01
-0.09
0.05
0.00
0.05
0.02
-1.15
0.59
490
M t experimental (g/gdm)
5.0
Concentration=60%
50oC
4.5
35oC
20oC
4.0
3.5
3.0
3.0
3.5
4.0
4.5
M t calculated (g/gdm)
5.0
Figure 3. Comparison between experimental and calculated
values of moisture content of pears cubes during osmotic
dehydration treatment in sucrose solution with concentrations
60% and at 20, 35 and 50 °C.
1.10
S g experimental (g/gdm)
0.05, respectively. These results showed a good
approximation to a normal distribution around zero
with a probability of 95% (2×SD), which means a
good generalization ability of developed models for
the range of observed experimental values (the skewness parameter showed minimal deviations from normal distribution, while the Kurtoisis parameter showed
almost neglecting difference in "peakedness" compared to normal distribution).
The comparison between experimental and
Peleg-predicted values for moisture content and SG
during osmotic dehydration treatment of pears at 20,
35 and 50 °C in 40% sucrose solution are shown in
Figures 3 and 4. It is observed that the differences
between the data and the predicted ones were small.
The parameters, statistical R2, as well as the relative
error, E (%), were used for characterizing the fitting to
the Peleg’s model. As statistical parameter, R2,
ranges from 0.936 to 0.997 for moisture content and
SG, and E (%) value is below 10%, the Peleg model
can be account as acceptable for the description of
the WL and SG kinetic in the osmotic dehydration of
pears cubes.
The influence of temperature on WL and SG
kinetics were checked out by applying the Arrhenius
type equation for modeling the Peleg’s rate constant
dependence on temperature. According to Eq. (8), the
plot of the ln k1 (natural logarithm of Peleg’s rate constant) versus reciprocal of temperature, 1/T, resulted
in a straight line with the slope equal Ea/R and intercept equal ln k0. The graphically obtained parameters
of Arrhenius equation for the Peleg’s rate constant of
SG and WL at different sucrose concentrations are
presented in Table 3 (figures not shown).
Concentration=60%
50oC
1.05
35oC
20oC
1.00
0.95
0.90
0.85
0.85
0.90
0.95
1.00
1.05
S gcalculated (g/gdm)
1.10
Figure 4. Comparison between experimental and calculated
values of solid gain of pears cubes during osmotic dehydration
treatment in sucrose solution with concentrations 60% and at
20, 35 and 50 °C.
V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER…
Table 3. Parameters of Arrhenius equation for the Peleg rate
constant of SG and WL at different sucrose concentrations
Concentration, %
Parameter
70
–1
Ea / kJ mol
R2
40
1.12±0.13
-7.61±0.84
-4.87±0.20
15.65±2.91
37.73±1.37
32.09±0.52
0.98
0.95
0.99
Solid gain
ln k0
-3.55±0.94
-0.74±0.08
-2.46±0.48
Ea / kJ mol–1
31.40±2.41
24.59±1.17
30.40±1.44
0.99
0.92
0.94
R2
dependency of the Peleg’s rate constant and activation energy determination.
Nomenclature
60
Water loss
ln k0
Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)
Energy required to initiate water removal and
solid uptake, when pear cubes were immersed in 40,
60 and 70% osmotic solutions at 20, 35 and 50 °C
were determined using Eq. (8). Activation energy for
WL and SG varied from 15.65 to 32.09 kJ/mol and
31.40 to 30.40 kJ/mol, respectively. The lowest activation energy value was found for samples immersed
into a 70% sucrose solution. This confirms the report
that osmotic dehydration has low energy requirement
[34], especially when carried out at higher concentration. The linearity of the data (R2 > 0.92) reveals
that the k1 for all the kinetics terms followed an Arrhenius relationship as a function of temperature for each
applied sucrose concentration. Higher values of Ea
revealed the greater temperature sensitivity of rate
constant k1 [35]. Depending on sucrose concentration, it was found that the rate constant for WL is more
temperature sensitive than the rate constant for SG
(Table 3.) for 40 and 60 mass% sucrose concentration. At higher sucrose concentration (70 mass%) the
rate constant for SG is more temperature sensitive
compared with the rate constant for WL.
CONCLUSION
The influence of concentration and temperature
on mass transfer kinetics was investigated through
WL and SG during osmotic dehydration treatment of
pear cubes. The SG and WL increased with increasing sucrose solution concentration and temperature during osmotic treatment of pear. Peleg model
was successfully applied to the experimental data and
for description of the osmotic dehydration process.
From the experimental data, equilibrium values for
moisture and solid content were estimated using
Peleg’s equation. The model predicted equilibrium
values fitted very good to experimental ones, which is
confirmed with high coefficients of determination and
by the residual analysis. The Arrhenius equation was
successfully applied to evaluate the temperature
IM - Intermediate moisture
OD - Osmotic dehydration
WL - Water loss
SG - Solid gain
Ea - Activation energy (kJ/mol)
M - Moisture content (g)
k1 - Peleg’s rate constant (h (g/g dm)-1)
k2 - Peleg’s capacity constant (h (g/g dm)-1)
dm – dry matter
R - universal gas constant (8.314 J/g mol K)
R2 - coefficient of determination
T - temperature (K)
t - time (s)
E - average relative error (%)
ne - number of experimental data
Subscripts
eq - equilibrium
0 - initial
Acknowledgement
This study was financial supported by Ministry of
Education, Science and Technological Development
of the Republic of Serbia, project No. TR 31055.
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ВЕСНА М. ПАВЕЛКИЋ1
ТАЊА П. БРДАРИЋ2
МАРИЈА П. ПЕТРОВИЋ3
ГАВРИЛО М. ШЕКУЛАРАЦ1
МИЛИЦА Г. КОШЕВИЋ1
ЛАТО Л. ПЕЗО4
МАРИЈА А. ИЛИЋ5
1
Научна установа ИХТМ,
Универзитет у Београду, Београд,
Србија
2
Институт за нуклеарне неуке Винча,
Универзитет у Београду, Београд,
Србија
3
Институт „Кирило Савић“ а.д.,
Београд, Србија
4
Институт за општу и физичку
хемију, Београд, Србија
5
Рударско-геолошки факултет,
Универзитет у Београду, Београд,
Србија
НАУЧНИ РАД
ПРИМЕНА ПЕЛЕГОВОГ МОДЕЛА НА КИНЕТИКУ
ТРАНСФЕРА МАСЕ ТОКОМ ОСМОТСКЕ
ДЕХИРАТАЦИЈЕ КРУШКЕ У РАСТВОРУ
САХАРОЗЕ
У раду је испитивана применљивост Пелеговог модела за предикцију кинетике
трансфера масе током процеса осмотске дихдратације крушака, на различитим
концентрацијама (40, 60 и 70 мас.%) и темпертурама (20, 35 и 50 °C) раствора сахарозе. Повећање концентрације раствора сахарозе доводи до већег губитка воде
(ГВ) и повећања суве материје (СМ) током процеса осмотске дехидратације. После
360 min осмотског третмана крушака, ГВ се креће од 23,71 до 31,68% на 20 °C, од
24,80 дo 40,38% на 35 °C и од 33,30 дo 52,07% на 50 °C од почетне масе крушака.
Повећање суве материје у узорцима, СМ, после 360 min осмотског третмана креће
се од 3,02 до 6,68% на 20 °C, од 4,15 дo 7,71% на 35 °C и од 5,00 дo 8,92% на 50 °C.
Пелегове константе брзине, k1ГВ и k1СМ, опадају са повећањем температуре, а такође
опадају са повећањем концентрације осмотског раствора на константној температури. Обе капацитивне константе, k2ГВ и k2СМ, такође показују инверзно понашање у
односу на температуру и концентрацију осмотског раствора. Пелегове константе
брзине процеса ГВ и СМ на свим температурама прате функционалну зависност
Аренијусовог типа. Моделом предвиђене равнотежне вредности су блиске експерименталним, што је потврђено високим коефицијентима одређивања и резидуалном
анализом.
Кључне речи: oсмотска дехидратација, крушке, кинетика, ефекат температуре, Пелегов модел.
492
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
RONGYAN SHEN
FANG LIU
TE LI
XIA XU
YUTING LIANG
XINGQING ZHAO
WENYI ZHANG
School of Environmental and
Safety Engineering, Changzhou
University, Wujin District, Changzhou City, Jiangsu Province, China
SCIENTIFIC PAPER
UDC 628.3:544.526.5:66
DOI 10.2298/CICEQ140609005S
CI&CEQ
TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER USING TIO2/SIO2
COMPOSITE FILM IN A PHOTOCATALYTIC
REACTOR
Article Highlights
• Photocatalytic activity of filter media modified by TiO2/SiO2 was evaluated using DDNP
wastewater
• By modified filter media, removal rates of chroma and COD separately reached 70.00
and 60.85%
-1
• Optimal working parameters were: 59:1 of Ti/Si, pH 1, 7 ml L H2O2, and 3000 times
chroma
• Under optimal condition, decolorization and COD removal rate separately reached
98.50 and 92.50%
Abstract
TiO2/SiO2 composite film was used to modify the surface of the filter media
sintered by coal refuse. 2-Diazo-4,6-dinitrophenol (DDNP) wastewater was
used as the response substrate to test its photocatalytic activity in the selfmade photocatalytic reactor. The influencing factors of the photocatalytic activity of the modified filter media were studied. When the modified filter media
was used, the decolorization rate and COD removal rate of DDNP wastewater
reached 70.00 and 60.85%, respectively. But unmodified filter media almost
had no photocatalytic activity. The orthogonal test showed that the optimal
working parameters separately were: 59:1 of Ti/Si in the TiO2/SiO2 composite
film, pH 1, 7 ml L-1 H2O2 and 3000 times chroma (equivalent initial concentration of DDNP wastewater). Under the above condition, the decolorization rate
and COD removal rate separately reached 98.50 and 92.50% after 1 h photocatalytic reaction. They were far higher than those in the reaction catalyzed by
pure TiO2. Furthermore, under the condition of illumination and aeration, the
photocatalytic activities were obviously higher than those under only illumination or aeration.
Keywords: TiO2/SiO2, photocatalysis, modification, DDNP, decolorization
rate, COD.
2-Diazo-4,6-dinitrophenol (DDNP) has been
widely used as an important and effective explosive
[1]. It is an energetic compound and a very promising
initiator [1-4]. But in the producing process of DDNP,
the accompanying DDNP wastewater contained many
toxic substances such as two nitro diazo phenol, nitro
Correspondence: W. Zhang, School of Environmental and
Safety Engineering, Changzhou University, No 1 Gehu Road,
Wujin District, Changzhou City, Jiangsu Province, 213164,
China.
E-mail: zhangwenyi888@sina.com; 397132626@qq.com
Paper received: 9 June, 2014
Paper revised: 28 November, 2014
Paper accepted: 4 February, 2015
compounds, sulfide, phenol, etc. DDNP wastewater
had the characteristics of higher chroma, higher COD,
higher toxicity, and complicated composition, etc.
[5,6]. If untreated DDNP wastewater was discharged
into river, it would severely pollute the environment
and threaten the health of people [7]. This problem
has attracted the researchers’ extensive attention.
At present, the main methods of treating DDNP
wastewater are adsorption method, microelectrolysis/H2O2 method, and biochemistry method [7,8].
But the cost of these methods was high. And some
methods are in the period of exploration, and it is difficult for them to be applied and promoted [9,10]. Photocatalytic oxidation was a newly developed techno-
493
R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER…
logy. Sunlight was used as a potential radiation
source. It could stimulate the generation of the holeelectron pairs. So strong redox occurred in this method.
Many pollutants could be treated by this method.
Coal gangue is the largest solid waste in our
country. Its emission and accumulation not only take
up a large number of cultivated land, but also cause
great pollution and endanger people’s health. It has
become a public nuisance. The comprehensive development and utilization of coal gangue are urgent and
imperative in our country. As the main component of
sintered filter material, coal gangue would not only
satisfy the basic requirement of water treatment, but
also have obvious mineralogy characteristics of crystal. It was widely used in wastewater treatment
because of its many surface pores, large roughness,
and more stable performance. Coal gangue and its
sintered products often contain a lot of quartz and
scale quartz. So their surface and photocatalytic activity can be increased by nano modification.
As a kind of typical nanomaterials, titanium dioxide (TiO2) was widely used in pollutants processing
due to its non-toxicity, high-stability, and photo-electric properties [11-16]. Despite many good properties,
there were certain problems associated with nanometric TiO2. Such problems included nanoparticles
agglomeration [17], phase transformation [18,19],
decrease in surface area upon thermal treatment
[19,20], recombination of photogenerated electron–hole pair [21], lack of visible light photo activity due to
its wide band gap (Eg = 3.2 eV), etc. [21]. Furthermore,
the photocatalytic efficiency of pure TiO2 in photocatalytic reactions was found to be limited in our previous study [16]. To solve most of these problems,
many TiO2-based composite photocatalysis have
been prepared to enhance the photocatalytic activity
[11,12]. In comparison to those single-phase titania
materials, these composites tend to show higher
photoactivity [22-24]. These composites were usually
composed of titania and other functional metals/metal
oxides nanoparticles such as SiO2, ZrO2, MoO3 and
Fe2O3 [25,26]. Silica was one of the best core materials [27,28] due to its rich and well-known surface
chemistry and adsorption capacity [29].
To efficiently and economically treat the DDNP
wastewater of higher chroma and further improve the
photocatalytic activity of the sintered filter media, the
glass photocatalytic reactor [16] was used and the
TiO2/SiO2 composite film was prepared. And the influencing factors of photocatalytic activity of TiO2/SiO2
composite film were investigated.
494
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
EXPERIMENTAL
Preparation of the filter media modified by TiO2/SiO2
Firstly, the modified filter media was prepared by
the liquid phase deposition method [16]. (NH4)2TiF6,
(NH4)2SiF6 and H3BO3 were used as the precursors.
The mole ratio of (NH4)2TiF6 + (NH4)2SiF6 and H3BO3
was 1:3. The molarity of (NH4)2TiF6 was 0.1 mol L-1
and the used concentrations of H3BO3 were 0.2, 0.3,
and 0.4 mol L-1. The distilled water was used as the
solvent of the coating solution. The other steps were
same as the reference [16]. After certain time, the sintered filter media modified by the TiO2/SiO2 composite
film was obtained.
Characterization of the modified filter media
Particle morphology and physico-chemical properties of the filter media modified by TiO2/SiO2 were
characterized by the same methods in the reference
[16]. The background of surface of the modified filter
media was bright. This was due to the reflection
because of the presence of TiO2 thin film. And light
was reflected on uneven surface many times. This
would inevitably increase the absorption and utilization of light. It would be advantageous to the catalytic reaction. Although the surface of the unmodified
filter media was very rough and there were many
irregular holes, its particle surface was smoother.
There were a large number of small bumps and uniform distribution on the particle surface of the modified filter media. They were TiO2 grains (30-50 nm).
These particles pilinged up in together in different
ways. This made the micro-structure of the surface of
modified filter media change. The specific surface
area of the modified filter media was greatly improved. It was advantageous to the adsorption of more
ultraviolet light. In our previous study we found that
the main components of the unmodified filter media
were silicon, aluminum, oxygen, carbon, calcium, and
iron. Titanium elements existed in the energy spectrum diagram of modified filter media. And they
existed in the form of TiO2 compounds. The weight
percentage and atomic percentage of titanium were
0.99 and 0.40%, respectively. There were a large
number of alpha-quartz crystal, scale quartz and calcium feldspar in the mineral phase structure. TiO2
crystal could not be found in unmodified filter media.
But new TiO2 crystal was found in XRD atlas of modified filter media. The superposition phenomenon
existed in the diffraction peaks of TiO2 crystals and
calcium feldspar crystal.
R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER…
Photocatalytic reactor
The photocatalytic reactor was same as the one
used in our previous work [16]. The interlayer was the
photocatalytic reaction unit filled with the sintered
filter media modified by the TiO2/SiO2 composite film.
The reactor had already been described in details
elsewhere [16].
Orthogonal test design
The orthogonal test design is a method that utilizes an orthogonal test table to organize the tests and
to scientifically analyze the test results before decision-making. This paper firstly analyzed the main
parameters that affected the photocatalytic activity of
TiO2/SiO2 composite film and their respective levels
and then discussed the conducted orthogonal test to
optimize the parameters of the photocatalytic system.
Based on the effects of varied factors on DDNP
wastewater degradation, the mole ratio of Si and Ti in
the TiO2/SiO2 composite film, chroma (initial concentration), pH and addition amount of H2O2 were selected as the orthogonal test factors. Each factor was
taken three levels. There were 27 combinations to be
tested in the orthogonal test L9 (34). We applied the
orthogonal array to select nine representative combinations to be tested. The factors and levels were
shown in Table 1.
rate and COD removal rate of unmodified filter media
reached 18.00 and 22.64%, respectively. But after the
filter media was modified by the TiO2/SiO2 composite
film, the decolorization rate and COD removal rate
reached 70.00 and 60.85%, respectively. They were
far higher than those in the reaction catalyzed by pure
TiO2 [16]. This indicated that the modified filter media
had better photocatalytic degradation activity.
Then, a series of photocatalytic reactions were
conducted to further improve the photocatalytic activity of the modified filter media. DDNP wastewater of
3250 times chroma and 317.99 mg L-1 COD was
treated and different influencing factors were analyzed.
Influence of mole ratio of Ti and Si
The experiments without irradiation had been
done in previous study reported in the China Water
and Wastewater. The decolorization rates were all
very small (< 7%) [30]. In present study, the decolorization rates of 24 h were also very small (< 2%)
and the results had no significant difference. So the
adsorption of the composite films of different Ti/Si
was neglected in further study.
In present study, when the mole ratio of Ti and
Si in the TiO2/SiO2 composite film was 59:1, the photocatalytic activity of the modified filter media was
best (Figure 1). The decolorization rate and COD
removal rate were 70.00 and 60.85%, respectively.
Table 1. Factors and levels of orthogonal test
80
Factor
Mole ratio of Ti
Initial
and Si (A)
chroma (B)
pH
(C)
H2O2 addition
-1
amount, ml L (D)
7
1
39:1
5000
1
2
59:1
3250
3
9
3
79:1
3000
5
11
Analysis method
In the process, COD removal rate and decolorization rate were evaluated. The COD values were
determined by the potassium dichromate method.
The variation of absorbency was characteristic of the
decolorization efficiency. The variation of absorbency
was calculated by the formula [16].
RESULTS AND DISCUSSION
Influencing factors of the photocatalytic activity of the
modified filter media
Under the condition of neutral and room temperature, the photocatalytic degradation experiment of
DDNP wastewater with 5000 times chroma (initial
concentration) was conducted. The decolorization
70
Removal rate (%)
Level
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
COD removal rate
Decolorization rate
60
50
40
30
20
10
0
19:1
39:1
59:1
79:1
99:1
Mole ratio of Ti and Si
Figure 1. Effect of mole ratio of Ti and Si on removal rate.
In TiO2/SiO2 composite film, the Si-O-Ti bond
formed between SiO2 and TiO2, and then SiO2 with
net structure entered into the compound [31]. SiO2 net
inhibited the TiO2 mass transport and reduced the
growth rate of crystal particle. So the TiO2 particle
size in TiO2/SiO2 compound with uniform composition
could be well controlled. The reduction of particle size
increased the width of the forbidden band, and the
effect of quantum size was significant. This caused
the energy increase of band gap. The time that carrier
495
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
was diffused from interior to surface of catalyst shortened in photocatalytic reaction, and the separation
efficiency of photo-generated electron and hole was
improved. So the photocatalytic degradation activity
was enhanced. However, SiO2 did not have photocatalytic activity. So, when TiO2 surface was occupied
by more SiO2, its effective surface reduced. Under the
condition, it was not easy for the photo-generated
electron and the hole to produce [32]. Hence, if the
content of SiO2 in the TiO2/SiO2 composite film was
too high, the photocatalytic activity of composite film
would decline.
Influence of reaction time
Influence of chroma
Removal rate (%)
R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER…
When the chroma of DDNP wastewater was
3250 times, the decolorization rate and COD removal
rate reached the highest value (Figure 2). The higher
the initial concentration of solution was, the weaker
the penetrating ability of ray was, and the lower the
amount of photons which participated in photocatalytic reaction was. More solute was adsorbed on the
surface of catalyst, and the active site reduced [31].
These inhibited the catalyst to absorb the ultraviolet
and produce the •OH. So the photocatalytic efficiency
reduced. Though the decolorization rate was high
when the initial concentration was too low, the
amount of treated DDNP wastewater was low. The
degradation ability of photocatalytic reaction could not
be fully exerted. In the experiment, the surface adsorption of the TiO2/SiO2 composite film reached saturation because of overhigh concentration wastewater.
Most active sites of the TiO2/SiO2 composite film surface were occupied due to surplus organic molecular.
And the absorption of ultraviolet and the production of
•
OH were influenced. But the photocatalyst could not
be fully applied because of overlow concentration
wastewater, which affected the degradation efficiency.
80
COD removal rate
Decolorization rate
Removal rate (%)
70
60
50
40
30
20
10
0
7500
5000
3250
3000
Chroma (time)
Figure 2. Effect of chroma on removal rate.
496
2500
When the reaction time was more than 60 min,
the efficiencies of photocatalytic degradation tend to
be steady (Figure 3). And the decolorization rate and
COD removal rates were 73.85 and 65.17%, respectively. The oxidation reaction incompletely happened
when illumination time was too short, so the removal
was not good. Too long illumination time had no significant effect on the removal of pollutant.
90
80
70
60
50
40
30
20
10
0
COD removal rate
Decolorization rate
15
30
45
60
75
90
Time (min)
Figure 3. Effect of reaction time on removal rate.
Influence of pH
Under the acidic condition, the decolorization
rate and COD removal rate both reached the maximum which were 81.54 and 72.34%, respectively
(Figure 4). When pH was more than 7, the decolorization rates declined with the rising of pH. The variation of pH would impel the change of electrification
state of TiO2 surface. When pH was below 3.5, the
particle surface took positive charge. And it was
beneficial for the photo electron to migrate to the
surface of catalyst. And the electron reacted with O2
adsorbed by catalyst, so the combination of E- and H+
was inhibited. Furthermore, pH of solution directly
affected the surface state, interfacial potential, surface charge, and aggregation of TiO2 [33]. The isoelectric point of TiO2 was about 6.5. When pH was
more than 6.5, the surface charge was negative and
the main form was TiO-. And when pH was below 6.5,
the surface charge was positive and the main form
was TiOH2+. The characteristic of surface charge
affected the TiO2 surface adsorption of organic molecules, and affected the migration of photo electron
and hole from the interior to the surface of TiO2 [31–33]. Due to different surface morphology and surface
charge, the adsorption ability of catalyst was significantly different, so the process of photodegradation
was affected.
90
80
70
60
50
40
30
20
10
0
COD removal rate
Decolorization rate
15
30
45
60
75
90
Time (min)
Figure 4. Effect of pH on removal rate.
Influence of H2O2 addition amount
Removal rate (%)
The optimal addition amount of H2O2 was 9 ml L-1
(Figure 5). When the addition amount was more than
9 ml L-1, there was not direct relationship between two
rates and H2O2 addition amount. This indicated that
H2O2 not only was the generating agent of •OH but
also the scavenger of •OH. The addition amount of
H2O2 influenced the yield of ·OH and the removal of
pollutant. Only in certain range, there was direct relationship between the yield of •OH and H2O2 amount,
and too much H2O2 could promote the clearance of
•
OH [34]. And the redundant H2O2 would enhance the
effluent COD. So it was very necessary for wastewater to find the optimal addition amount of H2O2.
100
90
80
70
60
50
40
30
20
10
0
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
under the condition of illumination and aeration were
higher than those under the condition of only illumination or aeration. Illumination and aeration were two
indispensable factors for photocatalytic reaction.
When the energy of light was greater than the width of
the forbidden band, the electrons in the valence band
of TiO2 particles would transit to the conduction band
and become the conduction band electrons, and
leave a hole in the valence band. The hole was usually captured by OH- and H2O. So the hydrogen and
oxygen free radicals (•OH), which has strong ability of
oxidation. When the electrons were captured by O2
adsorbed by the surface of TiO2 particles, many free
radicals formed (O2-·, HO2·, etc.), which participated in
multiple redox process [35]. Due to addition of silicon
in the composite film, the formation of Si-O-Ti key
reduced the surface energy and the agglomeration of
TiO2 reduced. The band-gap energy of the electrons
of TiO2 from the valence band to the conduction band,
so the photocatalytic ability of TiO2 raised.
80
Removal rate (%)
Removal rate (%)
R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER…
70
COD removal rate
60
Decolorization rate
50
40
30
20
10
0
Illumination Illumination
and aeration
5
7
9
11
Aeration
Figure 6. Effect of illumination and aeration on removal rate.
COD removal rate
Decolorization rate
3
Setting
Orthogonal test of optimal process parameters
13
H2O2 additional amount (ml/L)
Figure 5. Effect of H2O2 addition amount on removal rate.
Influence of Illumination and aeration
Under the condition of illumination and aeration,
the decolorization rate and COD removal rate were
73.85 and 65.17%, respectively (Figure 6). Without
illumination or aeration, two rates were only 7.69 and
11.96%, respectively. Under the condition of only illumination, two rates were 53.52 and 42.12%, and
under the condition of only aeration, two rates were
38.86 and 39.43%, respectively. So the removal rates
Based on the effects of varied factors on DDNP
wastewater degradation, the mole ratio of Si and Ti in
the TiO2/SiO2 composite film, chroma (initial concentration), pH, and H2O2 addition amount were selected
as the orthogonal test factors. Each factor was taken
three levels in the orthogonal test L9 (34). The range
analysis was shown in Table 2.
Table 2. Range analysis of orthogonal test
Factor
Number
Mole ratio of Ti
and Si (A)
K1
85.23
77.59
82.76
82.26
K2
85.71
79.52
79.71
80.41
K3
66.36
80.19
74.83
74.64
R
19.35
2.60
7.92
7.62
Initial
pH (C)
chroma (B)
H2O2 addition
amount (D)
497
R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER…
Table 2 is the result of range analysis of orthogonal test, and the decolorization rates were calculated. The primary and secondary orders of different
factors were defined by different range values in each
column. The best level of each factor was determined
by the maximum value of K (total of Kn of each factor
at the same level). As a result, the optimum process
parameters were determined. As could be seen from
Table 2, the mole ratio of Ti and Si in the TiO2/SiO2
composite film had more impact on decolorization
rate, whereas the initial chroma of DDNP wastewater
had less impact on decolorization rate. The order of
the effects of varied factors on photocatalytic degradation is A > C > D > B. The optimal parameter was
A2B3C1D1. Namely, the optimal parameters were 59:1
of mole ratio of Ti and Si, pH 1, 7ml L-1 H2O2 addition
amount, and 3000 times chroma of DDNP wastewater. Under the optimal condition, the decolorization
rate and COD removal rates were 98.50 and 92.50%,
respectively. They were higher than any group. And
they were far higher than those in the reaction catalyzed by pure TiO2 [16].
Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)
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Many factors affected the photocatalytic activity
of the filter media modified by TiO2/SiO2. The mole
ratio of Ti and Si, pH, H2O2 addition amount and
chroma of DDNP wastewater were researched. Under
the optimal condition, the decolorization rate and
COD removal rates are 98.50 and 92.50%, respectively. They were far higher than those in the reaction
catalyzed by pure TiO2. The chroma and COD of
effluent were 45 times and 22.89 mg L-1, which could
meet the first class standard in the national Sewage
Comprehensive Discharge Standard (GB8978-1996).
This demonstrated that higher catalytic activity
existed in the photocatalytic reaction under the optimal conditions determined by orthogonal test.
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Acknowledgments
The authors are grateful to the Jiangsu Province
Natural Scientific Foundation (BK2012159 and
BK2011233), the Major Science and Technology Program for Water Pollution Control and Treatment
(2012ZX07301001c), the College Students' Innovative Projects in Jiangsu Province (201410292044Y)
and National Natural Science Foundation of China
(41571471)for financial support of this work.
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RONGYAN SHEN
FANG LIU
TE LI
XIA XU
YUTING LIANG
XINGQING ZHAO
WENYI ZHANG
School of Environmental and Safety
Engineering, Changzhou University,
Wujin District, Changzhou City, Jiangsu
Province, China
NAUČNI RAD
TRETMAN OTPADNE VODE SA 2-DIAZO-4,6-DINITROFENOLOM POMOĆU TIO2/SIO2 KOMPOZITNOG FILMA U FOTOKATALITIČKOM
REAKTORU
TiO2/SiO2 kompozitni film je korišćen za modifikaciju površine filtera koji je sinterovan
otpadnim ugljem. Otpadna voda koja sadrži 2-diazo-4,6-dinitrofenol (DDNP) je korišćena
za testiranje njegove fotokatalitičke aktivnosti u fotokatalitičkom reaktoru. U radu je ispitan
uticaj odgovarajućih faktora na fotokatalitičku aktivnost modifikovanog filtera. Korišćenjem
modifikovanog filtera postižu se stepen dekolorizacije od 70% i stepen smanjenja hemijske
potrošnje kiseonika (HPK) merena preko DDNP od 60,85%. Nemodifikovani filter skoro da
nema fotokatalitičku aktivnost. Ortogonalni eksperiment je pokazao da su optimalni operativni parametri: odnos Ti/Si u kompozitnom filmu TiO2/SiO2 59:1, pH 1, 7 ml L-1 H2O2, i
hroma 3000 puta (ekvivalentno početnoj koncentraciji DDNP u otpadnoj vodi). Pod ovim
optimalnim uslovima posle 1 h fotokatalitičke reakcije, stepen obezbojenja i stepen uklanjanja HPK odstranjivanja su dostigli vrednosti 98,50 i 92,50%, redom. Ako se primene iluminacija i aeracija, fotokatalitička aktivnost je veća nego pri primeni samo iluminacije ili
samo aeracije.
Ključne reči: TiO2/SiO2, fotokataliza, modifikacija, DDNP, stepen dekolorizacije,
HPK.
499
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
MILUTIN M. MILOSAVLJEVIĆ1
IVAN M. VUKIĆEVIĆ1
VEIS ŠERIFI1
JASMINA S. MARKOVSKI2
IVANA STOJILJKOVIĆ3
DUŠAN Ž. MIJIN4
ALEKSANDAR D.
MARINKOVIĆ4
1
Faculty of Technical Science,
University of Priština, Kosovska
Mitrovica, Serbia
2
Vinča Institute of Nuclear
Sciences, University of Belgrade,
Belgrade, Serbia
3
Faculty of Chemistry, University of
Belgrade, Belgrade, Serbia
4
Faculty of Technology and
Metallurgy, University of Belgrade,
Belgrade, Serbia
SCIENTIFIC PAPER
UDC 628.3:547.495.2:543.42
DOI 10.2298/CICEQ141221006M
CI&CEQ
OPTIMIZATION OF THE SYNTHESIS OF
N-ALKYL AND N,N-DIALKYL THIOUREAS
FROM WASTE WATER CONTAINING
AMMONIUM THIOCYANATE
Article Highlights
• Synthesis of N-alkyl and N,N-dialkyl thioureas are optimized in laboratory
• The optimal laboratory synthesis of thioureas are transferred to semi-industrial level
• Commercial as well as industrial waste materials are used in synthesis of thioureas
• Presented methods are suitable environmentally benign option to existing procedures
Abstract
The optimized methods for N-alkyl and N,N-dialkyl substituted thioureas synthesis starting from ammonium thiocyanates, waste water constituent from the
production of tetramethylthiuram monosulfide (TMTS), and alkyl amine, are
presented in this work., Thioureas synthesis was developed in two ways:
Method I − reaction of the thiocyanate and alkylamine in the presence of hydrochloric acid; Method II − reaction of the thiocyanate with benzoyl chloride
following by amine addition in the first step, and base hydrolysis in the second
step. The structure of the synthesized compounds was confirmed by IR, 1Hand 13C-NMR and MS instrumental methods, and purity was determined by
high-performance liquid chromatography method. It is shown that the proposed
methods offer a high degree of conversion and purity of product, absence of
by-products and technological applicability at industrial scale. Considering the
importance of the tetramethylthiuram disulfide (TMTD) and TMTS as vulcanization accelerators as well as thiourea as the pharmacologically active compounds, it can be said that application of the optimized methods of thiourea
synthesis will provide significant improvement in sustainable development and
implementation of eco-friendly production technology. The described environmentally benign process of thioureas synthesis represents a suitable option to
existing methods.
Keywords: thioureas, optimization, semi-industrial level, thiocyanate.
Thiourea (NH2CSNH2) and its derivatives, as
well as oxidation products, found large alternative
application in different industrial fields. Depending on
the starting thiourea compound, used oxidants and
pH value of reaction medium, a variety of oxidation
products can be produced [1]. Catalytic oxidation by
the use of hydrogen peroxide in presence of ruthenium complexes ethylenediaminetetra sulfate pro-
Correspondence: M.M. Milosavljević, Faculty of Technical Science, University of Priština, Knjaza Miloša 7, 38220 Kosovska
Mitrovica, Serbia.
E-mail: vidahem@yahoo.com
Paper received: 21 December, 2014
Paper revised: 31 January, 2015
Paper accepted: 5 February, 2015
duce formamidine disulfide, thiourea dioxide, thiourea
trioxide and sulfate [2]. Also, uses of hydrogen peroxide as oxidative agent in reaction with thiourea produces a powerful bleaching agent that has various
applications in textile industry [3,4], and as corrosion
inhibitors for industrial equipment such as boiler [5,6].
Solution of thiourea in dilute hydrochloric acid is used
as a complexing agent for removing scales from boilers [7].
Synthesis of N-alkyl (aryl) and N,N-dialkyl thioureas, starting from the ammonium thiocyanate and
an appropriate amine in water at 80–90 °C [8], was the
first step in the overall procedure of obtaining certain
2-aminothiazole derivatives of 4-hydroxy-chromen-2-one. This product was used as inhibitors of enzymes
501
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
such as kinurenine-3-hydroxylase [9]. Also, N,N-dialkyl-N'-alkyl thioureas may be prepared from dialkylamine and carbon disulfide in the presence of sodium
hydroxide. The sodium salt of dialkyl dithiocarbamic
acid was obtained in first reaction step, which by addition of an alkyl amine, and extraction with methylene
chloride, gives the corresponding thiourea product [10].
A large number of the methods of thiourea derivatives synthesis has been established: reaction of
anilines and sodium isothiocyanate treated with trifluoroacetic acid [11], ammonium thiocyanate in the
presence of concentrated hydrochloric acid [12], aroyl
isothiocyanates with amines followed by basic hydrolysis of α-aroyl-β-phenylthiourea product [13], tetraisothiocyanatosilane with primary and secondary
amines [14], thioureas with long chain alkyl amines at
170–180 °C, alkyl or aryl isothiocyanates with amine
and carbon disulfide and amines [15]. Also, thiourea
derivatives have been obtained by reaction of alkyl
isothiocyanates with ammonia or amines [16], as well
as reaction of carbon disulfide and primary amines in
the presence of mercury acetate [17]. Reaction of
disubstituted cyanamides with either hydrogen chloride and LiAlHSH [18] or hydrogen sulfide in the presence of ammonia [19] provided thiourea products.
Recently, a new and efficient reagent 1-benzo-triazole-1-carbothioamide used for the preparation of
mono and N,N-disubstituted thioureas was described.
Nucleophilic displacement of benzotriazole from intermediary product by attack of a variety of amines gave
corresponding N,N-disubstituted thioureas product [20].
Due to its extensive ligands applications in coordination chemistry, the chemistry, structure and
potential applications of 1-(acyl/aroyl)-3-(mono-substituted) and 1-(acyl/aroyl)-3,3-(di-substituted) thioureas
have been overviewed recently [21]. A series of
N-aroyl-N′-substituted thiourea derivatives have been
prepared in good to excellent yields under the condition of solid-liquid phase transfer catalysis using
polyethylene glycol-400 (PEG-400) as the catalyst
[22]. Also, N-benzoyl-N'-carboxyl substituted thiourea
derivatives have been synthesized by the reaction of
benzoyl isothiocyanate with amino acids, and preliminary biological tests showed excellent plant growth
promotion activities [23]. Carbamoyl isothiocyanates
can be used for synthesis of 1,3-disubstituted and
1,1,3-trisubstituted thiourea derivatives in reaction
with alkyl or aryl amines. A secondary amine can be
coupled to the carbamoyl thiourea using EDC (1-ethyl-3-(3-dimethylaminopropyl)carbodiimide). This way,
the formation of 1,3-disubstituted and 1,1,3-trisubstituted guanidines through either stepwise or one-pot
synthesis was achieved [24].
502
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
Several new thiourea and urea derivatives were
prepared in satisfactory yield by the reaction of
4-amino-pyrazoles with substituted isothiocyanates or
isocyanates in acetone [25]. In reaction of dimethylamine, carbon disulfide and hydrogen peroxide, an
aqueous suspension of TMTD product was obtained
[26,27]. Industrial process for the TMTS synthesis
was performed by reaction of TMTD with cyanide ion
and in such way ammonium thiocyanate was released according to the following reaction [28]:
TMTS was obtained as filtration cake while the
collected filtrate was an aqueous solution of ammonium thiocyanate [29], which was chosen to be used
as reactant for thioureas synthesis.
The aim of this work was focused on the optimization of N-alkyl and N,N-dialkyl thioureas synthesis starting from either commercial ammonium
thiocyanate or waste water obtained from TMTS production which contains ammonium thiocyanate and
corresponding amines. The first method developed in
this paper, Method I, implied a reaction of thiocyanate
with the appropriate amines and hydrochloric acid in
ethyl acetate. Second method, Method II, was performed by thiocyanate treatment with benzoyl chloride, amines and sodium hydroxide. In order to get
highest reaction yield and purity of obtained product,
optimization of presented procedures was performed
with respect to variable reaction parameters: reaction
time, temperature and molar ratio of reactants. The
developed optimal technologies at the laboratory level
were transferred and implemented at semi-industrial
level with previously performed additional optimization of production technology in regards to reactant
mole ratio.
EXPERIMENTAL
Two optimized methods (Method I and Method
II) for the N-alkyl and N,N-dialkyl thioureas synthesis
were developed at laboratory and semi-industrial
level. The optimization of procedures was performed
in relation to reaction time, temperature and mole
ratio of reactant.
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
General procedure for the N-alkyl and N,N-dialkyl
thiourea synthesis according to Method I
General procedure for the N-alkyl and N,N-dialkyl
thioureas synthesis according to Method II
In a three-necked flask, equipped with magnetic
stirrer, dropping funnel, condenser and thermometer,
10.0 ml of 20% water solution of ammonium thiocyanate (0.12 mol) was introduced and heated to 90 °C.
Appropriate amine, i.e., methyl amine (11.73 cm3,
0.10 mol) was added drop-wise with vigorous stirring
of reaction mixture during one hour. Reaction took
place for 3 h in temperature range 80–90 °C. Dilute
hydrochloric acid (1:1) was added in a cooled reaction
mixture and stirring was continued for 30 min. Reaction medium was subjected to vacuum for 5 min (10
kPa) followed by immediate addition of ethyl acetate
(200 cm3) and 15 min intensive mixing. The reaction
mixture (suspension) was filtered through a Buchner
funnel and the ammonium chloride was separated as
filtration cake. The upper layer of filtrate, ethyl acetate
solution containing N-methyl thiourea, was separated
from water layer, dried with sodium sulphate and solvent was removed by atmospheric distillation. Pure
product was obtained by recrystallization from methanol followed by column chromatography purification
(silica gel 60, 230–400 mesh) using benzene/methanol (9:1) as mobile phase. After solvent evaporation
and product drying at 50 °C for 10 h, yield of N-methyl
thiourea was 76.2%, melting point was 203.5 °C, and
purity, obtained by HPLC analysis, was 98.9%. All
other thioureas were synthesized in an analogous
manner to the above described procedure and reaction conditions presented in Table 1.
In a three-necked flask equipped with magnetic
stirrer, dropping funnel, condenser and thermometer,
8.5 ml of 20% water solution of ammonium thiocyanate (0.10 mol) was introduced and heated to 45 °C.
Benzoyl chloride (12.90 cm3, 0.11 mol) was added
drop-wise with vigorous stirring of reaction mixture for
two hours. After addition of the appropriate amount of
alkyl amine reaction took place for 2 h at 45 °C and
cooled down to room temperature. Carefully, 15 ml of
sodium hydroxide solution (20%) was added to reaction mixture and continued with mixing for 30 min to
provide hydrolysis of N-benzoyl-N,N-dialkyl thiourea.
The reaction mixture was filtered through a Buchner
funnel giving a filtration cake which contains raw product and collected filtrate of sodium benzoate water
solution. Pure product was obtained by recrystallization from methanol followed by column chromatography purification (silica gel 60, 230–400 mesh)
using benzene/methanol (9:1) as a mobile phase.
After solvent evaporation and drying at 50 °C for 10 h,
N-methyl thiourea yield was 72.2%, melting point was
202-205 °C, and purity, obtained by performing HPLC
analysis, was 98.5%. All other thioureas were synthesized in an analogous manner to above procedure,
using the appropriate amine in regards to reaction
conditions presented in Table 2.
Additionally, developed procedures were analogously applied in the synthesis of thiourea derivatives starting from real waste water samples collected
from the synthesis of TMTS at laboratory level. Calculation of the starting reaction mixture was based on
the result of waste water composition: ammonium
Table 1. Reaction conditions, yield, melting point and purity of the product obtained according to Method I starting from model and real water
Product
NH4SCN
(mol)
Amine
(mol)
Reaction time Reaction temperature
Yield, %
h
°C
Melting point, °C
Found (reported) [lit.]
Purity
(HPLC method)
Model water sample
CH3NHC(S)NH2
0.12
0.10
3.0-4.0
80-90
76.2
203.5 (202-203) [33]
98.9
(CH3)2NC(S)NH2
0.12
0.11
4.0-4.5
85-92
71.0
162-165 (163-164) [34]
98.3
EtNHC(S)NH2
0.12
0.10
3.0-4.0
82-88
75.8
111-112 (110-111) [35]
98.6
Et2NC(S)NH2
0.12
0.12
4.0-4.5
88-92
70.5
98-100 (99.2-100.6) [34]
98.7
PrNHC(S)NH2
0.12
0.10
3.0-4.0
81-86
73.2
108-110 (109) [36]
99.0
Pr2NC(S)NH2
0.12
0.12
4.0-5.0
88-92
70.0
109-110 [37]
98.8
Real water sample
CH3NHC(S)NH2
0.06
0.07
3.0-4.0
80-90
59.5
201-202 (202-203) [33]
97.2
(CH3)2NC(S)NH2
0.06
0.06
4.0-4.5
85-92
53.4
161-163 (163-164) [34]
97.3
EtNHC(S)NH2
0.06
0.07
3.0-4.0
82-88
51.8
110-112 (110-111) [35]
98.1
Et2NC(S)NH2
0.06
0.08
4.0-4.5
88-92
49.7
97-99 (99.2-100.6) [34]
98.0
PrNHC(S)NH2
0.06
0.06
3.0-4.0
81-86
54.6
106-108 (109) [36]
97.9
Pr2NC(S)NH2
0.06
0.07
4.0-5.0
88-92
47.3
107-109 [37]
97.5
503
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
Table 2. Reaction conditions, yield, melting pint and purity of the product obtained according to Method II starting from model and real water
Product
NH4SCN PhCOCl
(mol)
(mol)
Amine
(mol)
Melting point, °C
Found (reported) [lit.]
Reaction Reaction temperature Yield
time, h
°C
%
Purity
(HPLC method)
Model water sample
CH3NHC(S)NH2
0.10
0.11
0.11
4.0-5.0
40-45
72.2
202-205 (202-203) [33]
98.5
(CH3)2NC(S)NH2
0.11
0.10
0.12
5.0-5.5
45-55
68.3
161-164 (163-164) [34]
98.7
EtNHC(S)NH2
0.10
0.11
0.11
4.0-4.5
40-45
72.5
109-111 (110-111) [35]
98.6
Et2NC(S)NH2
0.10
0.12
0.12
5.0-6.0
50-60
67.8
97.5-99.0 (99.2-100.6) [34]
98.9
PrNHC(S)NH2
0.10
0.11
0.11
4.0-5.0
45-55
71.3
108-111 (109) [36]
99.0
Pr2NC(S)NH2
0.10
0.12
0.13
5.5-6.0
55-65
66.7
110-111 [37]
98.9
CH3NHC(S)NH2
0.05
0.07
0.07
4.0-5.0
40-45
54.7
200-202 (202-203) [33]
97.1
(CH3)2NC(S)NH2
0.06
0.06
0.06
5.0-5.5
45-55
48.6
160-163 (163-164) [34]
98.0
EtNHC(S)NH2
0.05
0.07
0.07
4.0-4.5
40-45
49.5
108-110 (110-111) [35]
97.6
Et2NC(S)NH2
0.05
0.08
0.08
5.0-6.0
50-60
51.2
97-99 (99.2-100.6) [34]
98.2
PrNHC(S)NH2
0.05
0.07
0.07
4.0-5.0
45-55
50.7
105-108 (109) [36]
98.2
Pr2NC(S)NH2
0.05
0.08
0.08
5.5-6.0
55-65
42.8
108-111 [37]
97.2
Real water sample
thiocyanate 8.9%, sulfate 1.6%, phosphate 0.8% and
cations (K, Na, Ca, Mg, Fe, etc.) in overall content of
around 2.6%. Results of N-alkyl and N,N-dialkyl thiourea synthesis are given in Tables 1 and 2. The structure of the synthesized products was confirmed by IR,
1
H- and 13C-NMR spectroscopic, and MS spectrometric data (Table 3).
Semi-industrial development of ammonium
thiocyanate water solution treatment as
by-product from TMTS production plant
A schematic presentation of the developed technology at semi-industrial level for waste water treatment containing ammonium thiocyanate, obtained
from TMTS production facility, is given in Figure 1.
Table 3. 1H- and 13C-NMR data, as well as results of elemental and IR analysis of N-alkyl and N, N-dialkylthioureas
Product
CH3NHC(S)NH2
1
13
H-NMR (δ / ppm)
C-NMR (δ / ppm)
2.71 (CH3), 7.46 (NH), 7.08 (NH2)
30.9 (CH3), 183.1 (CS)
Elemental analysis
Calculated/Found (%)
C 26.65; H 6.71; N 31.08; S 35.57
C 26.52; H 6.78; N 31.22; S 35.48
(CH3)2NC(S)NH2
3.05 (CH3), 7.10 (NH2)
31.3 (CH3), 182.9 (CS)
C 34.59; H 7.74; N 26.89; S 30.78
C 34.64; H 7.78; N 26.95; S 30.63
EtNHC(S)NH2
1.19 (CH2-CH3), 3.51 (CH2-CH3),
7.49 (NH), 7.11 (NH2)
14.53 (CH2-CH3), 39.12 (CH2-CH3),
182.2 (CS)
C 34.59; H 7.74; N 26.89; S 30.78
Et2NC(S)NH2
1.03 (CH2-CH3), 3.13 (CH2-CH3),
7.11 (NH2)
12.83 (CH2-CH3), 41.37 (CH2-CH3),
181.6 (CS)
C 45.42. H 9.15. N 21.19; S 24.25
0.81 (CH2-CH2-CH3), 1.47
(CH2-CH2-CH3), 2.63 (CH2-CH2-CH3),
7.51 (NH), 7.10 (NH2)
10.93 (CH2-CH2-CH3), 21.55
(CH2-CH2-CH3), 43.75
(CH2-CH2-CH3), 181.4 (CS)
C 40.65; H 8.53; N 23.70; S 27.13
0.78 (CH2-CH2-CH3), 1.31
(CH2-CH2-CH3), 2.11 (CH2-CH2-CH3),
7.12 (NH2)
11.78 (CH2-CH2-CH3), 21.05
(CH2-CH2-CH3), 53.75
(CH2-CH2-CH3), 180.53 (CS)
C 52.45; H 10.06; N 17.48; S 20.01
PrNHC(S)NH2
Pr2NC(S)NH2
Product
IR, νmax / cm
-1
C 34.54; H 7.71; N 26.80; S 30.95
C 45.40; H 9.04; N 21.26; S 24.30
C 40.69; H 8.44; N 23.62; S 27.25
C 52.38; H 10.11; N 17.42; S 20.09
MS (m/z)
CH3NHC(S)NH2
3260, 3167 (NH, NH2), 2924, 2855, 1633 (NH2), 1557, 1465, 1300, 1152
(C=S), 1127
90
(CH3)2NC(S)NH2
3247 (NH2), 2935, 2865, 1628 (NH2), 1539, 1499, 1468, 1257, 1064 (C=S),
1048
104
3263, 3169 (NH, NH2), 2958, 2925, 2853, 1634 (NH2), 1554, 1464, 1302,
1155 (C=S), 1123
104
EtNHC(S)NH2
504
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
Table 3. Continued
IR, νmax / cm
Product
-1
MS (m/z)
Et2NC(S)NH2
3275, 3174 (NH2), 2938, 2867, 1630 (NH2), 1532, 1493, 1461, 1254,
1061 (C=S), 1045
132
PrNHC(S)NH2
3165 (NH, NH2), 2920, 2851, 1638 (NH2), 1543, 1462, 1300, 1163 (C=S),
1115 (C=S)
118
Pr2NC(S)NH2
3277 (NH2), 2939, 2866, 1631 (NH2), 1529, 1492, 1459, 1250, 1060 (C=S),
1039 (C=S)
160
Figure 1. Schematic presentation of semi-industrial production technology of N-alkyl and N,N-dialkyl thioureas.
TMTS is produced by heterolytic cleavage of
disulfide bridge present in TMTD by nucleophilic
attack of cyanide ion introduced by potassium cyanide in the presence of ammonium chloride as an pH
controlling agent (provide pH of reaction mixture in
the range 6-7). In the course of the production of
TMTS, waste water containing by-product ammonium
thiocyanate is inevitably generated. Method for the
processing of waste water included filtration and tran-
sport to reactor 3 (6 m3). Treatment of waste water by
the Method I was performed by the addition of alkyl
amine and hydrochloric acid (Table 4), vacuum treatment (10 KPa) for 10 min and ethyl acetate introduction into reaction mixture. After stirring of reaction
mixture at 80–90 °C for 3 h, obtained suspension was
filtered through a Buchner funnel (position 4). The
filtration cake contained technical ammonium chloride
and after purification and drying it could be used as
505
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
Table 4. Results of of N-ethyl and N,N-diethyl thiourea synthesis performed at semi-industrial level; reactant: EtNH2 (70%, ρ = 0.88
g/cm3, HCl (15%, ρ = 1.01 g/cm3), EtOOCCH3 (ρ = 0.89 g/cm3), MeOH ( ρ = 0.80 g/cm3), PhCOCl (ρ = 1.21 g/cm3), NaOH (20%, ρ =
1.2 g/cm3); Et2NH (98.5%, ρ = 0.71 g/cm3, HCl (15%, ρ = 1.01 g/cm3), EtOOCCH3 (ρ = 0.89 g/cm3) MeOH ( ρ = 0.80 g/cm3), PhCOCl (ρ
= 1.21 g/cm3), NaOH (20%, ρ = 1.2 g/cm3)
Reactant
Batch/
method
Waste Ethyl HCl
3
water amine (m )
3
(m ) (m3)
Reaction
condition
Ethyl MeOH ArCOCl NaOH
3
3
3
m
m
acetate
m
3
(m )
By-product
Product
Time Tempera- NH4Cl ArCOOH Yield Yield Purity
3
kg
m
h
ture, °C
kg
%
HPLC
Melting
point, °C
N-Ethyl thiourea
a
0.19 0.07
0.60
0.80
-
-
5.0
80-90
96.0
-
a
0.23 0.08
0.60
0.80
-
-
5.1
80-90
99.0
-
1/Method I
1.0
2/Method I
1.0
3/Method II
a
1.0
0.19
-
-
0.80
0.32
0.51
6.0
45-55
-
0.5
c
140.6
51.4
96.1
111-113
b
153.7
56.2
96.3
110-112
b
144.0
52.7
95.9
110-111
b
134.7
49.3
96.1
97-99
137.0
50.4
96.5
98-100
d
124.5
45.6
96.3
97-100
d
96.0
d
N,N-Diethyl thiourea
1/Method I
2/Method I
3/Method II
1/Method I
a
0.27 0.08
0.60
0.85
-
-
5.5
85-90
95.5
-
a
0.32 0.08
0.60
0.85
-
-
5.7
85-90
98.5
-
1.0
1.0
a
1.0
a
1.0
0.27
-
0.27 0.08
0.60
0.85
0.85
0.33
-
0.55
-
a
c
6.5
55-60
5.5
85-90
95.5
0.45
-
c
134.2
49.1
97-99
d
b
Quantity of ammonium thiocyanate in waste water - 200 kg (20% water solution); literature value of melting point of EtNHC(S)NH2 is 110-111 °C [35];
collected ArCOOH in water solution (concentration 40%); dliterature value of melting point of Et2NC(S)NH2 is 97-99 °C (99.2-100.6 °C) [34]
commercial product. Filtrate was consisted from two
layers: upper one contained dissolved product in ethyl
acetate and lower one was water layer which contained mostly inorganic salts. After separation from
water layer, upper layer was dried and subjected to
atmospheric distillation to remove ethyl acetate, followed by vacuum distillation applied to evacuate residual solvent and higher boiling materials (position 5).
Satisfactory quality for commercial application was
achieved by recrystallization (position 6) from methanol producing 140.6 kg (51.4%) and 96.1% purity of
N-ethyl thiourea, obtained by HPLC analysis (Table 4).
Production of N-ethyl thiourea (Method II) was
performed by transferring the waste water, containing
ammonium thiocyanate, into reactor 7 following by
addition of benzoyl chloride and alkyl amine (Table 4).
The reaction took place for 2 h at 45 °C, after what
reaction mixture was cooled down to room temperature. Addition of 0.51 m3 (20%) sodium hydroxide and
continuation of the mixing for 30 min provided hydrolysis of N-benzoyl-N-ethyl thiourea (position 8). The
reaction mixture was filtered through a Buchner funnel, the water solution of sodium benzoate was collected and filtration cake contained raw product. The
raw product was purified by double recrystallization
from methanol (position 6) producing 144.0 kg (52.7%)
of N-ethyl thiourea (HPLC purity 95.9%) (Table 4).
Analogous synthesis of N,N-diethyl thiourea was
performed at semi-industrial level (Table 4).
506
Instrumental techniques used for structure
determination of synthesized compounds
1
H- and 13C-NMR measurements were performed
on a Varian Gemini 2000 (200/50 MHz) instrument at
25 °C. Chemical shifts (δ) were reported in part per
million (ppm) relative to tetramethylsilane (δH = 0
ppm) in 1H-NMR, and to deuterated chloroform (δC =
= 77.2 ppm) in 13C-NMR, using the residual solvent
peak as a reference standard. Fourier-transform
infrared (FTIR) spectra were recorded in transmission
mode using a BOMEM (Hartmann & Braun) spectrometer. All mass spectra were recorded on a Thermo
Finnigan Polaris Q ion trap mass spectrometer, including TraceGC 2000 (ThermoFinnigan Corp., Austin,
TX, USA). Polaris Q ion trap GC/MS system with EI
and DIP (direct insertion probe) techniques was used.
DIP mode was used to introduce the sample and
EI/MS technique to acquire the spectra. The ionization conditions were: ion source temperature 200
°C, maximum energy of electron excitation 70 eV,
corona current 150 μA. The data obtained were processed using XcaliburTM 1.3 software. HPLC (high
performance liquid chromatograph) was performed on
Spectra System P4000 equipped with a UV detector,
Zorbax SB-C8 column, mobile phase benzene/methanol (HPLC grade) (9:1), isocratic mode. Elemental
analysis was performed on the Vario EL III elemental
analyzer, and the results of analysis are in good
agreement with theoretical values (±0.2%).
The concentration of starting ammonium-thiocyanate in waste water was determined according to
two methods: the Vollhard method [30], and method
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
based on thiocyanate reaction with thioglycolic acid
which provide quantitative conversion to N-substituted thiocarbamoylmercaptoacetate or 3-substituted
rhodamine, a product with characteristic UV absorption [31]. Determination of cations concentrations in
water solution from TMTS semi-industrial production
plant was performed by the use of inductively coupled
plasma mass spectrometry (ICP-MS) using an Agilent
7500ce ICP-MS system (Waldbronn, Germany) and
Perkin Elmer Analyst 200, MHS 15 (Waltham, MA,
USA). ICP-MS was equipped with an octopole collision/reaction cell, Agilent 7500 ICP-MS ChemStation
software, a MicroMist nebulizer and a Peltier cooled
(2.0 °C) quartz Scott-type double pass spray chamber. Standard optimization procedures and criteria are
specified in the manufacturer’s instruction manual.
Sulfate was determined by using standard gravimetric
method, and phosphate by spectrophotometric method
according to the Deniges procedure [32].
RESULTS AND DISCUSSION
In the experimental part of this work, optimal
parameters for N-alkyl and N,N-dialkyl thioureas synthesis (Methods I and II - Experimental) were postulated. In both methods a model and waste water
containing ammonium thiocyanate (the latter one is
obtained during the synthesis of TMTS) were used in
reaction with corresponding amine. Optimal conditions for N-alkyl and N,N-dialkyl thioureas synthesis
were selected on the basis of maxima yield and purity
of the product in relation to variable reaction parameters: reaction time, temperature and molar ratio of
reactants. The obtained optimal results of N-alkyl and
N,N-dialkyl thioureas synthesis are presented in
Tables 1 and 2.
Based on the results given in Tables 1 and 2, it
can be observed that high yields and purity of synthesized N-alkyl and N, N-dialkyl thioureas are
achieved starting from model and waste water containing ammonium thiocyanate. General consideration of the presented results clearly indicates somewhat higher yields obtained by the use of model
water. Such result is obviously a consequence of the
presence of interfering ions, which could have a detrimental effect on the reaction yield. The structure of
synthesized products was confirmed by IR, 1H-NMR
and MS spectrometric data (Table 3).
From the reaction yield and purity of the
obtained product, shown in Table 1, it can be concluded that an increase of the amount of the secondary amine over 0.12 mol have no influence on the
yield and purity of the synthesized N-alkyl and N,N-
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
-dialkyl thioureas. It may be noted that with the use of
secondary alkyl amines, at equimolar ratio of reactants, a negligible increase of the product yield from
70.0 to 71.0% is obtained. Also, it is interesting that if
the primary alkyl amine is used, wherein the thiocyanate is in excess, the yield is in the range from 73.2 to
76.2%. Thus, it can be deduced that the higher yield
is obtained by reaction of the primary amine with
ammonium thiocyanate, while the lowest yield is
obtained using dipropylamine as reactant. The longer
reaction time, more than six hours, and an reaction
temperature increase does not give a higher yield of
N,N-dialkyl thiourea (Method I).
Based on the data presented in Tables 1 and 2,
higher yields of N-alkyl and N,N-dialkyl thioureas
obtained following Method I could be assumed. Similar influences of amine structure on reaction yields is
obtained by comparing Methods I and II, while the
lowest yield for dipropyl amine (70.0% by Method I
and 66.7% by Method II) is observed (Tables 1 and
2). Also, longer reaction time and higher temperature
are applied for reaction performed in presence of disubstituted amines.
Analysis of the experimental data indicates that
influence of structural features of reacting species, i.e.
amine effect on the yield of N-alkyl and N,N-dialkylthioureas, could be discussed. Considering stereochemical aspect of amine involved in creation of activated complex indicate a significant influence of the
steric effect of the amine alkyl group on the stability of
activated complex. The lower yield found in reactions
with disubstituted alkyl amines is an indication of the
existence of more pronounced repulsive steric interaction of the alkyl groups in the activated complex.
More intensive steric repulsion of voluminous alkyl
groups presented in the disubstituted amine cause
decreasing of the ability of the amine to access to the
reaction center, i.e., electrophilic carbon of thiocyanate group. Reduced effectiveness of the amine
group to exert a nucleophilic attack caused a decrease in reaction yield. The higher reaction yield of
thiourea product obtained by Method I, in comparison
to Method II, could be reasonably explained by complexity of the reaction mechanism, due to high reactivity of benzoyl chloride and ability of N-benzoyl-N,N-dilakyl thiourea to participate in a side reaction
(Figure 2). It can be assumed that Method I takes
place as a one-step reaction by nucleophilic addition
of amine at the thiocyanate group, while in Method II,
a multistep reaction mechanism is operative. Nucleophilic attack of the thiocyanate anion to the carbonyl
group of benzoyl chloride occurs in the first step of
reaction mechanism following by an attack of the
507
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)
Figure 2. Proposed mechanisms of N-alkyl and N,N-dialkyl thioureas synthesis performed according to Method I and II.
amine on the thiocarbonyl carbon of the obtained
benzoyl thiocyanate in the second step. Basic hydrolysis of the intermediary compound produce benzoic
acid and N-alkyl and N,N-dialkyl thioureas product
(Figure 2).
The probable reaction mechanisms of the N-alkyl and N,N-dialkylthioureas synthesis performed
by Method I [8], and Method II, over benzoylthiocyanate intermediary compound and N-benzoyl-N,Ndilakyl thiourea [13], are presented in Figure 2.
Semi-industrial synthesis of N-ethyl and N,N-diethyl
thiourea
Based on the laboratory results of waste water
treatment containing thiocyanate from the synthesis
of the TMTS (Methods I and II), we transferred developed laboratory technology to semi-industrial level.
The described technological procedure of waste
water treatment in the production of the TMTS actually represents a new technological process for the
alkyl tioureas synthesis using waste water from the
production of the TMTS and the TMTD, which contains the ammonium thiocyanate. The results of semiindustrial synthesis of N-ethyl and N,N-diethyl thiourea, from ammonium thiocyanate present in the
508
waste water from the production plant of TMTS, are
summarized in Table 4.
The defined synthetic procedure, Method I, is
applied in Batches 1 and 2 (Table 4). In comparison
to Batch 1, where the thiocyanate excess of the 20%
is used and 51.4% yield is achieved, equimolar ratio
of the reactants increased yield to 56.2% in Batch 2.
However, as a result of Method II, reaction yield of
Batch 3 is lower than Batch 2, where Method I is
used. Identical reaction conditions presented in Table
4 are applied in a pilot-plant production of N,N-diethyl
thiourea (Table 4). It can be seen that the lower yields
is achieved in all three batches with N,N-diethyl thiourea in regards to the yields of pilot-plant synthesis of
N-ethyl thiourea (Table 4). On the basis of the results
obtained by the semi-industrial production process it
can be concluded that a) wastewater from the production TMTS's can be treated in two ways, b) significant conversion is achieved (over 45%) in all of the
three batches shown in Table 4 and the final commercial products of N-ethyl and N,N-diethylthiourea
are the high level of purity determined by the HPLC
method, c) the structure of the isolated components
and all of the synthesized products are confirmed by
instrumental methods.
M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL…
Developed optimal methods offers good alternative technology for industrial exploitation in production of N-alkyl and N,N-dialkylthiourea from commercial ammonium thiocyanate, or more preferably
from waste water containing this reactant obtained
from TMTS production plant. From an ecological point
of view, both facts related to use waste water as the
reaction medium and by-product ammonium thiocyanate as reagent in the synthesis of N-alkyl and N,N-dialkyl thioureas, indicate that such technology is
highly favorable to be implemented at semi-industrial
level. These environmentally friendly and simple processes, with short reaction times, represent a suitable
option to existing methods. This concept contributes
to the remarkable effectiveness and economic benefit
of the implemented optimal laboratory procedure at
the semi-industrial level.
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CONCLUSION
The results presented in this work describe an
optimal procedure for the laboratory and semi-industrial synthesis of N-alkyl and N,N-dialkyl thioureas.
The developed processes, presented by Method I and
Method II, start from either model or waste water
containing ammonium thiocyanate. High purity and
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synthesis were obtained by applying optimal Methods
I and II in both laboratory and semi-industrial level.
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duration and simplicity as well as low impact to the
environment. These results strongly indicate the usefulness of the presented methods for synthesis of
thiourea derivatives starting from commercial as well
as industrial waste material.
Acknowledgements
This study was carried out within the project
“Exploring the impact of climate change on the living
environment: monitoring of impact, adaptation, mitigation” (43007) funded by the Ministry of Education
and Science of the Republic of Serbia in the framework of integrated and interdisciplinary research including the period 2011-2015 year.
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1960
MILUTIN M. MILOSAVLJEVIĆ1
IVAN M. VUKIĆEVIĆ1
VEIS ŠERIFI1
2
JASMINA S. MARKOVSKI
3
IVANA STOJILJKOVIĆ
DUŠAN Ž. MIJIN4
ALEKSANDAR D. MARINKOVIĆ4
1
Fakultet Tehničkih Nauka, Univerzitet
u Prištini, Kosovska Mitrovica, Srbija
2
Institut za Nuklearne nauke Vinča,
Univerzitet u Beogradu, Beograd,
Srbija
3
Hemijski Fakultet, Univerzitet u
Beogradu, Beograd, Srbija
4
Tehnološko-Metalurški fakultet,
Univerzitet u Beogradu, Beograd,
Srbija
NAUČNI RAD
Ĺ. Drobnica, W. Knoppová, Chem. Zvesti 27(6) (1973)
799-780
OPTIMIZACIJA POSTUPAKA SINTEZE N-ALKIL- I
N,N-DIALKILTIOUREA IZ OTPADNE VODE KOJA
SADRŽI AMONIJUM-TIOCIJANAT
Optimizovane metode za sintezu N-alkil- i N,N-dialkiltiourea, koje polaze iz amonijum-tiocijanata, koji se nalazi u otpadnoj vodi iz proizvodnje tetrametiltiuram-monosulfida
(TMTS), i alkilamina, prikazane su u ovom radu. Osvojene su dve metode sinteze tiouree:
Metoda I − reakcija tiocijanata u prisustvu hlorovodonične kiseline; Metoda II − reakcija
tiocijanata sa benzoil-hloridom nakon čega sledi dodavanje odgovarajućeg amina u prvom
koraku, i bazne hidrolize inermedijera u drugom koraku. Struktura sintetisanih tiourea je
potvrđena na osnovu podataka iz IR, 1H- i 13C-NMR, kao i MS spektara, a čistoća je
potvrđena primenom metode tečne hromatografije pod visokim pritiskom. Pokazano je da
se primenom optimalnih metoda dobijaju visoki prinosi i čistoća proizvoda, a usled odsustva sporednih proizvoda metode su primenjive na industrijskom nivou proizvodnje. Uzimajući u obzir značaj tetrametiltiuram-disulfida (TMTD) i TMTS kao ubrzivača vulkanizacije
i tiouree kao potencijanih farmakološki aktivnih jedinjenja, može se konstatovati da će
primena optimizovanih metoda sinteze tiouree obezbediti značajna poboljšanja u primeni
zelenih tehnologija u proizvodnoj praksi, kao i doprineti održivom razvoju. Opisani procesi
sinteze tiourea imaju mali uticaj na životnu sredinu i zbog toga predstavljaju prihvatljive
opcije za primenu u odnosu na postojeće metode sinteze tiourea.
Ključne reči: tiourea, optimizacija, polu-industrijski nivo proizvodnje, tiocijanat.
510
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
SHENG FANG
LI-PING WANG
TING WU
School of Food Science and
Biotechnology Engineering,
Zhejiang Gongshang University,
Hangzhou, China
SCIENTIFIC PAPER
UDC 633.685(510):66.047.4/.6:51
DOI 10.2298/CICEQ140816007F
CI&CEQ
MATHEMATICAL MODELING AND EFFECT OF
BLANCHING PRETREATMENT ON THE
DRYING KINETICS OF CHINESE YAM
(Dioscorea opposita)
Article Highlights
• Drying kinetics of Chinese yam slices are investigated
• Effects of blanching pretreatment on drying kinetics
• Six thin layer drying models are compared
• The effective diffusivities and activation energy are obtained
Abstract
The effects of blanching pretreatment on the drying kinetics of Chinese yam
(Dioscorea opposita) slices were investigated. Drying experiments were carried out at 60, 70, 80 and 90 °C. Six thin layer models were evaluated and the
coefficient of determination (R2), chi-square (χ2), and root means square error
(RMSE) were used to analyze the model performance for both raw and
blanched samples. The Wang and Singh model gave best results with R2 of
0.9987 and RMSE of 0.0136 for raw yam slices, and R2 of 0.9989 and RMSE
of 0.0119 for blanched samples. The effective moisture diffusivity coefficient
Deff varied in the range of 0.7295×10-9 to 2.4087×10-9 m2 s-1 for raw slices, and
1.3748×10-9 to 3.8524×10-9 m2 s-1 for the blanched ones. The activation energies of yam slices drying were 41.149 and 33.499 kJ mol-1 for raw and blanched
yam slices, respectively. The results show that blanching pretreatment can
reduce the total drying time and improve the effective moisture diffusivity compared to the raw samples.
Keywords: Chinese yam, hot air drying, kinetics, modeling, blanching.
The Chinese yam (Dioscorea opposita), called
“Shan Yao” (which means “mountain medicine”) in
Chinese herbalism, has a long history of cultivation in
China and Eastern Asia for its edible tuber [1]. The
yam tuber is also a traditional ingredient of herbs that
prescribed in Chinese herbalism to treat diseases like
nephritis, hyperthyroidism and diabetes [1]. It contains
a large amount of water, similar to fruits, and can be
eaten raw or cooked before consumption. The dried
yam slices can be served fried, roasted and boiled,
used as an ingredient in herbs and for the production
of yam starch [2].
Correspondence: S. Fang, School of Food Science and Biotechnology Engineering, Zhejiang Gongshang University, Hangzhou 310018, China.
E-mail: fszjgsu@163.com
Paper received: 16 August, 2014
Paper revised: 29 January, 2015
Paper accepted: 19 February, 2015
Drying is one of the most important preservation
processes commonly used for food products that are
easily deteriorated [3]. As a simple postharvest technology, drying can prolong the shelf life of food products, and reduction in volume and weight in favor of
transportation. Drying can also preserve food quality
by lowering their water activity, thus avoiding contamination and spoilage during transportation and storage. Convective drying by hot air is a common technology for food postharvest processing because of its
large scalability and easy to performance [3,4]. However, hot air drying is a high energy consumption
process. It is a complex process containing both the
heat and mass transfer where water is transferred
from the inside of food materials to the outside atmosphere by diffusion, which is very slow. The total
energy consumption in hot air drying process depends on many parameters such as pretreatments,
drying temperature drying time and air velocity [4,5].
511
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
High drying temperature may shorten the drying time,
however, it can bring disadvantages such as color
deterioration and nutrients degradation [5,6]. Previously, many investigations have explored the effects
of different drying parameters, including drying temperature, air velocity, relative humidity and sample
thickness on the drying characteristics of agricultural
and food products, such as bottle gourd [7], Chinese
jujube [8], carrots [9], sweet potatoes [10,11] and
pumpkins [12].
Meanwhile, many pretreatments methods are
employed in order to mitigate quality attributes degradation [3,6]. They can also reduce the total drying
time, which is more energy efficient and generate final
products with good quality. Many natural or synthetic
chemicals are used for dipping pretreatments prior to
drying such as ascorbic acids [13], potassium metabisulphide and alkaline ethyl oleate [14]. Alternatively,
raw foods and vegetables can also be pretreated by
thermal methods such as hot water blanching prior to
drying. Generally, thermal blanching is carried out by
exposing samples either at low temperature for a long
time (LTLT) or high temperature for a short time
(HTST). Blanching is the most commonly used
thermal pretreatments before processing of agricultural products as it can destroy enzymes, which
cause deterioration reactions, off-flavour and undesirable changes in color, texture and nutrients [15]. In
addition, blanching can also enhance drying rate by
expelling intercellular air from the tissues, softening
the texture or by dissociating the wax on the products
skin [16,17].
Mathematical modeling and simulation of the
drying kinetics of food products is an important tool
for designing novel drying systems, drying equipment
and minimize operative energy consumption [3]. Recently, several studies have been conducted on the
experimental and mathematical modeling of the drying characteristics of various food products, like tomato slices [18,19] and peach slices [20]. Comprehensive review [3] on the subject of mathematical
models on convective drying of different agricultural
and food materials is available. Some studies have
been published concerning the drying process of yam
[2,21-23]. However, some of them were concerning
about the drying process of yam starch [2]. Xiao et al.
[21] investigated the effect of superheated steam
blanching on the drying kinetics and quality of yam
slices under air impingement drying. Lin et al. [22]
studied the dehydration of yam slices by using FIR-assisted freeze drying. Sobukola et al. [23] studied
the convective hot air drying at temperature 70, 80
and 90 °C of blanched yam slices (Dioscorea rotun-
512
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
data) under LTLT condition and have not compared
with the raw yam slices. According to our best knowledge, the effects of temperature and steam blanching
on the dry characteristics and its modeling for Chinese yam (Dioscorea opposita) slices have not been
reported.
The objective of this study was to: a) investigate
the effect of air temperatures and steam blanching
pretreatment on the drying time and b) fit the experimental drying data of yam slices to several mathematical models available in literatures and evaluate a
suitable model to describe the process. Four temperatures 50, 60, 70 and 80 °C were investigated and
six equations were compared. The effective moisture
diffusivities at different drying temperatures for
blanched and untreated yam slices were estimated
from Fick’s law. Furthermore, the activation energy
was estimated from the Arrhenius equation.
MATERIALS AND METHODS
Materials
Chinese yams (Dioscorea opposita) were purchased from a local supermarket (Hangzhou Wumart
Supermarket) in Hangzhou, China. They were selected by homogeneous diameter as well as the absence of physical damage. The yams were washed by
tap water and put into a refrigerator at about 4 °C for
storage before usage.
Experimental apparatus
The drying experiments were performed in a
continuous convective dryer as described previously
by Meng et al. [24]. It is composed of a heater,
blower, square air tunnel and other temperature
instruments and is shown in Figure 1. The air was
sucked by the blower and heated to the desired
temperature automatically by regulating voltage to the
heaters inside the air channel. The air velocity is controlled by a revolution speed regulator. A digital electronic balance (Model BS124S, Beijing Sartorius instrument system Co., LTD., China) with an accuracy of
0.01 g and a range of 0-210 g was used to continuously measure the moisture loss of samples. The
values shown in the electronic balance were monitored by a camera connected to a computer for recording.
Experimental procedures
Yams were cut into cylindrical slices homogeneously with height of 3±0.2 mm and diameter of
15±0.2 mm. The slices were put into the drying
chamber after the target condition was steady for
about 1 h. Then, the slices were placed on wire
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
Figure 1. Schematic diagram of drying equipment.
meshes, which were weighed by the electronic balance. The experiments were performed at air temperatures 50, 60, 70 and 80 °C with a constant perpendicular air velocity of 1.2 m s-1. The mass of yam
slices were recorded at first and about 17.5±0.5 g of
yam samples were utilized in the each run. The
weight of slices was recorded continuously at 3 s
intervals during the drying process. For drawing the
drying curve, the time for certain change of slice
weight was obtained by manual statistics. The drying
process was stopped until the weight of slices was
invariable for more than 2 h. The final weight of dried
slices was taken as the equilibrium moisture content
(Me) that used to calculate the moisture ratio (MR).
The yam slices were placed on the stainless steel
wire mesh in an electric cooker and blanched by the
saturated water steam at atmosphere. The blanching
temperature was estimated at 98±2 °C and 100%
relative humidity. All the yam slices were blanched at
the same condition for 3 min prior to drying.
Mathematical modeling of drying curves
The moisture ratio (MR) can be calculated from
the moisture content of drying sample at time t as
shown below:
MR =
Xt − X *
X0 − X *
(1)
where Xt, X0 and X* are the moisture content at time t,
the initial moisture content and the equilibrium
moisture content, respectively; and the moisture content X is expressed as:
m − md
(2)
Xt = t
md
where mt and md are the mass of sample at time t and
the final mass of dried samples, respectively.
The experimental convective drying data for
Chinese yam were fitted to six thin-layer drying
models. For the details of each model, readers can
refer to the comprehensive review [3]. The empirical
equations of each model are shown in Table 1.
The parameters of equations in Table 1 were
estimated by using the nonlinear Levenberg-Marquardt algorithm. The primary criterion for the selection
of the best equation to describe drying curves was the
coefficient of determination (R2). In addition, the chi
Table 1. Mathematical models applied to fit the drying curves
Model No.
Equation
Model name
Parameters
Reference
1
MR = exp(-kt)
2
MR = exp(-ktn)
Newton
k
[25]
Page
k, n
3
[26]
MR = aexp(-kt)
Henderson and Pabis
a, k
[27]
4
MR = 1+at+bt2
Wang and Singh
a, b
[28]
5
n
MR = aexp(-k t )
Modified page
a, k, n
[29]
6
MR = aexp(-kt)+c
Logarithmic
a, k, c
[30]
513
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
square (χ2) and root mean square error (RMSE) were
also used to determine the goodness of correlation. χ2
stands the mean square of the deviations between
the predicted and experimental values of the equation. It is known that the higher the values of R2, the
lower were the values of χ2 and RMSE, and hence the
better of model performance. These statistical parameters are calculated by equations shown as below:
χ
2

=
N
i =1
(MRi ,pre − MRi ,exp )2
N −n

RMSE =
N
i =1
(MRi ,pre − MRi ,exp )2
N
i ,exp
i ,expmean )
i =1
i ,exp
i ,expmean )
−
(5)
2
i ,expmean )
i ,exp
i =1
where MRi,pre and MRi,exp stand for the ith predicted
moisture ratio and the experimental moisture ratio,
respectively; N is the number of observations, and n
is the number of parameters in the drying equation.
Determination of effective moisture diffusivity
The effective moisture diffusivity coefficient is an
important transport property in the drying of food materials. It was calculated by fitting the experimental
data to the Fick’s second law of diffusion equation:
∂X
∂
=
∂t
∂x
∂X 

 D eff

∂x 

(6)
With the assumption of uniform initial moisture
distribution, negligible shrinkage and external resistance, constant diffusion coefficients and temperature,
the solution of Eq. (6) for slab geometry is solved as
follows [3,20]:
MR =
8
π
2
∞
1
 (2n − 1)
2
n =0
 −(2n − 1)2 π 2D efft
exp 
4L2




(7)
where Deff is the effective moisture diffusivity (m2 s-1), t
is the drying time (s), L is the half-thickness of
samples (m). When for a long drying time, Eq. (7) can
be simplified to the following equation:
MR =
514
 −π 2D efft 
exp 
2

π
 4L

8
2
 π2
Slope =  2
 4L

 D eff

(8)
(9)
When given the value of the half-thickness of
sample L, the Deff could be determined from Eq. (9).
Determination of activation energy
The activation energy for moisture diffusion, Ea,
during the drying process can be related with the
effective diffusion coefficient as following equation
[19,20]:
D eff = D0 exp  −
2
i ,exp )
i ,pre
i =1
2
Plot ln(MR) against the time t gives the value of
slope that contain the effective moisture diffusivity,
Deff, as:


Ea

 R (T + 273.15 ) 


2
i =1
N
N
N
(4)
N
 (MR − MR
R =
 (MR − MR
 (MR − MR
−
 (MR − MR
2
(3)
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
(10)
where D0 is the pre-exponential factor of the Arrhenius equation in m2 s-1, R is the universal gas constant, and T is temperature in °C.
RESULTS AND DISCUSSIONS
Influence of drying air temperature
The change of moisture ratio, MR, with drying
time at hot air temperatures of 50, 60, 70 and 80 °C
for Chinese yam slices at thickness of 3 mm and air
velocity of 1.2 m s-1 are shown in Figure 1. It is shown
that the increase in hot air temperature leads to a
decrease in the total drying time. It is well known that
the higher temperature makes the relative humidity of
air around sample slices become lower. As a result,
the heat transfer and evaporation of water from the
samples are greatly enhanced which then reduce the
drying time. However, the drying rate increased as
the temperature increased, but the increase became
gradually smaller especially for the blanched yam
slices as shown in Figure 2. Similar trends can also
be found in several studies for different agricultural
and food products [17,19-20].
On the other hand, although the increase of air
temperatures can dramatically reduce the total drying
time, it has disadvantageous effects on the total
energy consumption and the quality of end products
like the oxidation of phytochemicals and color deterioration [31]. For yam slices, it was found that the
samples dried at 80 °C had the highest drying rate in
all the temperatures concerned; however, the extent
of surface hardening and shrinkage effect was intensified on the slice surface. This can be explained by
the fact that the migration rate of moisture to the surface is lower than the moisture evaporation rate from
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
Figure 2. Drying curves at different hot air temperatures for: a) raw yam slices and b) blanched Chinese yam slices.
surface to air at that drying temperature. This allows
the presence of phenomena such as hardening and
shrinkage of yam slices. Moreover, high temperatures
will also lead to color changes, which are not desirable.
Influence of pretreatment on drying time
Pretreatment is an important parameter that
affects the drying characteristics. As can be seen in
Figure 1, the yam slices blanched prior to the hot air
drying are found to shorten the drying time compared
with the raw yam slices. For example, the total time
required for the drying of raw yam slices to the MR of
10% at 60 °C is about 110 min, while for blanched
yam slices 81 min are needed to reach this moisture
content. Blanching pretreatment can shorten the drying time with about 30% to reach the same moisture
content at that condition. Similar trends are found at
other drying temperatures. It is believed that the
blanching pretreatment can loosen the cellular network and separate along the middle lamella in organic
materials which then result in the softening of tissues
[14-17]. Moreover, it was shown that the reducing
cohesiveness of the matrix for food materials could
improve the absorption capability of water, which led
to better rehydration at their end use [32]. Furthermore, blanching pretreatment can avoid enzymes to
be active at least during the drying process [15].
These profiles have been regarded as beneficial
effects of the blanching prior to hot air drying.
Fitting of drying curves
Six thin layer drying equations listed in Table 1
are used to correlate the experimental drying data of
Chinese yam slices at 4 different drying temperatures
(50, 60, 70 and 80 °C). These equations are frequently used in literatures for the description of drying
curves. The Levenberg-Marquardt algorithm is used
to obtain the parameters of these six equations. The
statistical parameters R2, χ2 and RMSE obtained for
six equations are shown in Table 2. The best equation that can describe the hot air drying characteristics
of yam slices should with the highest R2 and lowest
values of RMSE and χ2.
The results showed in Table 2 shows that the
values of R2 are all greater than 0.94, indicating a
good fitness. The values of R2, χ2, and RMSE for
different equations for raw yam slices are range from
0.9487 to 0.9995, 0.000046 to 0.004033, and 0.006716
to 0.062729, respectively. Better results are obtained
for blanched yam slices, the values of R2, χ2 and
RMSE are range from 0.9754 to 0.9993, 0.006716 to
0.062729, and 0.006716 to 0.062729, respectively.
Model 4 (Wang and Singh) gave the best results to fit
the experimental data of yam slices for all temperatures, followed by model 5 (Modified page). The average R2 of Wang and Singh equation for different temperatures is 0.9987 and 0.9989, respectively. Hence,
the Wang and Singh model could be selected as the
most suitable model to represent the thin-layer hot air
drying behavior of the yam slices. For the convenience of calculation, the parameters of Wang and
Singh equation are shown in Table 3 for raw and
blanched yam slices. Actually, the Wang and Singh
model use the polynomial equations to represent the
logarithmic relation between MR and t. Many studies
shows that the Wang and Singh model can be well
used to represent the drying curves of different agricultural and food materials, such as green apples [33]
and long grain paddy [34].
Effective moisture diffusivity
Table 4 shows the calculated effective moisture
diffusivity, Deff, by Eq. (10) for the raw and blanched
515
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
CI&CEQ 21 (4) 511−518 (2015)
Table 2. The fitting models and statistical results for models at different temperatures
Model No.
1
2
3
4
5
6
T / °C
Raw, RMSE
χ2
R2
Blanched, RMSE
χ2
R2
50
0.057294
0.003367
0.9841
0.062116
0.003900
0.9863
60
0.062729
0.003985
0.9871
0.059828
0.003778
0.9821
70
0.061973
0.004033
0.9865
0.062944
0.004255
0.9827
80
0.057206
0.003329
0.9883
0.056986
0.003518
0.9855
50
0.023414
0.000562
0.9880
0.017363
0.000305
0.9972
60
0.014301
0.000207
0.9982
0.024514
0.000634
0.9944
70
0.015781
0.000261
0.9978
0.022517
0.000545
0.9956
80
0.012782
0.000166
0.9985
0.019905
0.000429
0.9965
50
0.049036
0.002466
0.9487
0.049015
0.002428
0.9781
60
0.048641
0.002396
0.9790
0.051900
0.002843
0.9754
70
0.049362
0.002558
0.9789
0.053918
0.003123
0.9757
80
0.044447
0.002010
0.9826
0.049064
0.002608
0.9798
50
0.006716
0.000046
0.9995
0.013151
0.000175
0.9989
60
0.016413
0.000273
0.9984
0.008714
0.000080
0.9993
70
0.014555
0.000222
0.9988
0.015315
0.000252
0.9982
80
0.016872
0.000290
0.9979
0.010302
0.000115
0.9992
50
0.017493
0.000314
0.9969
0.013696
0.000190
0.9982
60
0.010864
0.000120
0.9989
0.019307
0.000393
0.9963
70
0.013701
0.000197
0.9983
0.019506
0.000409
0.9965
80
0.010041
0.000103
0.9989
0.016632
0.000300
0.9974
50
0.013664
0.000191
0.9980
0.016379
0.000271
0.9971
60
0.020035
0.000407
0.9958
0.015276
0.000246
0.9975
70
0.018209
0.000348
0.9966
0.025000
0.000671
0.9938
80
0.029604
0.000892
0.9908
0.022917
0.000569
0.9947
Table 3. Values of parameters of the Wang and Singh equation for raw and belched samples at different temperatures
T / °C
Raw, a
b×105
Blanched, a
b×105
50
-0.007359
1.32
-0.009458
2.17
60
-0.011846
3.46
-0.015696
5.95
70
-0.014787
5.36
-0.023180
13.3
80
-0.020061
10.1
-0.027022
18.3
Table 4. The effective moisture diffusion coefficient (Deff) of raw and blanched yam at different temperatures
T / °C
Deff×109 / m2 s–1
Raw
Blanched
50
0.7295
1.3748
60
1.0126
2.3124
70
2.1314
3.5062
80
2.4087
3.8524
yam slices at different drying temperatures. The
values of Deff varied in the range of 0.7295×10-9 to
2.4087×10-9 m2 s-1 for raw yam slices, while 1.3748×109
to 3.8524×10-9 m2 s-1 for blanched samples. The
results show that the values of Deff increased with the
increase of drying temperature. For food materials,
many studies have showed that the value of Deff are in
a general range of 10-12 to 10-8 m2 s-1 [35]. Sobukola
516
et al. [23] obtained the values of Deff from 7.62×10-8 to
9.06×10-8 m2 s-1 for blanched yam slices (Dioscorea
rotundata) under LTLT pretreatment. The values of
Deff obtained in this study for Chinese yam (Dioscorea
opposita) slices are similar to those for other food
products, like 5.61×10-10 to 1.03×10-9 m2 s-1 for peach
slices at 60-80 °C [20], 1.68×10-9 to 4.77×10-9 m2 s-1
for tomatoes at 40-80 °C [36], 2.74×10-9 to 4.64×10-9
S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING…
m2 s-1 for carrot pomace at 60-75 °C [37]. The differences between these results can be explained by
effect of material type, slice thickness, temperature
and tissue characteristics. It can be found that the Deff
values are larger than some root crops with more firm
tissue characteristics, such as sweet potato slices at
level of 9.32×10-11 to 1.75×10-10 m2 s-1 at 50-70 °C
[11].
Activation energy
The activation energy of Chinese yam slices
drying at temperature range 50-80 °C is obtained by
the Arrhenius relationship as shown in the Eq. (10).
The results and values are shown in the Eq. (11) and
(12) for raw and blanched yam slices with R2 of
0.9407 and 0.9400, respectively:


−41149

 R (T + 273.15) 
Deff,raw = 3.223 × 10−3 exp 

Deff,blanched = 3.879 × 10−4 exp 
−33499
(11)


 R (T + 273.15) 
(12)
As shown in Figure 3, the values of activation
energy are found to be 41.149 and 33.499 kJ mol-1 for
raw and blanched yam slices, respectively. The
values of activation energy of yam slice are in the
range of 15-40 kJ mol-1 found for various food materials [3]. As can be seen above, the obtained activation energy are similar to those found by other
authors for different agricultural and food products:
28.14 kJ mol-1 for tiger nuts [38]; 25.35 to 30.83 kJ
mol-1 for blanched eggplant slices [39]; 38.78 kJ mol-1
in cape gooseberry [40]; 37.76 kJ mol-1 in red chilies
drying [41].
Figure 3.The relationship of ln Deff and 1/R(T+273.15) for the
raw and blanched yam.
Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)
CONCLUSIONS
The effects of temperature on drying characteristics of raw and blanched Chinese yam slices
were investigated. The results show that blanching
pretreatment can reduce the total drying time compared to the raw samples. Six thin layer drying
models were calculated and compared by their capability in the correlation of drying curves at four temperatures. The Wang and Singh model gave best
results with R2 of 0.9987 and RMSE of 0.0136 for raw
yam slices, and R2 of 0.9989 and RMSE of 0.0119 for
blanched samples. The effective moisture diffusivity
coefficient, Deff, varied in the range of 0.7295×10-9 to
2.4087×10-9 m2 s-1 for raw slices, and 1.3748×10-9 to
3.8524×10-9 m2 s-1 for blanched samples. The activation energy of yam slices drying were 41.149 and
33.499 kJ mol-1 for raw and blanched yam slices,
respectively.
Acknowledgements
The authors acknowledge financial support from
the National Natural Science Foundation of China
(21006094).
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SHENG FANG
LI-PING WANG
TING WU
School of Food Science and
Biotechnology Engineering, Zhejiang
Gongshang University, Hangzhou,
China
NAUČNI RAD
MATEMATIČKO MODELOVANJE I EFEKAT
PRETRETMANA BLAŠIRANJEM NA KINETIKU
SUŠENJA KINESKOG JAMA (Dioscorea opposita)
U radu je analiziran uticaj pretretmana blaširanjem na kinetiku sušenja kriški kineskog
jama (Dioscorea opposita). Eksperimenti sušenja su izvedeni na temperaturama od 60,
70, 80 i 90 °C. Analizirano je šest modela sušenja tankog sloja. Koeficijent determinacije
(R2), hi-kvadrat test (χ2) i srednja kvadratna greška (RMSE) su korišćeni za analizu
performansi modela za sirove i blanširane uzorke. Wang i Singh model daje najbolje rezultate sa R2 = 0,9987 i RMSE = 0,0136 za sirove uzorke, kao i R2 = 0,9989 i RMSE = 0,0119
za blanširane uzorke. Efektivni koeficijent difuzivnosti vlage je u opsegu od 0,7295×10-9 do
2,4087×10-9 m2 s-1 za sirove uzorke, a u opsegu od 1,3748×10-9 do 3,8524×10-9 m2 s-1 za
blanširane uzorke. Energija aktivacije za sirove i blanširane kriške iznosi 41,149 i 33,499
kJ mol-1, redom. Rezultati pokazuju da pretretman blaširanjem može da smanji ukupno
vreme sušenja i da poboljša efektivnu difuzivnosts vlage u odnosu na sirove uzorke.
Ključne reči: kineski jam, sušenje toplim vazduhom, kinetika, modelovanje, blanširanje.
518
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
ZORANA ARSENIJEVIĆ1
TATJANA KALUĐEROVIĆ
RADOIČIĆ2
MIHAL ĐURIŠ1
ŽELJKO GRBAVČIĆ 2
1
Institute of Chemistry, Technology
and Metallurgy - Department of
Catalysis and Chemical
Engineering, University of
Belgrade, Belgrade, Serbia
2
Faculty of Technology and
Metallurgy, University of Belgrade,
Belgrade, Serbia
CI&CEQ
EXPERIMENTAL INVESTIGATION OF HEAT
TRANSFER IN THREE-PHASE FLUIDIZED
BED COOLING COLUMN
Article Highlights
• A three-phase fluidized bed was used to study the heat transfer characteristics of the
system
• The overall heat transfer in this system was compared to the existing literature correlations
• The smallest error for the case of heat transfer correlation for fluidized beds was
obtained
• A new correlation was proposed specifically for the three-phase countercurrent contactor
• Hydrodynamic parameters were calculated according to the available literature correlations
SCIENTIFIC PAPER
Abstract
UDC 66.096.5:536.2:51
DOI 10.2298/CICEQ141022008A
A three-phase (gas-liquid-solid) fluidized bed was used to study the heat
transfer characteristics of a system consisting of low-density (290 kg/m3)
spherical particles (2 cm diameter) in a 0.25 m cylindrical column with countercurrent flow of water and air. The experimental investigation and mathematical
modeling of heat transfer between the hot air and the cooling water was carried out. The experiments were conducted for a variety of different fluid flow
rates and inlet air temperatures, while the air flow rate was kept constant.
Based on the obtained experimental results, a new correlation for heat transfer
in a three-phase fluidized system was proposed. The mean percentage error
between the experimental and the correlated values of the jHp obtained was
1.69%. The hydrodynamic parameters of the system were also calculated
according to the available literature correlations.
Keywords: turbulent bed contactor, fluidization, heat transfer coefficient,
hydrodynamics.
Three-phase fluidized bed systems provide very
efficient contact between the present solid, liquid and
gaseous phases. They can be applied in various
physical, chemical and biochemical processes [1].
Three-phase fluidized bed systems offer considerable
advantages over conventional packed-bed columns
because they operate at high gas velocities, they
have high mass-transfer rates and the mobility of the
packing prevents plugging. This makes three-phase
systems suitable for handling streams containing parCorrespondence: Z. Arsenijević, Institute of Chemistry, Technology and Metallurgy - Department of Catalysis and Chemical
Engineering, University of Belgrade, Njegoševa 12, Belgrade,
Serbia.
E-mail: zorana@tmf.bg.ac.rs
Paper received: 22 October, 2014
Paper revised: 9 February, 2015
Paper accepted: 10 March, 2015
ticulate matter and precipitates. In addition, there is
practically no channeling or bypassing. The high gas
and liquid throughputs are made possible by bed
expansion by which the flooding is avoided. Some of
the disadvantages of three-phase systems include
bed pulsations, back mixing in the liquid phase and
mechanical erosion of the packing spheres. However,
the characteristics of high capacity and high mass
transfer and particulate removal rate enabled their
successful industrial application. Hydrodynamic properties of three-phase fluidized beds such as bed
pressure drop, minimum fluidization velocity, liquid
phase holdup, bubble properties, mixing characteristics and bed expansion are very important for analyzing their performance [2-16].
There are several types of three-phase fluidized
bed systems [5]. The flow of the liquid and the gase-
519
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
ous phases in three-phase systems can be cocurrent
or countercurrent. In the case of cocurrent flow of the
liquid and the gas phase, the particles constituting the
fluidized bed are usually of high density and of small
particle diameter. In the case of countercurrent flow of
the fluid phases, the fluidization phase can be either
the gas or the liquid phase. Countercurrent fluidized
beds in which the gaseous phase is used as fluidizing
agent are characterized by the large spherical particles of low density. These types of contactors are
often referred to as turbulent bed contactors (TBC). In
this work, a countercurrent system was investigated,
in which the gaseous phase (air) flows upwards and
is used as a fluidizing medium, while the liquid phase
(water) flows downwards and is used as a cooling
medium.
O'Neill et al. [3] classified the operating regimes
of the three-phase turbulent bed contactors as type I
and type II. In type I regime, fluidization begins before
flooding in the column, while for type II regime, fluidization begins after flooding in the column. VunjakNovakovic et al. [4] developed a chart that can be
used for the determination of the type of operating
regime in TBC systems.
Packing density contributes significantly to the
operating mode. Generally, the packing density of
more than 300 kg/m3 is characteristic of the type II
regime, while the packing density of less than 300
kg/m3 is characteristic of the type I regime. Increasing
the flow rate of the liquid phase and the reduction of
the particle diameter of the package also changes the
mode from type I to type II. Therefore, unlike packed
bed towers, TBC systems may operate in flooding
conditions (type II) [5].
While the hydrodynamic parameters of the TBCs
were investigated by many authors [2-16], to our
knowledge there are no available models in the
literature describing the heat transfer between the
liquid and the gaseous phases in these types of contactors. The main aim of this work was the experimental investigation of the heat transfer between the
cold water and the hot air in a countercurrent turbulent bed contactor. Based on the experimental findings, a model for the heat transfer coefficient between
the liquid and gas phase in TBC was proposed. The
hydrodynamic parameters of the system (the minimum fluidization gas velocity, pressure drop through
the bed, liquid hold-up, and bed expansion) were
calculated using the available literature models best
suited for our experimental system [4]. The countercurrent TBC contactor used in this work consisted of a
bed of spherical particles and operated in type I
regime.
520
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
EXPERIMENTAL SET-UP
The experiments were carried out in three-phase
system with fluidized bed, which is used for cooling of
the hot air, at different air and water flow rates. The
experimental setup is shown in Figure 1. The measured variables included the inlet and the outlet air
temperatures (Tgi and Tge) as well as inlet and outlet
water temperatures (TLi and TLe).
Figure 1. Experimental set-up of the three phase fluidized bed
contactor (a - fan, b - butterfly valve for air flow rate regulation,
c - throttle plates for air flow rate measurement, d - "U" manometer, e - electric air heater, f - column, g - steel mesh
5mm×5 mm, h - bed of plastic spheres, i - water spraying
nozzles, j - drops separator, k - water flow rate control valve,
L - rotameter; TIC - temperature indication and control,
TI - temperature indicator).
Experimental measurements were performed at
constant inlet air volumetric flowrate (Vg) of 275 m3/h
(at 20 °C) and constant inlet water temperature (TLi) of
16 °C. Particle Reynolds number (Rep) varies from
1795 to 1896 in the experiments because of the
change of air velocity (ug), viscosity (μ) and density
(ρg) with temperature. A total of 40 experimental
points were obtained for different water flowrates and
different inlet air temperatures. The parameters of the
system and the conditions at which the measurements were made are shown in Table 1.
Based on the water mass flux as well as on the
diameter and density of the spheres the operating
regime was determined according to the diagram proposed by Vunjak-Novakovic et al. [4]. It is clear that
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
Table 1. Basic parameters of the experimental system
Column diameter
Dc
0.25
m
Column cross-sectional area
Ac
0.04909
m
Diameter of light spheres
dp
0.02
m
Density of light spheres
ρp
290
kg/m
3
Density of water
ρl
1000
kg/m
3
Static bed height
H0
0.25
m
Water inlet temperature
TLi
16
ºC
Mbed
1.779
Mass of the particles in the bed
2
kg
-3
Mass of one particle (sphere)
M1
1.215·10
Number of particles
Np
1465
pieces
The total external surface of the particles
Ap
1.841
m
our experimental system is in the operational mode of
type I.
RESULTS AND DISCUSSION
Heat transfer coefficient
The purpose of the TBC used in this work was
cooling of the hot air, which was introduced at the
bottom of the column. Therefore, the objective was to
achieve the gas outlet temperature as low as possible, and to achieve the best possible heat transfer
between the cold water and the hot air. The experimental data of the outlet gas temperature as a function of liquid flow rate at constant air flow rate for
three inlet air temperatures are shown in Figure 2.
Figure 2 shows that with the increase in water flow
rate, the outlet air temperature decreases, i.e. the
cooling is improved, as expected.
The main objective of this study was the development of the correlation for heat transfer between
kg
2
the hot gas and the cooling water. If it is assumed that
the entire amount of water is evenly distributed on the
surface of the light solid spheres, the heat transfer
actually occurs between the hot gas and the liquid
film around the spheres. The overall heat transfer in
this system includes the convective, conductive and
the radiative heat transfer.
The radiative heat transfer coefficient is very
small in temperature ranges lower than 600 °C [17],
so it was neglected in this work, as the maximum temperatures in our system are in the range of 110 °C.
The conductive heat transfer between the hot air
and the liquid film formed around the solid spheres
was also neglected since the thickness of the liquid
film around the particles was calculated to be between
0.012 and 0.023 mm (Figure 3). The conduction can
be neglected through the hollow plastic sphere, since
the air and plastic are substances with small thermal
conductivity [18]. Only conduction can occur through
the liquid film. The Biot number is defined as the ratio
Figure 2. The outlet air temperature as a function of water flow rate at constant air flow rate of Vg (20 ºC) = 275 m3/h (Gv = 331 kg/h) for
three inlet air temperatures.
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Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
Figure 3. Liquid film thickness in function of water flowrate.
of the convective to the conductive heat transfer,
Bi = (hpL)/λwater, where the liquid film thickness (L = δ)
was taken as a characteristic dimension. As the
calculated values of the Bi numbers were much less
than 1 (Bi << 1), it was concluded that there is
negligible resistance to the heat transfer through the
liquid film.
The liquid film thickness that is formed around
the light spheres in the column was determined from
Eq. (1) assuming that the entire amount of liquid
present in the column is evenly distributed on the
surface of the particles [19]:
δ = 1000
d p (mm) 
2

h ( % ) ρp
 3 1+
− 1
100 ρl




(1)
The obtained liquid film thickness is presented
graphically as a function of the water flowrate for
three inlet air temperatures: 108.5, 96 and 85 °C (Figure 3). It can be seen that as the water flowrate
increases, the thickness of the film also increases. On
the other hand, the inlet air temperatures do not have
a significant impact on the film thickness.
According to the above, it was assumed that the
overall heat transfer coefficient K is approximately
equal to the convective heat transfer coefficient and
that all other mechanisms of heat transfer (conduction, radiation) are neglected. Additionally, since the
liquid film is very thin, it is appropriate to use the particle diameter for all of the further calculations.
The heat transfer between the hot gas and the
liquid film around the particles can be described
according to the following equation:
Q = KAp Δt lm
522
(2)
where K ≈ hp, and:
Δt lm =
(Tgi −TLe ) − (Tge −TLi )
T −T
ln gi Le
Tge −TLi
(3)
The overall heat balance is shown by the
following equation:
G vC pG (Tgi −Tge ) = GLC pL (TLe −TLi )
(4)
where Gv and GL represent mass flow rates of air and
water, CpL and CpG specific heat of air and water, Tgi
and Tge inlet and outlet air temperature, TLi and TLe
inlet and outlet water temperatures.
The amount of exchanged heat per unit time, Q,
can also be determined from the total heat balance
based on gas or on water. In this work, the balance is
calculated on the basis of the gas phase, since the
gas flowrate was kept constant:
Q = G vC pG (Tgi −T ge )
(5)
In the above heat balances (Eqs. (4) and (5))
heat losses were neglected.
According to Eqs. (2), (3) and (5), hp was calculated for each experimental run.
The obtained results are shown in Figure 4 as a
function of Rep. It can be seen that with increasing
Rep the heat transfer coefficient slightly decreases
(except for the five points that do not follow the trend
of other).
Since, to our knowledge, there are no literature
correlations describing the heat transfer in turbulent
bed contactors, the results obtained were compared
to the correlations for heat transfer between the single
sphere and the fluid flowing around it [20] as well as
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
Figure 4. Dependence of heat transfer coefficient of Rep.
with the correlations for overall heat transfer in
packed and fluidized beds [21]. In order to be able to
compare the results with the mentioned correlations,
Nup number was calculated according to the equation:
Nu p =
hpd p
λ
(6)
Ranz and Marshall [19] correlation for heat
transfer from the flowing gas to the single sphere in
the form of Nusselt number is:
Nu p = 2 + 0.6Rep1/2Pr 1/3
(7)
Kunii and Levenspiel [20] developed correlations for heat transfer in packed beds (Eq. (8)) and in
fluidized beds (Eq. (9)) in the same form with different
coefficients:
Nu p = 2 + 1.8Pr 1/3Rep1/2
Nu p = 2 + 1.5Pr 1/3 (1 − ε )Rep 
(8)
1/2
(9)
The results of the comparison of our experimental data with the mentioned correlations are shown in
Figure 5. As can be seen from the Figure 5, our experimental values of Nup lie mainly between the Nup
numbers for the packed and fluidized bed systems,
closer to the values of the fluidized bed. The mean
percentage error of Nup in comparison with presented
correlations is: for single spheres 49.2%, for packed
bed 44.4%, and for fluidized bed 19.6%.
The smallest error obtained for the Nup number
calculated according to the correlation for the fluidized
bed was expected. However, an error of almost 20%
Figure 5. Comparison of the experimental values of Nup with literature correlations for single sphere heat transfer, packed and fluidized
bed heat transfer.
523
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
is significant and that is why a new correlation based
on our experimental data was proposed.
In this work, a correlation for heat transfer coefficient calculation was developed in the form of jHp:
j Hp =
Nu p
RepPr 1/3
(10)
The correlation is a function of gas and liquid
flow rate and input and output gas temperatures (Eq.
(11)):
L

G 
0.1129
j Hp 
Tgi −Tge 
= 0.0787 

 Tgi 
1.7815
(11)
Comparison of experimental values of the jHp
and the jHp values obtained by Eq. (11) is presented in
Figure 6. The mean percentage error between the
experimental and the calculated values was 1.69%,
which represents a very good agreement.
Hydrodynamic parameters of the system
There are a variety of correlations in the literature for the calculation of basic hydrodynamic characteristics of three-phase fluidized bed contactors:
liquid hold-up, pressure drop, minimum fluidization
velocity and bed expansion [4-16]. However, the
problem is that most of these correlations were
derived for the specific test system and the range of
the experimental data obtained in it. For the cal-
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
culation of the hydrodynamic characteristics of our
experimental system, Vunjak-Novakovic et al. [4,6]
correlations were chosen, since they were obtained in
the systems that are the most similar to our system.
The parameters of the system on which the experiments were carried out are given in Table 2. Table 3
shows the corresponding correlations of VunjakNovakovic et al. [4,6].
The hydrodynamic characteristics of threephase fluidized bed contactors: liquid hold-up,
pressure drop, minimum fluidization velocity and bed
expansion were calculated by Vunjak-Novakovic et al.
[4,6] correlations given in Table 3. The calculated
values of hydrodynamic parameters in our TBC
system are given in Table 4.
CONCLUSIONS
The experimentally investigated three-phase
system consisted of a fluidized bed of light hollow
spheres, with countercurrent flow of hot air and cooling water. The main objective of the study was the
development of a correlation for heat transfer coefficient calculation. It was assumed that the total
amount of liquid hold-up was evenly distributed on the
surface of the solid spheres and that the heat transfer
actually occurred between the hot gas and the liquid
film around the spheres. The overall heat transfer in
this system was compared to existing literature correlations for heat transfer between a single sphere and
Figure 6. Comparison between the experimental values of jHp and the values of jHp calculated from correlation (Eq. (11)).
Table 2. System parameters in Vunjak-Novakovic et al. [4,6] and in our work
Reference
[4,6]
This work
524
f
H0 / cm
0.36-0.78
10-30
0.7
25
ul / m s–1
ug / m s–1
Dc / cm
dp / mm
ρp / kg m–3
0-0.034
0-4
14-29
10-38
182-980
1.73-1.84
0.001-0.002
25
20
290
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)
Table 3. Used correlations for calculation of the basic hydrodynamic characteristics [4,6]
 H0 

 Dc 
ε l,st = 6.49Frl 0.858 Rel−0.139 
{
(
−0.567
)
u mF = kd p1.2 (1 − ε 0 ) ρp − ρg + 2.48 × 10−3 ρld p−0.568L0.71910−4.788×10
Δp =
{(1− ε 0 ) ρp + hL 0 ρl} gH 0
(12)
, Type I operation [4]
−2
L
}
0.5
 g
,k = 
 m ρg

0.5




, m = 0.064 [6]
(13)
[6]
(14)
−0.567


 1 − ε + 0.00248  H 0 
d p−0.568L0.719 + 0.02 
0
D 


 c 
H
 , Type I operation [6]
=
H0
1 − 0.62u g0.237
(
(15)
)
Table 4. Calculated values of hydrodynamic parameters
εl,st / m3 m–3
Δp / Pa
umF, avg / m s–1
(H/H0, avg) / m m
0.023–0.013
413.1-386.2
1.43
1.96
the fluid flowing around it, as well as with the correlations for overall heat transfer in packed and fluidized
beds. The smallest error for the case of correlation for
fluidized beds was obtained.
As the existing literature correlations for heat
transfer did not have sufficient accuracy, a new correlation was proposed specifically for the three-phase
countercurrent contactor, given in Eq. (11).
The basic hydrodynamic characteristics of the
experimental system were also calculated according
to the available literature correlations. The most
appropriate correlations proposed by Vunjak-Novakovic et al. were chosen according to the parameters
of the system.
Acknowledgement
Financial support of the Serbian Ministry of
Education, Science and Technological Development
(Project ON172022) is gratefully acknowledged.
Nomenclature
Ac – cross-sectional area of the column (m2)
Ap – total particle outer surface area (m2)
Bi – Biot number
CpG – heat capacity of air (J/kg K)
CpL – heat capacity of water (J/kg K)
Dc – column diameter (m)
dp – light particle diameter (m)
f – fractional free area of support grid
Frl –Froud number for liquid phase, ul/(gdp)1/2
g – gravitational acceleration, 9.81 m2/s
GL – water mass flowrate (kg/s)
Gv – air mass flowrate (kg/s)
H – height of expanded bed (m)
H0 – static bed height (m)
–1
h – liquid hold-up (%)
hLo – operational liquid hold-up (m3/m3)
hp – convective heat transfer coefficient (W/(m2K))
jHp – heat transfer factor
K – overall heat transfer coefficient (W/(m2K) )
L – water mass flux (kg/(m2 s))
M1 – weight of single sphere (kg)
Mbed – bed weight (kg)
Np – number of particles
Nup – Nuselt number for particle
Pr – Prantl number
Q – exchanged heat per unit time (W)
Rel – Reynolds number for water, (Dculρl)/μl
Rep – Reynolds number for particle, (dpugρg)/μg
Tge – outlet air temperature (°C)
Tgi – inlet air temperature (°C)
TLe – outlet water temperature (°C)
TLi – inlet water temperature (°C)
Vg (20°C) – volumetric air flowrate at 20 °C (m3/h)
ug – superficial air velocity (m/s)
ul – superficial water velocity (m/s)
umf – minimum fluidization air velocity (m/s)
Δp – pressure drop in the column (Pa)
Δtlm – logaritmic temperature diffference
Greek symbols
λ – air thermal conductivity (W/(m K))
λwater – water thermal conductivity (W/(m K))
ε0 – bed porosity
εl,st – liguid hold-up in stationary regime (m3/m3)
μ - air dynamic viscosity (Pa s)
ρg – air density (kg/m3)
ρl – water density (kg/m3)
ρp – density of light plastic spheres (kg/m3)
δ – liquid film thickness (mm)
525
Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER…
Abbreviations
TBC – Turbulent Bed Contactor
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702-706
ZORANA ARSENIJEVIĆ1
TATJANA KALUĐEROVIĆ
2
RADOIČIĆ
1
MIHAL ĐURIŠ
ŽELJKO GRBAVČIĆ 2
1
Institut za hemiju, tehnologiju i
metalurgiju – Centar za katalizu i
hemijsko inženjerstvo, Univerzitet u
Beogradu, Beograd, Srbija
2
Tehnološko–metalurški fakultet,
Univerzitet u Beogradu, Beograd,
Srbija
NAUČNI RAD
nd
ed.,
EKSPERIMENTALNA ISPITIVANJA PRENOSA
TOPLOTE U KOLONI ZA HLAĐENJE SA
TROFAZNO FLUIDIZOVANIM SLOJEM
U okviru ovog rada je proučavan prenos toplote u trofaznom (gas–tečnost–čvrsto) fluidizovanom sloju. Eksperimentalna ispitivanja obavljena su u koloni prečnika 0.25 m sa fluidizovanim slojem sferičnih čestica male gustine (290 kg/m3) prečnika 2 cm u suprotnostrujnom toku vode i vazduha. Izvršeno je eksperimentalno ispitivanje i matematičko
modelovanje prenosa toplote između zagrejanog vazduha i vode za hlađenje. Eksperimenti su izvršeni pri različitim protocima vode za hlađenje i različitim temperaturama
zagrejanog vazduha, dok je protok vazduha održavan konstantnim. Na osnovu dobijenih
eksperimentalnih rezultata predložena je nova korelacija za prenos toplote u trofaznom
fluidizovanom sloju. Srednja procentualna greška između eksperimentalnih i korelisanih
vrednosti faktora prenosa toplote, jHp, je iznosila 1,69%. Hidrodinamički parametri ispitivanog sistema su izračunati na osnovu raspoloživih literaturnih korelacija.
Ključne reči: turbulentni trofazni kontaktor, fluidizacija, koeficijent prenosa toplote, hidrodinamika.
526
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
VESNA S. CVETKOVIĆ1
LUKA J. BJELICA2
NATAŠA M. VUKIĆEVIĆ1
JOVAN N. JOVIĆEVIĆ1
1
Institute of Chemistry, Technology
and Metallurgy, University of
Belgrade, Belgrade, Serbia
2
Faculty of Sciences and
Mathematics, University of Novi
Sad, Novi Sad, Serbia
SCIENTIFIC PAPER
UDC 544.6:669.729:543.42
DOI 10.2298/CICEQ141205009C
CI&CEQ
ALLOY FORMATION BY Mg UNDERPOTENTIAL DEPOSITION ON Al FROM
NITRATE MELTS
Article Highlights
• Water removal from magnesium nitrate hexahydrate
• Preparation of magnesium nitrate melts
• Underpotential deposition of magnesium on aluminium substrate
• Mg-Al surface alloy formation by UPD of magnesium
Abstract
Magnesium was underpotentially deposited on aluminium electrodes from
magnesium nitrate-ammonium nitrate melts at temperatures ranging from 390
to 500 K. The electrochemical techniques used were linear sweep voltammetry
and potential step. Electrodes were studied by scanning electron microscopy
(SEM), energy dispersive spectrometry (EDS), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD). It was found that reduction processes of nitrate, nitrite and water (when present), in the underpotential range
studied, took part simultaneously with magnesium underpotential deposition.
Consequently, magnesium UPD reduction and stripping voltammetry peaks
were not pronounced and well defined. Nevertheless, EDS, EDX and XRD
measurements showed evidence of Mg2Al3, MgAl2 and Al12Mg17 alloys formed
by underpotential deposition of magnesium onto aluminium substrate.
Keywords: magnesium/aluminium alloys, underpotential deposition,
magnesium nitrate melts.
One of the ways to obtain a metal, and/or an
alloy, under very controlled conditions is direct isothermal electrochemical deposition (electrodeposition). The current density that sustains electrochemical deposition of a metal, or an alloy, directly reflects the rate of the process [1].
However, metals like Li, Na, K, Al, Mg, Ti and W
cannot be electrodeposited from water solutions,
because hydrogen starts evolving on the working
cathode before any of them start depositing. This prevents even the smallest amounts of the metal from
remaining as a deposit on an electrode in a water
solution without being dissolved. For electrodeposition of Al, Mg and other metals, with very negative
standard electrode potentials, melts based on chlo-
Correspondence: V.S. Cvetković, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Njegoševa
12,11000 Belgrade.
E-mail: v.cvetkovic@ihtm.bg.ac.rs
Paper received: 5 December, 2014
Paper revised: 26 February, 2015
Paper accepted: 20 March, 2015
ride salts at temperatures above 900 K are used.
These are mainly inorganic or organic, chlorides or
fluorides, salts that are combined with a cation of
some alkaline/alkaline earth metal, or some organic
cation or anion [1-3]. Ionic liquids (made of organic
salts) became known relatively recently and proved to
be suitable media for electrodeposition of metals and
alloys at relatively low temperatures (from 273 to 373
K) [1,4].
To electrodeposit bulk of any metal, it is necessary to provide a working electrode with a potential
that is more negative than the standard electrode
potential of the depositing metal, this process is referred to as overpotential deposition (OPD). It was
also found that it is possible to co-deposit two or even
three metals using overpotential deposition conditions
and thus produce alloys on the surface of the working
electrode.
Further detailed investigations of the processes
that regulate electrodeposition of metals and alloys
lead to the recognition of electrodeposition of metals
on foreign substrates at potentials more positive than
527
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
the equilibrium potential of the depositing metal (also
referred to as underpotential deposition – UPD) [5]. In
the last 40 years, UPD has been a subject of intensive experimental and theoretical interest. Most of the
initial experimental work was done in aqueous electrolytes until the 1980s when the same phenomena
was observed in deposition experiments of aluminium
on gold, silver and copper from chloride melts at
temperatures below 573 K [6-8].
It was soon found that a metal electrodeposited
under UPD conditions from aqueous, non-aqueous
solutions and melts at room temperatures onto a
cathode of a different metal can diffuse into the substrate and generate alloys. Alloys obtained by electrochemical deposition (OPD and UPD) can have different chemical and phase structures than the alloys
of the same composition obtained by metallurgical
(thermal) methods [1,9].
Over the past ten years, the automotive industry
has shown renewed interest in the applications of
magnesium and its alloys, because magnesium with a
density of 1.74 g/cm3 is 4.5 times lighter than steel
and 1.6 times lighter than aluminium [10,11], while
being able to achieve similar levels of ultimate strength
in some alloys (200-250 MPa). As a result, magnesium alloys offer a very high specific strength among
conventional engineering alloys and have a wide
application prospect in aerospace transportation,
electronic engineering, as well as electrode components as chemical sources of electrical energy [12,13].
Currently, the most widely used magnesium alloys
are based on the Mg-Al system [12]. Electrodeposition of magnesium and its alloys is of increasing
importance in the development of rechargeable magnesium battery systems [14].
It is known that Mg cannot be deposited from
solutions of simple Mg salts such as Mg(ClO4)4 in
conventional organic solvents, for example, acetonitrile, propylene carbonate or dimethylformamide. Most
likely, this is due to the working electrode surface
becoming covered by passivating surface films of
very low ionic conductivity [14].
Available literature that references electrodeposition of magnesium from nitrate melts, and magnesium underpotential deposition is rather limited, while
that of alloy formation from nitrate melts is practically
nonexistent. Physicochemical characteristics of nitrate melts of alkaline and alkaline earth metals became
a subject of interest in the second half of twentieth
century [15-17] including their possible usage as electrolytes [18-20]. However, among a number of nitrate
melts investigated electrochemically, neither mag-
528
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
nesium nitrate nor magnesium nitrate-ammonium nitrate mixture melts were studied.
There are multiple reasons why these melts are
not conducive to this work. Very pronounced oxidative
characteristics of nitrates, great number of oxidation/
/reduction processes that can take place with cations
and anions present in nitrates at the potentials more
negative and more positive than the reversible potential of magnesium [19,20], prevent realization of more
experiments regarding metal electrodeposition from
nitrate melts. Difficulties related to sustaining of the
intended melt temperature variation below ±3 K arise
from the large latent heats of the numerous nitrates,
phase transformations in the temperature range from
373 to 500 K [15]. Also, it is impossible to remove
water from magnesium nitrate hexahydrate by heating, because it decomposes before it loses water and
transforms into magnesium(II) oxide. The backbone
of this octahedral complex is the magnesium cation
[Mg(H2O)6]2+, which is very stable and cannot lose
water thermally. As such, presence of water in magnesium melts cancels the advantages the melts have
as compared to the magnesium aqueous solutions.
The aim of this work was to overcome the limitations of working on electrodeposition from nitrate
melts, establish whether underpotential deposition of
magnesium onto aluminium surface from magnesium
nitrate melts occurred, and if it lead to magnesium/
aluminium alloy formation.
EXPERIMENTAL
Experiments were done under 99.99% Ar atmosphere in a three-neck (joints) electrochemical cell
made of Pyrex glass placed in a heating mantle with
temperature controlled (electronic thermostat) between
363 and 463 (±2 K). The central neck was closed with
a PTFE plug carrying the working electrode (a
99.999% Al plate with active surface area of 0.4 cm2),
the left neck with a PTFE plug holding an argon glass
inlet-outlet and glass Luggin capillary with magnesium reference electrode (3 mm diameter 99.999%
Mg wire), and the right neck with a Teflon plug holding a magnesium anode (99.999% Mg) in the shape
of a curved rectangular shovel (7.5 cm2 active surface
area) and a tube of thin glass with a thermocouple.
Argon and other possible gases coming out of the cell
were captured/washed in two bottles (first with a
slightly basic solution and second with a slightly acid
solution). The entire cell setup was placed into a
transparent plastic “glove box” in order to create a
moisture free atmosphere around the cell.
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
The melts used in experiments were: non-aqueous Mg(NO3)2, Mg(NO3)2⋅XH2O, eutectic mixture non-aqueous Mg(NO3)2: NH4NO3 and eutectic mixture
Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O.
The procedure for water removal from magnesium nitrate hexahydrate consisted of two steps. The
first step: the mixture of 5 g of magnesium nitrate
hexahydrate and 15 cm3 of trimethyl orthoformate
was brought to boiling and kept for 90 min under
reflux at 343 K. In the first 20 min Mg(NO3)2⋅6H2O was
completely dissolved in trimethyl orthoformate and
after 45 min snow white crystals started appearing at
the walls of the glass vessel. The second step: after
90 minutes of previous treatment, the mixture, now
consisting of an ethyl ester of formic acid, methanol
and crystals of non-aqueous magnesium nitrate, was
subjected to vacuum distillation at 343 K. Upon removal of the visible liquid, the remaining crystals were
vacuum dried for additional 60 min. Non-aqueous
magnesium nitrate was kept in a closed glass container in a desiccator furnished with plenty of silicagel.
Ammonium nitrate hexahydrate was dried for 10 h at
378 K. Required amounts of magnesium nitrate
alone, or mixtures with ammonium nitrate, were
placed into the cell supplied with electrodes. Closed
cell was then placed into the heating mantel, argon
supply was turned on and the system was heated
gradually to the wanted temperature.
The aluminium cathodes (99.999% Al) were
mechanically polished by emery paper (FEPA
P-4000) to a mirror finish and then etched in (50% HF
+ 15% H2O2) water solution for 30-60 s with intensive
steering before being left in (NH4NO3 + 5% H2O2) solution for 30-60 s. Finally, the electrodes were washed
in deionised water, absolute ethyl alcohol, dried and
mounted into the cell.
The magnesium anode and reference electrode
(99.999% Mg) were mechanically polished by emery
paper (FEPA P-4000) to a mirror finish and then
etched in the solution, made of 78.2 cm3 conc. HNO3
+ 23.4 cm3 conc. H2SO4 + 898.4 cm3 deionised water,
in several 10 s intervals alternating with washing with
deionised water. Finally, the electrodes were washed
in deionised water, absolute ethyl alcohol, dried and
mounted into the cell.
The electrochemical techniques used were:
linear sweep voltammetry (LSV) and potential step.
The potentials of working electrodes were measured
in relation to the equilibrium potential of magnesium
reference electrode in the melt used under the given
conditions.
The cyclic voltammetry experiments included
one or more cycles of the working electrode potential
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
cycling from a starting potential, ES (usually 50 to 100
mV more negative than the reversible potential of the
Al working electrode) to a final potential, EF (which
was positive to the reversible potential of Mg) and
then back again to ES all at scan rates (between 5
and 100 mVs-1). The obtained results were recorded
on an X-Y recorder.
The potential step method included change of
the working electrode potential from an initial potential, EI (50 to 100 mV more negative to aluminium
equilibrium potential in the given melt) to a potential,
EX (50 to 100 mV more positive to magnesium equilibrium potential in the given melt). EX potential was
held constant for some time, whereupon the cathode
was retrieved from the cell under potential in order to
preserve deposited material or possible alloys formed
during UPD of magnesium. The electrodes were successively washed with deionised water and absolute
ethyl alcohol until visible remains of melt were removed. The surfaces of the electrodes were analyzed
by scanning electron microscopy (SEM - JEOL, model
JSM-5800, Japan), energy dispersive spectrometry
(EDS - Oxford INCA 3.2, U.K.), energy dispersive
X-ray spectroscopy (EDX-maping - Oxford IncaEnergy
EDX) and X- ray diffraction (XRD - Enraf Nonius powder diffractometer, Germany). IR analysis of the
“anhydrous” magnesium nitrate was performed using
Thermoscientific Nicolet 6700 (FT-IR) Smart Orbit
Diamond (4000-200 cm-1).
RESULTS AND DISCUSSION
It was important to make sure that the method of
water removal from magnesium nitrate described
above is effective. The mass difference between the
magnesium nitrate hexahydrate entering the process
of water removal and the magnesium nitrate leaving
the said process was 39±3%. This would suggest that
at least 92% of water had been removed. The difference to 100% can be attributed to the residual
methanol, methyl ester of formic acid or some of their
derivatives because obtained Mg(NO3)2 crystals
appeared to give off these chemicals immediately
after drying. Obtained results strongly suggest that
the process of water removing from magnesium nitrate hexahydrate was successful. This conclusion is
supported by the results obtained with IR and XRD
analysis (Figures 1 and 2). The results of “anhydrous”
magnesium nitrate IR analysis (Figure 1) show
[21,22]: a) OH group at 3235 cm-1; b) CH groups at
2960 and 2850 cm-1; c) NO3 at 1344, 1128 and 1012
cm-1, possibly MgO group at 644 and 407 cm-1 and
support the above conclusions.
529
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
Figure 1. IR spectrogram of Mg(NO3)2 crystals obtained after water removing process.
Figure 2. XRD spectra of: a) non-aqueous eutectic mixture
Mg(NO3)2 + NH4NO3, (*) Mg(NO3)2, (+) NH4NO3; b) eutectic
mixture Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O; (*) Mg(NO3)2⋅6H2O,
(+) NH4NO3⋅XH2O [24,25].
In Figure 2a, XRD measurements do not show
characteristic lines which would belong to the crystal
structure of Mg(NO3)2⋅6H2O shown in Figure 2b. They
show the lines, which with some reservations could
be attributed to the crystals of “anhydrous” magnesium nitrate. The reservations are due to the fact
530
that the data on “anhydrous” magnesium nitrate in the
available literature are very few and not fully reliable.
Contrary to work solutions where hydrogen ions
are present and where hydrogen reference electrode
can be universal, there is no universal reference
electrode in experiments with melts. Therefore, in the
systems where underpotential deposition is examined
it is common practice to use the reversible potential of
the depositing metal as a reference electrode
potential with ascribed value of 0.000 V. In the nitrate
melts used, for magnesium underpotential deposition
on aluminium, a magnesium electrode was used as
the reference electrode. Polarization measurements
and cyclic voltammetry performed on the magnesium
working electrode with magnesium reference and
counter electrodes have shown that magnesium reversible potential in the used magnesium nitrate melts,
under temperatures ranging from 340 to 500 K, was
stable [23]. Reversible potential of polycrystalline aluminium in anhydrous Mg(NO3)2 melt at temperature
interval between 360 and 400 K was 630±10 mV vs.
Mg/Mg(II); in non-aqueous eutectic mixture Mg(NO3)2
+ NH4NO3 at temperature between 390 and 500 K
was 970±20 mV vs. Mg/Mg(II); in Mg(NO3)2⋅6H2O
melt between 440 and 500 K was 260±30 mV vs.
Mg/Mg(II) and in eutectic mixture Mg(NO3)2⋅6H2O +
NH4NO3⋅xXH2O at temperature interval between 380
and 450 K was 1000±30 mV vs. Mg/Mg(II). With all
other conditions being kept constant, the higher the
temperature, the more positive aluminium reversible
potential is. Addition of ammonium nitrate to magnesium nitrate moved the aluminium reversible potential
to more positive values as well.
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
General characteristics of the voltammograms
obtained in all melts used is that more than one reduction peak was observed in the magnesium underpotential area, but with no oxidation counterparts.
Typical example of the voltammograms obtained is
presented in Figure 3. It can be seen that stripping
peaks were not observed even when the cathodic end
potential was pushed into the overpotential range.
Sometimes reduction peaks were spread over a wider
range of applied potentials without showing a steeper
increase or decrease of current density values. Such
structures of voltammogram peaks are characteristic
for processes that start at close successive potentials
and proceed simultaneously (often next process
starts and increases rate while previous process dyes
out with falling rate). Therefore, the obtained peaks
represent a sum of all the rates of all the processes
taking part at the certain potential.
Suggestions of possible processes that could
produce reduction peaks in the magnesium UPD
region investigated, apart from ones brought about by
the magnesium underpotential deposition itself, can
be found in rare published works [19,20]. The potentials of the proposed reactions measured relative to
Na, K or Li cannot be directly used, but it can be
assumed with enough certainty that the order of the
potentials and their differences between these processes is preserved with respect to the magnesium
reference potential. However, absolute values must
be changed by the amounts that reflect differences in
reference potentials between Na, K and Li in their
nitrate melts and magnesium in used nitrate melts.
Reduction processes in the nitrate melts with
water present, at the most anodic potentials, start
with:
2NO3− + 6H2O + 10e −  N2 + 12OH−
(1)
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
NO3− + H2O + 2e −  NO2− + 2OH−
(2)
followed by the group of reactions with very close
nitrate reduction potentials, in the melts with and
without water present, which is reflected in wider
cathodic voltammogram peaks:
NO3− + 5e −  1/ 2N2 + 3O2 −
(3)
NO3− + 2e − ↔ NO2− + O2 −
(4)
2NO3− + 2e − ↔ 2NO2− + O22 −
(5)
2NO3− + 8e − ↔ N2O + 5O2 −
(6)
NO3− + 3e −  NO + 2O2 −
(7)
which at their end decrease close to zero cathodic
current densities. At potentials of –350 to –600 mV
more negative to the previous peak, but still in the
magnesium UPD region, next group of the nitrate
reduction processes starts at mutually very close potentials:
2NO3− + 2e −  2NO2− + O22 −
(8)
NO3− + e −  NO2 + O2 −
(9)
The absence of anodic (oxidation) counterparts
to the cathodic peaks was a subject of a number of
works [9,19,20,26-28]. These studies emphasize that
changes of the aluminium electrode potential in nitrate melts from anodic to cathodic values compared
to magnesium reversible potential provoke passivation of the working electrode which becomes partially (or fully) covered with magnesium oxides layers.
These layers do not dissolve when the potential is
returned to the starting positive value.
In the UP region of the magnesium on aluminium cycle in nitrate melts used, the change of the
electrode potential from positive values up to the
Figure 3. Linear sweep voltammograms of magnesium deposition onto aluminium electrode, υ = 30 mV s−1 from non-aqueous eutectic
mixture Mg(NO3)2 + NH4NO3 at T = 430 K, Ei = 0.700 V  Ef = –0.550 V vs. Mg/Mg(II).
531
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
magnesium reversible potential induces a number of
reactions based on nitrogen, very reactive oxygen
anion O2-, OH- and sometimes water. All produced
gases were removed from the electrochemical cell by
the argon stream, so when the electrode potential is
reversed into positive direction, their possible theoretical reverse oxidation reaction back to initial NO3or H2O could not be expected. As a result, no anodic
voltammogram peaks could be recorded. Furthermore, O2- produced in inner and outer parts of the
electrochemical double layer very quickly engaged in
reaction with present Mg2+ [9,19,20,26-28]:
Mg2 + + O2 − → MgO
(10)
the result being formation of insoluble magnesium
oxides in the magnesium UPD region. The thermal
decomposition constant [19,20] defines the stability of
the possibly present magnesium hydroxide:
Mg(OH)2  MgO + H2O
(11)
However, examined anodic voltammogram
peaks cannot be expected in the UP region.
In the melt made of eutectic mixture of magnesium nitrate and ammonium nitrate, at the temperatures used, ammonium ion, resulting from NH4NO3
dissociation
[19,20],
form
the
compound
(NH4)3Mg(NO3)5. In the melt this compound exists as a
quasicrystalline structure made of NH4+, Mg2+ and
NO3‒ [19,20]. The fact that reduction current densities
in the magnesium nitrate melts increase with the increase of the ammonium nitrate present, at the constant temperature in the magnesium UP region investigated, leads to the conclusion that NH4+ reduction is
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
taking place:
2NH+4 + 2e − → 2NH3 + H2
(12)
However, this reaction is, under given conditions, irreversible and voltammograms could not show
oxidation peaks when the electrode potential was reversed in the positive direction.
It is logical to assume that the reduction peaks
obtained by LSV measurements on the aluminium
working electrode from magnesium nitrate and magnesium nitrate + ammonium nitrate melts in the magnesium underpotential region are sums of partial current densities for: Mg2+ underpotential reduction, nitrate anion reduction and ammonium cation reduction.
Being a sum, the recorded current densities suggest
small magnesium underpotential deposition partial
current densities. Such small current densities exhibited by the UPD voltammograms from similar melts
[9,23,29,30] were characteristic of deposited metal
monolayer diffusion into the substrate and forming
alloys.
According to the Hume/Rothery rules [31], Mg
and Al fulfil the required conditions to form alloys
(solid solutions), including “the 15% rule”, because
Mg and Al atomic radii differ only by 16.6%. EDS and
XRD measurements obtained from the aluminium
electrodes in used magnesium nitrate melts exposed
to constant potentials in the magnesium underpotential region (50 to 150 mV vs. Mg/Mg(II)) supported
the assumption.
An example of the indication that magnesium
does underpotentially deposit on aluminium is exhibited in Figure 4 and represents SEM, EDS and EDX
Figure 4. a) SEM photograph for the surface of the Al electrode after 120 min holding at the potential of Ex = 60 mV vs. Mg/Mg(II) in
non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at T = 450 K, mag. 2500x; b) EDS data for the sample in Figure 4a and EDX
mapping; c) magnesium distribution image; d) oxygen distribution image; and e) aluminium distribution image
of the Al electrode surface.
532
V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
results obtained from the aluminium electrode held for
two hours at magnesium underpotential of 60 mV vs.
Mg/Mg(II) in a non-aqueous eutectic mixture
Mg(NO3)2 + NH4NO3 at T = 450 K. A typical example
of XRD analysis results on the aluminium sample
exposed to underpotential of 60 mV vs. Mg/Mg(II) in
the same melt and at T = 460 K for: a)1, b) 2 and c) 5
h are shown in Figures 5a-c, and strongly suggest
that magnesium-aluminium alloys are being formed.
The results obtained by EDS, EDX (Table 1)
and XRD (Table 2) analysis of Al substrates after
being exposed to magnesium underpotential deposition to constant potential of 60 to 100 mV vs.
Mg/Mg(II) for 120 min, from all used melts at the
temperatures applied (under 500 K) seriously indicate
that magnesium-aluminium alloys have been formed.
Table 1. Results of EDS quasi-quantitative analysis for the Al
samples exposed to constant potential of 60 to 100 mV vs.
Mg/Mg(II) for 120 min in used melts
Melt
Mg(NO3)2⋅6H2O
Al (at.%) Mg (at.%) O (mass%)
-
-
33.79
Mg(NO3)2
59.99
6.22
Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O
94.63
5.37
-
Mg(NO3)2 + NH4NO3
19.19
11.45
69.37
According to the Mg-Al phase diagrams [36,37],
the equilibrium solid phases are: a) the fcc solid
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
solution with maximum solubility Mg in Al of at.18.9%
at eutectic temperature of 723 K; b) the hcp solid
solution with maximum solubility of Al in Mg of 11.8
at.% at eutectic temperature of 710 K; c) the β compound of approximate stoichiometry Al3Mg2, with
complex fcc structure at low temperature, β transforms martensitically to another structure that may be
a distortion of the β structure, but the equilibrium
phase relations have not been investigated); d) the
line compound R (or ε), of composition 42 at.% Mg; e)
compound γ which at 723 K has a maximum composition range of approximately 45-60 at.% Mg, but
the ideal crystal structure has the stoichiometry
Al12Mg17 at 58.6 at.% Mg. At the lower cooling rates,
β, γ and γ' can be formed, while at higher cooling
rates a new phase Φ was observed, found in a 30
at.% Mg alloy where a metastable solid solution and
metastable phase appeared. Based on the structure,
the new phase was identified as having stoichiometry
Al2Mg.
All of the alloys described by the literature
[36,37] have been recorded in magnesium underpotential deposition performed on aluminium in used
nitrate melts but at temperatures that are several
hundred K lower, Table 2. There is β compound
(Al3Mg2) with complex fcc structure which is known to
exist over a range of composition. This compound
starts as a supersaturated Al solid solutions and
Figure 5. Diffraction patterns of aluminium sample after: a) 1, b) 2 and c) 5 h of magnesium underpotential deposition at Ex = 60 mV vs.
Mg/Mg(II) in non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at T = 460 K; a) (∙) (hcp) – Al0.9Mg3.1[32]; (*) (bcc) – Al12Mg17 [33];
(+) (hcp) – Mg2Al3 [34]; b) (+) (hcp) – Mg2Al3 [34]; (*) (bcc) – Al12Mg17 [33]; c) (+) (hcp) – Mg2Al3 [34]; (*) (bcc) – Al12Mg17 [33];
(∙) – (rhombohedral) MgO4 [35].
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V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
undergoes a phase transformation through continued
decomposition by formation of a nonequilibrium
phase β' and solid solution with less Mg content than
equilibrium, and ends up in the formation of equilibrium β phase. The metastable solid solution with
relatively high Mg content (up to 30 at.%) with approximate stoichiometry Al2Mg was also recorded. The
apparent existence of Al12Mg17 (at 58.6 at.% Mg) is a
rather convincing argument in support of very successful interdiffusion of Mg and Al during magnesium
underpotential deposition onto aluminium performed
here at temperatures ranging from 390 to 500 K.
Table 2. Alloys identified by XRD analysis on Al substrates
exposed to constant potential of 60 to 100 mV vs. Mg/Mg(II)
(magnesium UPD) for 120 min in used melts
Melt
Alloy 1
Alloy 2
Mg(NO3)2⋅6H2O
bcc - Al12Mg17
Mg(NO3)2
bcc - Al12Mg17
fcc - Al3Mg2
fcc - Al2Mg
hcp - Mg2Al3
Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O
Mg(NO3)2 + NH4NO3
bcc - Al12Mg17 hcp - Mg2Al3
Which of the magnesium adatoms formed by
underpotential deposition on aluminium surface participate in oxide formation and which ones diffuse into
substrate and contribute to alloy formation could not
be concluded by linear sweep voltammetry, EDS or
XRD results. LSV results indicated, EDS and XRD
results confirmed, formation of both the magnesium
oxide and the magnesium-aluminium alloy at the surface of the aluminium electrode in nitrate melts used.
Eqs. (3)–(9) describe sources of oxygen needed for
the process shown in Eq. (10) in the absence of water
and Eq. (11) magnesium oxide formation in the presence of water in the melt. In addition, some novel
results [26-28] suggest that every amount of reactive
magnesium on the electrode surface in the presence
of O2- and OH- very quickly becomes MgO. Therefore,
the surface of the aluminium working electrode
becomes partially covered with MgOx even in the first
linear change of the potential from anodic end to
cathodic end of the magnesium underpotential range.
This, however, did not preclude enough of magnesium adatoms from participating in magnesium-aluminium alloys formation by interdiffusion. Part of the
magnesium ions in magnesium (II) oxide probably
diffuse through the oxide layer to the aluminium surface where they become discharged into magnesium
adatoms which are then participating in the interdiffusion processes. Fast and unavoidable formation of
insoluble MgO in the magnesium underpotential
deposition range on aluminium from used nitrate
melts explains quasi-passivation of the working elec-
534
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
trode and the lack of anodic current peaks on the voltammograms recorded.
CONCLUSIONS
The value for the half of work function difference
in the case of Al and Mg is 0.20 to 0.30 eV and
magnesium should show an underpotential deposition
on aluminium at potentials close to 0.100 V vs.
Mg/Mg(II). This work has confirmed UPD of Mg on Al
substrate from nitrate melts used at potentials very
close to 100 mV vs. Mg/Mg(II).
However, this rule does not predict whether
there are going to be alloys formed between the substrate and underpotentially deposited metal. And yet,
the most pronounced effects of the established magnesium underpotential deposition from magnesium
nitrate melts used were three alloys formed with aluminium substrate: Al12Mg17, Mg2Al3 and metastable
solid solution Al2Mg. All the alloys obtained were
formed at the temperatures several hundred Kelvin
degrees lower than the temperatures which are,
according to the relevant existing binary phase diagrams, needed for their formation thermally.
It was established that underpotential deposition
of the metals unsuitable for electrodeposition from
aqueous electrolytes, like magnesium, can be performed even from low temperature nitrate melts and
that it can lead to the formation of alloys in a very
controlled way under more technologically suitable
conditions than most of the known ones.
Acknowledgement
This work was supported by the Ministry of
Education, Science and Technological Development
of the Republic of Serbia (Grant ON 172060).
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V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL…
VESNA S. CVETKOVIĆ1
LUKA J. BJELICA2
NATAŠA M. VUKIĆEVIĆ1
JOVAN N. JOVIĆEVIĆ1
1
Institut za hemiju, tehnologiju i
metalurgiju, Centar za elektrohemiju,
Univerzitet u Beogradu, Beograd,
Srbija
2
Prirodno-matematički fakultet,
Univerzitet u Novom Sadu, Novi Sad,
Srbija
NAUČNI RAD
Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)
FORMIRANJE LEGURA ELEKTROTALOŽENJEM
Mg PRI POTPOTENCIJALIMA NA Al IZ RASTOPA
NITRATA
Ispitivano je elektrotaloženje magnezijuma pri potpotencijalima (underpotential deposition UPD) na elektrodi od aluminijuma iz rastopa smeše magnezijum nitrata i amonijum nitrata
na temperaturama od 390 do 500 K. Elektrohemijske tehnike koje su korišćene bile su
ciklička voltametrija i metoda potenciostatskog pulsa. Nakon elektrotaloženja magnezijuma
pri potpotencijalima aluminijumske elektrode ispitivane su skenirajućom elektronskom
mikroskopijom (SEM), energetsko disperzivnom spektroskopijom (EDS), energetsko
disperzivnom spektroskopijom X-zraka (EDX) i metodom difrakcije X-zraka. Utvrđeno je da
reakcije redukcije nitratnih i nitritnih jona i vode (kada je prisutna), koje se odigravaju u
istom i širem području potpotencijala magnezijuma učestvuju istovremeno sa reakcijama
elektrolitičkog taloženja magnezijuma u datom rastopu i deformišu i/ili prekrivaju redukcione struje elektrotaloženja magnezijuma. EDS, EDX i XRD merenja su pokazala da
dolazi do formiranja Mg2Al3, MgAl2 and Al12Mg17 legura kao posledice elektrotaloženja
magnezijuma pri potpotencijalima na elektrodama od Al u ispitivanim rastopima.
Ključne reči: magnezijum/aluminijum legure, elektrotaloženje pri potpotencijalima, rastopi magnezijum-nitrata.
536
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
RAJAMOHAN NATARAJAN1
JAMILA AL-SINANI1
SARAVANAN
VISWANATHAN2
1
Faculty of engineering, Sohar
University, Sohar, Oman
2
Department of Chemical
Engineering, Annamalai University,
India
SCIENTIFIC PAPER
UDC 547.532:66:544
DOI 10.2298/CICEQ141022010N
CI&CEQ
PERFORMANCE EVALUATION AND KINETIC
STUDIES ON REMOVAL OF BENZENE IN
UP-FLOW TREE BARK BASED BIOFILTER
Article Highlights
• The removal of benzene at different in loading rates were studied in a biofilter employing
a novel biofilter media
• The performance was evaluated in terms of removal efficiency and elimination capacity
• The effect of flow rates of influent pollutant and biofilter bed height was studied
• Carbon dioxide gas production profile was recorded and related with elimination capacity
• Kinetic modeling was performed and the constants were estimated
Abstract
This study aims to evaluate the feasibility of Phoenix dactylifera tree barks as
the novel filter medium in an upflow biofilter employing mixed culture to degrade benzene. The experiments were conducted at different benzene concentrations (1.5-6.0 g m-3) and EBRT (1.2-4.7 min). The elimination capacity was
found to vary linearly with inlet loading rate in the range of 0–306 g m–3 h–1.
Removal efficiency of 99% was achieved when the benzene concentration was
1.5 g m-3 and decreased with increase in benzene concentration. Lower flow
rates resulted in higher benzene removal efficiency. The concentration profile
was observed at different heights of filter media. Temperature increase during
biofiltration experiments confirmed the exothermic nature of biofiltration. The
carbon dioxide production rate was related to elimination capacity by the
equation CPR = 1.76EC + 18. A Michaelis-Menten type model was applied and
the kinetic constants, maximum elimination capacity, ECmax’ and saturation
constant, Ks were found to be 217.4 g m–3h–1 and 3.54 g m–3, respectively.
Keywords: kinetics, benzene, pollution.
Volatile organic compounds (VOCs) are considered to be a potential group of contaminants for
atmospheric air pollution caused through ozone layer
depletion and greenhouse effect. Benzene, along with
toluene, ethyl benzene and xylene, forms a group of
VOCs called as BTEX compounds and are reported
to contribute 59 mass% of gasoline pollutants [1,2].
Benzene is a potential carcinogen while the others
are mutagenic. These pollutants are listed in the European Pollutant Release and Transfer Register [3].
Due to the harmful nature of benzene, Environmental
Protection Agency has set a target to lower the benCorrespondence: N. Rajamohan, Faculty of Engineering, Sohar
University, Sohar, Oman.
E-mail: Rnatarajan@soharuni.edu.om
Paper received: 22 October, 2014
Paper revised: 9 March, 2015
Paper accepted: 31 March, 2015
zene concentration to 0.62% by 2011 [4]. Long term
exposure of benzene leads to leukemia, excessive
bleeding, anemia and immune system disorders [5,6].
Major sources of VOCs occur through storage tank
losses, process vessel vents, refining operations,
automotive emissions, heat exchangers and leaks
from piping network and equipment [7]. In addition,
VOCs are released by several industries including
chemical industries, foundries, printing and coating
industries, electronics and paint manufacturing indusries. Various technologies available for VOCs control
include absorption, incineration, ozonation, membrane separation, etc. However, these methods suffer
from demerits like high operating costs, lower removal
efficiency and secondary pollution problems [8]. In
this background, biotechnological processes evolved
and gained popularity due to their simplicity and cost-
537
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
effectiveness. Different bioreactor configurations,
namely biofilters, bio trickling filters, bio scrubbers
and suspended growth bioreactors are available for
VOC treatment [9]. Biofiltration is one of the biotechnological processes which involve the use of packing
media over which pollutant decomposing microorganisms are immobilized as a biofilm. The pollutant
laden air is passed through the biofilter column and
transferred from the air stream to the biofilm due to
the difference in concentrations [10]. A series of processes like absorption, diffusion and degradation are
involved in this process [11] and involves physical,
chemical and biological interactions [12]. In all instances, the microorganisms are reported to convert
the organics to carbon dioxide and water vapor. The
food source is provided by the organic compound
which helps in multiplication or activity of microorganisms [13]. Various factors like particle size and
surface area of packing media, pH, carbon source,
temperature and solubility of target pollutant are
reported to affect the efficiency of biofilters [14,15].
Biofilter operations have been reported under
unsteady-state, transient, short term and long term
shock loads, shut down and starvation conditions
[16,17]. Different packing media like compost and
pumice [18], press mud [19] and corn stacks [20]
have been investigated in various biofiltration studies.
Biofiltration of benzene was reported using Stenotrophomonas maltophilia 3c in a polyurethane based
biofilter [21]. Biofiltration of benzene in a compost
based biofilter was investigated in the concentration
range up to 1.7 g/m3 and removal efficiency of 90%
was reported [22]. BTEX degradation was evaluated
as separate substrates and in mixtures, in liquid
culture, and in packed biofilters with the filamentous
fungus Paecilomyces variotii CBS115145 and a benzene elimination capacity of 10 g C m-3 h-1, was
reported [23]. The maximum elimination capacities of
benzene obtained, at an inlet load of 6.12 g m-3 h-1,
were 3.50 and 3.80 g m-3 h-1 with raw and ground
sugarcane bagasse based biofilter, respectively [24].
Studies on biofiltration of benzene at very high concentrations were few and the choice of date palm tree
bark as a filter media was not investigated earlier. In
this experimental work, the feasibility of a novel biofilter media for biofiltration of benzene under mesophilic conditions was studied. The biofilter performance was evaluated in terms of removal efficiency
and elimination capacity. The influence of inlet loading and flow rate of the pollutant on the elimination
capacity was investigated. In addition, axial concentration profile and biomass growth variations are
538
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
monitored. Kinetic modeling was performed and the
constants were evaluated.
MATERIALS AND METHODS
Biofilter media
The biofilter media used in this study was date
palm tree barks. Date palm tree, Phoenix dactylifera,
belongs to the Palmae (Arecaceae) family and is a
native to Middle East countries where it is found in
large number and used as a staple food in Oman. The
tree barks were cut into pieces and screened for sizes
lesser than the diameter of the column by eight times
in order to avoid preferential flow on the side of the
column walls [25]. Physicochemical characterization
studies were performed to verify the chemical resistance of the filter media. The chemical resistance of
novel packing medium was tested by placing it in
glass beakers containing pure benzene, tap water,
acidic (pH 4.91) and basic (pH 9.23) solutions for 30
days. The filter media were then removed from the
solution, rinsed repeatedly with deionized water, dried
in an oven at 60 °C for 24 h, cooled in a desiccator,
and then reweighed. A slight change in color was
observed and the weight losses of 2.0 and 2.6% were
recorded with the samples placed in acidic and basic
solutions respectively. The choice of this filter media
was justified by its extensive availability and environmentally friendly disposability due to the natural biodegradaing ability in the longer duration.
Inoculum
The biofilter media was sterilized with an autoclave four times at 120 °C for 60 min and mixed with
40 mL of an activated sludge (1.5% w/V) collected
from a municipal wastewater treatment plant in a 5.0
L tank. After standing overnight, the biofilter was
loaded with the filter media in different sections. The
concentrated sludge was cultured in an aerated batch
reactor and diluted in 1 L of nutrient solution containing the following composition: K2HPO4 – 3.84 g L-1,
KH2PO4 – 1.94 g L-1and NH4Cl – 3.00 g L-1, at pH 6.9.
The packing media was mixed with the sludge in the
biofilter column and drained after 24 h and this procedure was repeated several times until visible biofilm
formation was noticed on the biofilter media.
Experimental studies
The biofilter reactor set up consists of an acrylic
column with an inside diameter of 5 cm and column
height of 100 cm. The biofilter column was equipped
with two sets of sampling ports located at 0 cm (inlet),
25 cm (section-1), 50 cm (section-2), 75 cm (section-3) and 100 cm (exit), for treated gas sampling and
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
temperature measurements along the height of the
biofilter. The treated gas was collected at the reactor
headspace and nutrient feed addition was performed
at the top of the column while a 10 cm bottom space
was utilized for leachate collection was provided. Figure 1 shows the biofilter setup with its components.
The biofilter column is equipped with a carbon dioxide
gas sensor (Extox, Germany) connected at the exit.
The synthetic benzene polluted air stream was generated by injecting a low flow compressed air stream
into the benzene tank. The air stream loaded with
benzene was mixed with the humidified pure air
stream in the mixing chamber in order to attain the
desired inlet concentration and fed into the biofilter
reactor in an up flow mode. The air flow rates are
regulated in the low (0-0.3 L min-1) and high (0-10.0 L
min-1) flow rate range using rotameter. All the gas flow
rates are manipulated using brass control valves. The
operating parameters are varied in the ranges: inlet
benzene concentration 1.5-6.0 g m-3 and flow rate
0.25-1.0 m3 h-1 and the samples were collected at
periodic intervals for analysis of residual benzene.
The nutrient solution, basal salts medium, with the following composition: K2HPO4 – 0.91 g; Na2HPO4⋅2H2O
– 2.39 g; (NH4)2SO4 – 1.97 g; FeSO4⋅2H2O – 0.2 g;
MgSO 4 ⋅7H 2 O – 2.0 g; MnSO 4 ⋅7H 2 O – 0.88 g;
Na2MoO4⋅2H2O – 1.0 mg; CaCl2 – 3.0 mg; ZnSO4⋅7H2O
– 0.04 g and CoCl2⋅6H2O – 0.04 mg per litre of water
was sprayed twice a day through the nutrient distribution system equipped with a peristaltic pump and
spray nozzle. The nutrient solution along with the
humidified air helps in maintaining the required relative humidity in the biofilter.
kin-Elmer, USA) equipped with a FID and a capillary
column, operated in off-line mode. The temperature
conditions were 160 °C for injector and 280 °C for
detector. The oven temperature was set at 60 °C for
the first 5 min and increased at a rate of 15 °C per
min to reach 180 °C and held at 4 min. Helium was
used as a carrier gas at a flow rate of 2 ml min-1. The
temperature of the filter bed was measured using
temperature sensors connected to a data logger. The
head space gas was analysed for carbon dioxide concentration using online gas analyzer (Extox, Germany).
Performance evaluation
The performance of the biofilter was measured
in terms of the removal efficiency (%RE), elimination
capacity (EC), g m–3 h–1, and carbon dioxide production rate (CPR), g m–3 h–1. These parameters are
defined as given below:
%RE = 100
EC =
C 0 − Ct
C0
(1)
Q (C 0 − Ct )
(g m-3 h-1)
V
CPR =
Q (C CO2 out − C CO2 ,in )
V
(g m-3 h-1)
(2)
(3)
The Empty Bed Residence Time (EBRT) is
defined as:
EBRT =
V
(h)
Q
(4)
The inlet loading rate (ILR) is defined as:
Analytical methods
Inlet and exit benzene concentrations in gas
samples were measured by gas chromatograph (Per-
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
ILR =
QC 0
(g m-3 h-1)
V
(5)
Figure 1. Biofiltration experimental setup.
539
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
where C0 and Ct represent the inlet and exit
concentrations of benzene (g m-3), Q is the flow rate
of the benzene (m3.h-1),V is the volume of the biofilter
(m3), CCO2out and CCO2,in represent exit and inlet concentrations of carbon dioxide (g m-3).
RESULTS AND DISCUSSION
Effect of inlet benzene concentration
The effect of inlet benzene concentration was
studied in the range of 1.5-6.0 g m-3 during a biofiltration period of 65 days. In order to acclimate the
microbial culture to higher VOC concentrations, the
concentration of input benzene was increased stepwise by maintaining an inlet concentration of 1.5 g m-3
for the first 16 days followed by 3.2 g m-3 during the
second phase of 17-32 days of operation. The outlet
concentrations of benzene were monitored once in 24
h and the removal efficiency was calculated. The variation in removal efficiency during the different phases
is presented in Figure 2. The maximum removal efficiency obtained was 99% with the lowest benzene
concentration and the efficiency dropped to 91.8, 85.1
and 76%, respectively, with the inlet concentrations of
3.2, 4.8 and 6.0 g m-3, respectively. The experimental
data confirmed the decrease in the removal efficiency
and increase in exit VOC concentration when the inlet
benzene concentration was increased. Excessive
addition of input benzene beyond the threshold withstanding ability of microbes was reported to be a
reason for this behaviour [26]. At higher inlet benzene
concentrations,a transient state induced by high concentration shock to microorganism was reported to
occur and it leads to kinetic limitation. In addition, drying of the bed axially, channeling of air stream due to
biomass accumulation and product inhibition were
reported to be the other factors [8].
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
Elimination capacity, defined as the amount of
pollutant degraded per unit time, normalized to the
packed bed volume is reported to be affected by the
inlet loading of benzene. The influence of inlet benzene loading rate on the elimination capacity was studied in the range of 0-306 g m–3 h-1. From Figure 3, a
linear relationship between elimination capacity and
loading rate was observed. A linear relation was reported in the biofiltration study on hydrogen sulfide
using granular activated carbon [27]. The maximum
elimination capacity achieved was 192.7 g m–3 h–1 as
shown in the plot which is comparatively higher than
the capacities of 3.8 and 44.9 g m–3 h–1 reported on
other benzene biofiltration studies [6,23]. The rate of
increase in elimination capacity was observed to be
slower at higher loading rates of benzene. This phenomenon could be related to the attainment of maximum removal capacity of microorganisms. Biofiltration studies on hydrogen sulfide using pine bark filter
media reported a similar relationship between elimination capacity and inlet loading rate [28]. The leachate was collected periodically from the tail end of the
column and its volume was approximately 250 mL per
day.
Effect of EBRT
The flow rate of the benzene laden air is identified as an important process variable as it decides
the quantity of pollutant to be degraded per unit time.
In this study, the influence of flow rate (or EBRT) was
studied in the range of 1.2-4.7 min. Figure 4 presents
a plot of EBRT versus removal efficiency attained at
different times. At increased EBRT, the time of exposure of microorganism to the target pollutant was high
and could possibly resulted in better removal efficiency [19,26]. It was observed that when the inlet benzene concentration was low in the range of 1.5-3.0 g
m-3, the removal efficiencies achieved at lowest flow
Figure 2. Biofiltration results for benzene removal at different inlet loading rates.
540
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
Figure 3. Effect of inlet loading rate on elimination capacity of benzene.
Figure 4. Effect of EBRT on benzene removal efficiency.
rate were higher by 20%. But, at higher benzene
concentrations of 4.5 and 6.0 g m-3, the effect is less
pronounced with a reduced net difference in removal
efficiency.
Effect of biofilter height
The biofilter reactor employed consisted of four
different sections with different biomass distributions.
In order to identify the relative contribution of each
section in benzene degradation, the concentration
profile was studied axially and plotted in Figure 5. The
lowest section of the biofilter contributes to 40-45% of
the total removal while the other sections degrade the
remaining benzene. The reasons reported to be responsible for better removal at the section-1 were
better biomass distribution and moisture content.
During the course of biofiltration, the temperature of
Figure 5. Concentration profile of benzene along the biofilter height.
541
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
the bed is expected to increase which could affect the
moisture content at the top sections of the biofilter.
Since the biofilter was operated in up-flow mode, the
driving force varies from section to section. The local
benzene concentration was high at the lowest section
and lowest in the topmost section of the biofilter [6].
Higher microbial density and homogeneous biomass
distribution in the lowest part of the bed could be the
reasons for this behaviour. Moreover, the concentration gradients in the upper sections are comparatively lower, which resulted in lower removal efficiencies. Also, the filter bed could be dry in the upper
sections due to the exothermic nature of the bio reaction. More efficient removal of toluene was reported in
the first section of a compost based biofilter [24]. Studies on removal of xylene in the inlet loading range of
12-34 g m–3 h–1 reported most of the removal in the
lower part of the biofilter column in a peat based biofilter [23].
Variation of bed temperature
The temperature variations during the biofiltration experiments were followed by recording the average bed temperature. Figure 6 shows the interactive
variation patterns in temperature and elimination capacity. As expected, the biodegradation reaction of
benzene was found to be exothermic which is proved
by increase in temperatures at higher elimination capacities and microbial metabolic activity causes the
increase of temperature. The temperature of the bed
increased from 26.6 to 29.7 °C when there is a corresponding increase in elimination capacity from 16.8
to 192.7 g m–3 h–1. The increase in temperature within
the mesophilic range was reported to favour better
removal of benzene by enhancing the activity of microorganisms [8].
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
Carbon dioxide production profile
The proposed biodegradation mechanism of
benzene is as shown in Eq. (6), where the possible
products are carbon dioxide, water and biomass:
aC6H6 + b O2 →c CO2 + d H2O + e(biomass)
The carbon dioxide production profile was recorded and plotted against elimination capacity in Figure 7. A linear relationship represented by an equation CPR = 1.76EC + 18.6 was found out with a high
value of correlation coefficient, R2 (> 0.99). When
complete mineralization of benzene into water and
carbon dioxide was assumed, the stoichiometric mole
ratio between benzene and carbon dioxide is 1:6 and
mass ratio could be 1:3.38. However, the actual conversion ratio was 1.76, which was lower than the
theoretical value of 3.38. The difference in value was
attributed to the possible consumption of benzene for
the microbial growth inside the reactor during the biofiltration process. Also, the carbon dioxide could have
accumulated in the liquid phase in the form of carbonates and bicarbonates [29]. Studies on removal of
toluene in peat based biofilter [30] and xylene in an
inert filter media biofilter [2] reported actual conversion ratios lesser than the stoichiometric ratios.
Biomass profile during biofiltration
Biodegradation efficiency depends on the establishment of uniform biofilm and growth intensity inside
the biofilter column. The dry cell mass was measured
in different sections during the benzene biofiltration
experiments and plotted in Figure 8. In section 1 of
the biofilter column, the dry cell mass concentration
increased from 0.16 to 0.35 g g-1 of filter media and
found to be the maximum biomass buildup compared
Figure 6. Temperature variation profile during the biofiltration experiments.
542
(6)
R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
Figure 7. Elimination capacity versus carbon dioxide production.
Figure 8. Biomass profile during benzene biofiltration.
to other sections of the biofilter. This observation was
supplemented by enhanced removal percentages at
section-1. These results show the attainment of a
stable microbial density which is higher than the initial
biomass in the filter media. The cell mass build up
was found to be less at the top section due to the
lower availability of benzene.
Kinetic modeling
The removal rate of benzene in the immobilized
cell biofilter was fitted to a modified Michaelis- Menten
model, shown below in a linearized form as Eq. (7)
[31]:
1
EC
=
Ks
Ks
+
ECmaxC ln ECmax
(7)
where ECmax (g m-3 h-1) is the maximum EC, Cln (g m-3)
is the logarithmic mean of inlet and outlet benzene
concentrations and Ks (g m-3) is the saturation constant. The slope and intercept of the linear fit between
1/EC and 1/Cln plot shown in Figure 9 gives the
values of the kinetic parameters, ECmax and Ks. The
value of R2 was found to be 0.61. The kinetic constants will depend on the microorganisms attached to
the filter media. The values of ECmax and Ks were
found to be 217.4 g m-3 h-1 and 3.54 g m-3, respectively. The value of ECmax observed in this study was
found to be in the range of values reported for ethyl
benzene removal using Macadamia ternifolia nutshells as filter media [32]. The physical meaning of Ks
corresponds to the benzene concentration that must
be treated to achieve ECmax/2. A material having a
small Ks value was reported to have a greater affinity
to benzene and vice-versa. The value of Ks observed
in this study was comparatively less than the values
of 70 g m-3 reported with biofiltration of hydrogen
sulfide in a novel media biofilter [28] and 47 g m-3
reported with biofiltration of hydrogen sulfide and
ammonia in an alginate beads based biofilter [33].
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R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES…
Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)
Figure 9. Kinetic model plot for biofiltration kinetics of benzene.
CONCLUSION
The performance of a biofilter to treat benzene
at different inlet loading rates was evaluated using a
novel tree bark filter medium. The influence of inlet
benzene concentration on the removal efficiency was
studied and the biofilter was found to handle high
concentrations of benzene effectively. Higher retention times or lower flow rates favoured better removal
of benzene in the biofilter. The axial concentration
profile of benzene in the biofilter column proved a
larger percentage of benzene removal in the lowest
part of the column reactor. Carbon dioxide production
rate was compared with the elimination capacity of
benzene and a linear relationship was proposed.
Temperature variations were recorded and found to
vary with elimination capacity changes. The biokinetic
constants were calculated using a modified Michaelis–Menten model. The results suggest that the date
palm tree bark based biofilter is a suitable choice for
treating benzene in the concentration range of 1.5-6.0
g m-3.
Acknowledgement
The authors acknowledge that this research
leading to these results has received project funding
from The Research Council of Oman under Research
Agreement No.: ORG/SU/EBR/12/020. Also, the
authors thankfully acknowledge the facilities provided
by Sohar University, Oman.
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RAJAMOHAN NATARAJAN1
JAMILA AL-SINANI1
SARAVANAN VISWANATHAN2
PROCENA PERFORMANSI I KINETIKA
UKLANJANJA BENZENA U BIOFILTERU NA BAZI
KORE DRVETA SA STRUJANJEM NAVIŠE
1
Faculty of engineering, Sohar
University, Sohar, Oman
2
Department of Chemical Engineering,
Annamalai University, India
NAUČNI RAD
U radu je pogodnost primene kore drveta Phoenix dactylifera kao novog filter medija u
biofilteru sa strujenjem naviše i mešanom kulturom za uklanjanje benzena. Eksperimenti
su rađeni sa različitim koncentracijama benzena (1,5–6,0 g m-3) i vremenom zadržavanja u
filter bez biomaterijala (EBRT = 1,2- 4,7 min). Nađeno je da eliminacioni kapacitet linearno
varira sa brzinom ulaznih količina benzena u opsegu od 0-306 g.m-3 h-1. Pri koncentraciji
benzena od 1,5 g m-3 postiže se efikasnost uklanjanja od 99%. Ona opada sa porastom
koncentracije benzena. Pri manjim protocima efikasnost uklanjanja benzena je veća. Analiziran je koncentracioni profil za različite visine filter medija. Pošto temperatura raste za
vreme biofiltracije eksperiment potvrđuje egzotermnu prirodu biofiltracije. Brzina stvaranja
ugljen dioksida u odnosu na kapacitet eliminacije data je jednačinom CPR = 1.76EC +
+ 18.6. Primenom Michaelis-Menten modela nađene su kinetičke konstante, kao što su:
maksimalni eliminacioni kapacitet 217,4 g m-3 h-1 i konstanta zasićenja 3,54 g m-3.
Ključne reči: kinetika, benzen, zagađenje.
545
Available on line at
Association of the Chemical Engineers of Serbia AChE
www.ache.org.rs/CICEQ
Chemical Industry & Chemical Engineering Quarterly
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
D.TIROUTCHELVAME1
V. SIVAKUMAR2
J. PRAKASH MARAN3
1
Department of Food Processing
and Engineering, Karunya
University, Coimbatore, Tamil
Nadu, India
2
Department of Chemical
Engineering, AC Tech Campus,
Anna University, Chennai, Tamil
Nadu, India
3
Department of Food Technology,
Kongu Engineering College,
Perundurai, Erode, Tamil Nadu,
India
SCIENTIFIC PAPER
UDC 66.093.48:58(540):544
DOI 10.2298/CICEQ140712011T
CI&CEQ
MASS TRANSFER KINETICS DURING
OSMOTIC DEHYDRATION OF AMLA (Emblica
officinalis L.) CUBES IN SUGAR SOLUTION
Article Highlights
• Osmotic dehydration of amla cubes were studied using RSM
• Mass transfer properties and quality characteristics of dehydrated amla cubes were
studied
• Second order polynomial models were developed for responses
• Optimization of osmotic dehydration process was done by desired function methodology
Abstract
A four-factor three-level Box-Behnken response surface design was employed
in this study to investigate and optimize the effect of process variables (osmotic solution concentration, fruit to liquid ratio, temperature and dehydration
time) on mass transfer properties such as weight reduction, solute gain, water
loss, rehydration ratio, shrinkage and overall acceptability of the osmotically
dehydrated amla cubes. The cubes of uniform size (10 mm×10 mm×10 mm)
were impregnated into sugar solution of different solution concentration (30-50
°Brix), temperature (30-50 °C), fruit to liquid ratio (1:5-1:15 w/V) and time (30–180 min). It was observed from the results that the process variables have
significant effects on osmotic dehydration process. The optimum condition was
found to be: sugar concentration of 50 °Brix, solution temperature of 30 °C,
fruit to liquid ratio of 1:5 and immersion time of 133 min, respectively. The microstructural changes during osmotic dehydration were also investigated using
scanning electron microscopy (SEM).
Keywords: amla, osmotic dehydration, response surface methodology,
microstructure.
Fruits and vegetables are considered to be
important components of life for the health of human
beings by providing the required nutrients. Since fruits
and vegetables are highly perishable in nature, they
should be processed quickly after harvest in order to
reduce the post-harvest losses during glut period. As
a perishable commodity, they are available at much
cheaper in terms of selling price during the peak
season, and can also lead to more financial losses to
the grower resulting in the spoilage in larger quantities. The preservation of fruits and vegetables can
Correspondence: V. Sivakumar, Department of Chemical Engineering, AC Tech Campus, Anna University, Chennai, Tamil
Nadu, India.
E-mail: drvsivakumar@yahoo.com
Paper received: 12 July, 2014
Paper revised: 16 March, 2015
Paper accepted: 20 April, 2015
prevent a huge wastage and make them available
during the off-season at remunerative prices [1].
The removal of water from solid food is a form of
food preservation, inhibiting the growth of microorganisms, besides preventing a large part of biochemical reactions that occur due to the presence of
moisture [2]. The dehydration process of fruits and
vegetables provides many advantages, such as reduced weight, inexpensive packaging, dry shelf stability and negligible deterioration in quality due to
enzymatic changes. However, this method has some
disadvantages related to the preparation and handling
of large volumes of osmotic solutions, high water consumption and losses of soluble nutritional compounds
in the osmotic solution. Proper management and
reuse of the spent osmotic solution need to be
addressed in order to develop this process to be economically viable and cost effective.
547
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Osmotic dehydration is the process of partial
removal of water from fruits and vegetables using
hypertonic solutions. These solutions can contain one
or more solutes. For fruits, sugar is the commonly
used solute. Other solutes that are used as osmotic
agents include glucose, fructose, maltodextrose and
corn syrup [3]. Common salt (sodium chloride) is the
most used solute for vegetables. In some cases, a
combination of solutes can also be used. Osmotic
dehydration is governed by the osmotic pressure difference between the food material (hypotonic
medium) and concentrated osmotic solution (hypertonic medium) [4]. The cell membrane works as a
semi-permeable tissue and allows water to pass
through faster than solutes [5]. The mass transfer rate
is higher at the beginning of the process because of
the largest difference in the osmotic pressure
between the osmotic solution and cell tissue of the
material and less mass transfer resistance at the initial stage of the process [6]. The rate of water removal
from the food material and changes in the chemical
composition depend on the type of osmotic solute
used, its concentration, temperature, time of impregnation in the solution, fruit to solution ratio, size and
kind of the material and the type of apparatus used.
During osmotic dehydration, two main mass fluxes
(water loss and solid gain) take place as countercurrent. The effectiveness of the osmotic treatment
can be evaluated by the ratio of water loss to solid
gain, considering that the water removal must be
greater than the solid intake [7]. The low values of this
ratio establish the best condition of osmotic dehydration [8].
Amla (Emblica officinalis L.), commonly called
as Indian gooseberry is an important seasonal fruit
crop of the Indian subcontinent [9]. The plant has the
ability to grow in wastelands and cultivation area has
increased in the recent years [10]. Owing to hardy
nature, suitability to various wastelands, high productivity/unit area (15-20 t/ha), nutritive and therapeutic
value, amla is becoming more and more commercially
important now a days. Amla is highly nutritious and is
an important dietary source of Vitamin C, minerals
and amino acids. It contains 500-1500 mg of ascorbic
acid per 100 g of pulp [11]. The medicinal properties
of amla were studied as a preventive and therapeutic
drug for cancer in humans [12]. Studies have also
been performed for the evaluation of amla properties
on in vivo tests [13].
Amla is highly perishable in nature and it can be
stored under atmospheric conditions only for about 56 days after harvesting [14]. The storage and shelf life
of the fruits can be increased by adopting appropriate
548
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
processing methods and it could eliminate the post-harvest losses up to 30% [15]. The methods adopted
for extending the shelf life of amla fruit include cold
storage, sun drying and hot air drying or by value
addition of the fruits by converting to murabba, pickle,
juice, syrup, squash and dehydrated powder [16].
Among the various drying methods available, osmotic
dehydration is one of the most simple and inexpensive alternate processes. It is an energy-saving and
low capital investment process that offers a way to
make available this highly perishable and valuable
crop for the regions away from production zones and
also during off-season. The cultivation of amla has
increased, thus augmenting the post-harvest storage
problems. Development of shelf stable products from
amla is important for the reduction of post-harvest
losses. Hence, the objective of the present research
was to evaluate and optimize the influence of the
process variables such as osmotic solution concentration, time of dehydration, temperature and fruit to
liquid ratio on the osmotic dehydration characteristics
(water loss, solid gain, weight reduction, rehydration
ratio and shrinkage) of amla cubes in sugar solution
using statistical experimental design. In addition, the
overall acceptability of the product was also analyzed
with the help of trained panelist using a nine point
hedonic scale sensory evaluation method. Scanning
electron microscopy (SEM) was also used to analyze
the microstructural changes during osmotic dehydration of amla.
MATERIALS AND METHODS
Raw materials
Fresh amla fruits (uniform size, shape, and maturity) were procured from local market near Coimbatore, Tamil Nadu, India. Osmotic solutions with
different concentration (30-50 °Brix) were prepared by
dissolving appropriate amount of sugar in distilled
water. The concentrations (°Brix) of the prepared
osmotic solutions were checked by using a hand refractometer. The initial moisture content of the raw fruit
and the final moisture content after impregnation in
sugar solution were determined by following AOAC
procedure [17]. The initial moisture content (wet
basis) of fresh amla fruit was 80.5% and the final
moisture content after osmotic treatment in sugar solution was found to be 61.5%.
Experimental procedure
The amla fruit was cut in to 1 cm3 (10 mm×10
mm×10 mm) size cubes for each experiment. The
amla fruits were washed in running tap water in order
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
to remove any adhering foreign matters on the surface. The outer skin of the fruit is waxy in nature
which will resist the mass transfer rate. Hence, the
fruits were blanched for 5 min in hot water, which
could remove the unacceptable odor and to increase
the mass transfer by loosening the tissues of the fruit.
The fruits were then removed from hot water and the
excess moisture on the surface was removed by
using muslin cloth. The seeds were removed by using
seed remover and the pulp of the fruit was used for
further experimental analysis.
The desired concentration of osmotic solution of
sugar was prepared and the known weight of amla
cubes were immersed in Erlenmeyer flasks containing
osmotic solutions of different concentrations (30-50
°Brix) at different temperatures (30-50 °C), fruit to
liquid ratio (1:5-1:15 w/V) and time (30-180 min).
From the preliminary experimental results, the process variables and their ranges were selected. The
osmotic dehydration process was carried out in a
temperature-controlled chamber. The Erlenmeyer
flasks were covered with a plastic wrap during the
experiments in order to prevent evaporation of the
osmotic solution. During osmotic treatment, at a particular interval of time, the cubes were removed from
the osmotic solution and weighed after removing the
solution adhering on the surface using filter paper
(Whatman No. 1). The experiments were carried out
in randomized order to minimize the variability in the
observed responses due to extraneous factors. All the
experiments were performed in triplicate and the
mean value was used for the determination of water
loss, weight reduction and solid gain.
Mathematical calculations
Determination of mass transfer properties
In osmotic dehydration, both water loss and
solid gain take place simultaneously. The reduction in
weight is attributed to the loss of water from the
sample and increase in the weight of the sample due
to solute gain from the osmotic solution. The evaluation of mass transfer between the solution and
samples during osmotic dehydration process were
estimated by using the parameters such as weight
reduction (WR), solid gain (SG) and water loss (WL)
and the parameters were calculated by using the
following equations:
W − Wt
WR ( % ) = 100 0
W0
SG ( % ) = 100
St − S 0
W0
(1)
(2)
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
WL ( % ) = WR + SG
(3)
where W0 is the initial weight of amla cubes (g), Wt
the weight of amla cubes after osmotic dehydration
for any time t (g), S0 is the initial dry weight of amla
(g), and St is dry weight of amla after osmotic
dehydration for any time t (g).
Estimation of quality parameters
The quality parameters such as rehydration ratio
(RR) and shrinkage (SH) of the osmotic dehydrated
amla cubes were studied in the present work. The
rehydration characteristics of the osmotically dehydrated amla cubes were determined by soaking a
known amount of sample in 50 ml of water and kept at
room temperature [18] until constant weight was
attained. The rehydration ratio was computed by
using the formula:
RR (%) =
Weight of rehydrated amla cube (g)
× 100 (4)
Weight of dehydrated amla cube (g)
Shrinkage (SH) of the dehydrated sample was
determined by using the following equation:

SH (%) = 100  1 −

Vi 

V 0 
(5)
where Vi is the volume displaced by the dehydrated
sample and V0 is the volume displaced by the fresh
sample [19].
Organoleptic evaluation
Overall acceptability (OA) of dehydrated amla
cubes was evaluated by a trained panel of 10 members of all age groups (15-50). The samples were
served in plastic cups, coded with three-digit randomly selected numbers to the panelists in a random
order. The panelists were instructed to cleanse their
palates using water between the samples. All the
panelists evaluated the odor and taste of the samples
using quantitative descriptive analysis (QDA) technique with a line scale of 0-9 [20] where 0 and 9 are
assigned to negative and positive intensity of overall
acceptability of dehydrated amla cubes. The overall
acceptability was computed by the average scores of
all the 10 panelists.
Response surface methodology modeling
Response surface methodology (RSM) is an
empirical statistical modeling technique employed for
multiple regression analysis using quantitative data
obtained from properly designed experiments to solve
multivariate equations simultaneously. A Box Behnken Design (BBD) with four factors at three levels was
used to design the experiments and it is exhibited in
549
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Table 1. The process parameters (independent variables) selected for the optimization were osmotic
solution concentration (X1), fruit to liquid ratio (X2),
osmotic temperature (X3) and osmotic dehydration
time (X4). The number of experiments (N) required for
the development of BBD is defined as N = 2k(k-1) +
+ Co (where k is the number of factors and Co is the
number of central point) [21]. The design included 29
experiments and with 5 central points. Each independent variable was coded at three levels between
+1, 0 and -1, whereas osmotic solution concentration:
30-50 °Brix, fruit to liquid ratio: 1:5-1:15 g/ml, osmotic
temperature: 30-50 °C and time: 30-180 min. Coding
of the variables was done according to the following
equation:
xi =
x i − x cp
, i = 1,2,3..., k
Δx i
(6)
where xi is the dimensionless value of an independent
variable; Xi is the real value of an independent
variable; xcp is the real value of an independent variable at the center point; and ΔXi is the step change of
real value of the variable i corresponding to a variation of a unit for the dimensionless value of the variable i.
Performance of the process was evaluated by
analyzing the responses (Y), which depend on the
input factors x1, x2,…,xk, and the relationship between
the response and the input process parameters is
described by:
Y = f ( x 1, x 2 ,..., x k ) + e
(7)
where f is the real response function the format of
which is unknown and e is the error which describes
the differentiation [22].
A second-order polynomial equation was used
to fit the experimental data to identify the relevant
model terms using statistical software (Design Expert
8.0.7.1). A quadratic model, which also includes the
linear model, can be described as
k
k
j =1
j =1
k
Y = β0 + Σ β j x j + Σ β jj x 2j + Σ Σ βij x i x j + ei
i < j =2
(8)
where xi and xj are variables (i and j range from 1 to
k); β0 is the model intercept coefficient; βj, βjj and βij
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
are interaction coefficients of linear, quadratic and the
second-order terms, respectively; k is the number of
independent parameters (k = 4 in this study); and ei is
the error [23].
The statistical analysis was performed using
Design Expert Statistical Software package 8.0.7.1
(Stat Ease Inc., Minneapolis, MN, USA). The experimental data was analyzed using multiple regressions
and the significance of regression coefficients was
evaluated by F-test. Modeling was started with a
quadratic model including linear, squared and interaction terms and the model adequacies were checked
in terms of the values of R2, adjusted R2 and prediction error sum of squares (PRESS). The significant
terms in the model were found by Pareto analysis of
variance (ANOVA) for each response at significance
level of 95% and ANOVA tables were generated. The
regression coefficients were used to make statistical
calculations to generate response surface plots from
the regression models.
Microstructure analysis
The fresh and osmotically treated (optimal condition) amla pieces were examined using scanning
electron microscopy (SEM) in order to determine the
effect of osmotic dehydration process on the microstructure of the tissue. Samples were cut into cubes
with a sharp blade and mounted on aluminium SEM
stubs for gold coating with a fine coat. The microstructure of the tissue was examined by a JEOL scanning electron microscope (JSM-6390) and the images
were recorded at the magnification of 100×.
RESULTS AND DISCUSSION
Model fitting and statistical analysis
A total number of 29 experiments were performed with different combinations of process variables in order to study and optimize the combined
effect of independent variables (osmotic solution concentration, fruit to liquid ratio, osmotic temperature
and time) on the responses (WR, SG, WL, RR, SH
and OA) and the results are shown in Table 2.
By applying multiple regression analysis on the
experimental data, Design-Expert software generated
the second-order polynomial equation, which can
Table 1. Coded and uncoded values of process variables and their levels during osmotic dehydration of amla cubes in sugar solution
Independent variables
Coded levels
−1
0
Solution concentration, °Brix
X1
30
40
50
FL ratio, g/ml
X2
1:5
1:10
1:15
Temperature, °C
X3
30
40
50
Time, min
X4
30
105
180
550
+1
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Table 2. Box-Behnken experimental design matrix with observed values of responses for the osmotically treated amla cubes in sugar
solution; WR: weight reduction, SG: solid gain, WL: water loss, RR: rehydration ratio, OA: overall acceptability, SH: shrinkage
Std. order
X1
X2
X3
X4
WR / %
SG / %
1
-1
-1
0
0
22.91±1.03
7.75±0.43
28.19±1.21
4.6±0.13
6.2±0.18
3.8±0.23
2
1
-1
0
0
32.55±1.18
17.35±0.65
37.84±1.30
14.3±0.27
7.9±0.21
11.9±0.48
3
-1
1
0
0
22.34±1.09
7.18±0.23
27.62±1.26
4.0±0.14
6.1±0.19
3.4±0.09
4
1
1
0
0
26.26±1.24
11.06±0.43
31.51±1.32
8.0±0.32
6.8±0.22
6.6±0.31
5
0
0
-1
-1
27.30±1.17
12.11±0.26
32.54±1.05
9.0±0.37
7.0±0.36
7.5±0.28
6
0
0
1
-1
31.46±1.13
16.26±0.68
36.71±1.28
13.2±0.28
7.7±0.43
11.0±0.45
7
0
0
-1
1
23.86±1.31
8.71±0.29
29.10±1.15
5.6±0.17
6.4±0.61
4.6±0.17
8
0
0
1
1
33.68±1.26
18.53±0.41
38.93±1.29
15.4±0.33
8.1±0.24
12.8±0.29
9
-1
0
0
-1
24.56±1.14
9.36±0.09
29.81±1.14
6.3±0.19
6.5±0.08
5.2±0.22
10
1
0
0
-1
32.95±1.21
17.75±0.62
38.23±1.35
14.7±0.52
8.0±0.25
12.2±0.26
11
-1
0
0
1
24.55±1.09
9.35±0.33
29.81±1.26
6.3±0.18
6.5±0.36
5.2±0.17
12
1
0
0
1
33.87±1.21
18.71±0.53
39.11±1.17
15.6±0.53
8.2±0.28
13.0±0.26
13
0
-1
-1
0
26.96±1.15
11.76±0.27
32.24±1.24
8.7±0.16
7.1±0.23
7.2±0.19
14
0
1
-1
0
17.14±1.04
1.94±0.06
22.38±1.18
1.2±0.11
5.2±0.23
1.0±0.06
15
0
-1
1
0
28.05±1.12
12.86±0.47
33.30±1.27
9.8±0.47
7.0±0.18
8.1±0.25
16
0
1
1
0
31.44±1.36
16.25±0.18
36.73±1.35
13.2±0. 53
7.7±0.17
11.0±0.39
17
-1
0
-1
0
19.48±1.07
4.29±0.08
24.76±1.13
1.2±0.12
5.6±0.37
1.0±0.05
18
1
0
-1
0
31.21±1.27
16.06±0.41
36.46±1.24
12.9±0.61
7.7±0.19
10.8±0.24
19
-1
0
1
0
31.44±1.32
16.24±0.29
36.73±1.28
13.2±0.53
7.7±0.31
11.0±0.27
20
1
0
1
0
37.11±1.35
21.91±0.63
42.35±1.35
18.8±0.61
8.7±0.22
15.7±0.39
21
0
-1
0
-1
26.83±1.17
11.63±0.25
32.11±1.23
8.5±0.24
6.9±0.27
7.1±0.21
22
0
1
0
-1
28.11±1.09
12.92±0.37
33.36±1.19
9.8±0.29
7.1±0.37
7.6±0.14
23
0
-1
0
1
27.46±1.05
12.27±0.31
32.71±1.16
9.2±0.27
7.0±0.62
7.6±0.18
24
0
1
0
1
23.90±1.13
8.71±0.26
29.19±1.14
5.6±0.18
6.4±0.65
4.7±0.21
25
0
0
0
0
39.29±1.28
24.10±0.72
44.53±1.25
21.0±0.67
9.1±0.53
17.5±0.29
26
0
0
0
0
39.29±1.25
24.11±0.63
44.53±1.27
21.0±0.62
9.1±0.45
17.5±0.22
27
0
0
0
0
39.29±1.21
24.14±0.68
44.53±1.23
21.0±0.58
9.1±0.32
17.5±0.36
28
0
0
0
0
39.29±1.19
24.10±0.47
44.54±1.19
21.0±0.64
9.1±0.31
17.5±0.32
29
0
0
0
0
39.29±1.16
24.10±0.61
44.54±1.28
21.0±0.39
9.1±0.56
17.5±0.41
express the relationship between process variables
and the responses. The final equations obtained in
terms of coded factors are as follows:
WL / %
RR / %
OA
Pareto analysis of variance (ANOVA) was used
to analyze the experimental data and the results are
listed in Table 3. The higher model F-value (84.10 for
WR = 39.29 + 4.06 X 1 − 1.301X 2 + 3.94 X 3 + 1.43 X 1X 2 − 1.52 X 1X 3 + 3.30 X 2 X 3 − 1.21X 2 X 4 + 1.42 X 3 X 4 −
−4.97 X 12 − 8.13 X 22 − 4.98 X 32 − 5.05 X 42
SG = 24.11 + 4.06 X 1 − 1.30 X 2 + 3.93 X 3 + 1.43 X 1X 2 − 1.52 X 1X 3 + 3.30 X 2 X 3 − 1.21X 2 X 4 + 1.42 X 3 X 4 −
−4.97 X 12 − 8.13 X 22 − 4.98 X 32 − 5.06 X 42
WL = 44.53 + 4.05 X 1 − 1.30 X 2 + 3.94 X 3 + 1.44 X 1X 2 − 1.52 X 1X 3 + 3.32 X 2 X 3 − 1.19 X 2 X 4 + 1.41X 3 X 4 −
−4.95 X 12 − 8.11X 22 − 4.98 X 32 − 5.05 X 42
SH = 17.50 + 3.38 X 1 − 0.97 X 2 + 3.12 X 3 − 1.19 X 1X 2 − 1.26 X 1X 3 + 2.27 X 2 X 3 − 0.87 X 2 X 4 + 1.18 X 3 X 4 −
−4.20 X 12 − 6.66 X 22 − 3.97 X 32 − 4.34 X 42
RR = 21.00 + 4.06 X 1 − 1.11X 2 + 3.75 X 3 − 1.43 X 1X 2 − 1.52 X 1X 3 + 2.73 X 2 X 3 − 1.21X 2 X 4 + 1.42 X 3 X 4 −
−5.06 X 12 − 7.94 X 22 − 4.79 X 32 − 5.15 X 42
OA = 9.12 + 0.71X 1 − 0.23 X 2 + 0.66 X 3 − 0.25 X 1X 2 − 0.27 X 1X 3 + 0.67 X 2 X 3 − 0.20 X 2 X 4 + 0.25 X 3 X 4 −
−0.87 X 12 − 1.42 X 22 − 0.87 X 32 − 0.89 X 42
SH / %
(9)
(10)
(11)
(12)
(13)
(14)
551
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Table 3. Analysis of variance (ANOVA) for the observed responses; DF: degree of freedom, RC: regression coefficient
Source
DF
WR / %
RC
Model
14
X1
X2
SG / %
p value
RC
p value
WL / %
RR / %
OA / %
SH / %
RC
p value
RC
p value
RC
p value
RC
p value
44.53
< 0.0001
21
< 0.0001
9.12
< 0.0001
17.50
< 0.0001
< 0.0001
39.29
< 0.0001 24.11 < 0.0001
1
4.06
< 0.0001
4.06
< 0.0001
4.05
< 0.0001
4.06
< 0.0001
0.71
< 0.0001
3.38
1
-1.30
0.0004
-1.30
0.0004
-1.30
0.0004
-1.11
0.0013
-0.23
0.0004
-0.97
0.0005
X3
1
3.94
< 0.0001
3.93
< 0.0001
3.94
< 0.0001
3.75
< 0.0001
0.66
< 0.0001
3.12
< 0.0001
X4
1
-0.32
0.2660
-0.31
0.2823
-0.33
0.2609
-0.32
0.2639
-0.05
0.2972
-0.22
0.3189
X12
1
-1.43
0.0101
-1.43
0.0105
-1.44
0.0097
-1.43
0.0098
-0.25
0.0114
-1.19
0.0061
X13
1
-1.52
0.0071
-1.53
0.0071
-1.52
0.0070
-1.52
0.0069
-0.27
0.0081
-1.26
0.0042
X14
1
0.23
0.6341
0.24
0.6241
0.22
0.6548
0.23
0.6326
0.04
0.6413
0.20
0.6058
X23
1
3.30
< 0.0001
3.30
< 0.0001
3.32
< 0.0001
2.73
< 0.0001
0.67
< 0.0001
2.27
< 0.0001
X24
1
-1.21
0.0248
-1.21
0.0252
-1.19
0.0267
-1.21
0.0242
-0.20
0.0326
-0.87
0.0346
X34
1
1.42
0.0108
1.42
0.0110
1.42
0.0108
1.42
0.0105
0.25
0.0122
1.18
0.0065
X12
1
-4.97
< 0.0001
-4.97
< 0.0001
-4.95
< 0.0001
-5.06
< 0.0001
-0.87
< 0.0001
-4.20
< 0.0001
X22
1
-8.13
< 0.0001
-8.14
< 0.0001
-8.11
< 0.0001
-7.94
< 0.0001
-1.43
< 0.0001
-6.66
< 0.0001
2
3
1
-4.98
< 0.0001
-4.98
< 0.0001
-4.98
< 0.0001
-4.79
< 0.0001
-0.87
< 0.0001
-3.97
< 0.0001
X42
1
-5.05
< 0.0001
-5.06
< 0.0001
-5.05
< 0.0001
-5.15
< 0.0001
-0.89
< 0.0001
-4.34
< 0.0001
X
R2
Adj-R
0.988
0.988
0.988
0.988
0.988
0.990
2
0.976
0.976
0.976
0.976
0.975
0.979
2
0.940
Pre-R
0.932
0.932
0.932
0.930
0.929
CV / %
3.24
6.66
2.75
8.33
2.32
7.73
Adeq.
Pre.
31.25
31.09
31.24
29.44
31.13
31.94
WR, 83.27 for SG, 83.89 for WL, 80.78 for RR, 94.65
for SH and 80.55 for OA) and the associated lower
p-values (p < 0.0001) demonstrated the significance
of developed models and also indicated that most of
the variation in the responses could be explained
through the regression equations. The high value of
R2 (0.9882 for WR, 0.9881 for SG, 0.9882 for WL,
0.9878 for RR, 0.9875 for SH and 0.9867 for OA) and
adj-R2 (0.9765 for WR, 0.9763 for SG, 0.9764 for WL,
0.9755 for RR, 0.9791 for SH and 0.9755 for OA)
clearly demonstrated that the form of the model
chosen to represent the actual relationship between
the response and independent variables is well correlated and accurate. Low values of coefficient of variance (3.24 for WR, 6.66 for SG, 2.75 for WL, 8.33 for
RR, 7.73 for SH and 2.32 for OA) exhibited the high
degree of precision and good reliability of the conducted experiments. In this study, the adequate precision (signal to noise ratio) was found to be > 29 for
all the responses, which indicated the best fitness of
the developed models.
Diagnostics of model adequacy
Generally, it is important to confirm that the fitted
model gives a sufficient approximation to the actual
values. Unless the model shows a satisfactory fit, proceeding with an investigation and optimization of the
552
fitted response surface likely gives poor or misleading
results. In addition to determination coefficient, the
adequacy of the models was also evaluated by the
residuals (difference between the observed and the
predicted response value) and the influence plots for
the experimental data obtained from this study. Diagnostic plots such as predicted versus actual (Figure 1)
help us to evaluate the model suitability and find out
the relationship between predicted and experimental
values. The data points on this plot lie reasonably
close to the straight line and indicated that an adequate agreement between real data and the data
obtained from the models. Hence, trends observed in
Figure 1 revealed that no obvious patterns were found
and residuals appeared to be randomly scattered.
Effect of process variables
To understand the interaction between the independent variables and dependent variables, three
dimensional (3D) response surface plots were plotted
from the developed model. In this study, the model
has more than two factors. Hence, the 3D plots were
drawn by maintaining two factors at constant level (in
turn at its central level), whereas the other two factors
were varied in their range in order to understand their
main and interactive effects on the dependent vari-
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Figure 1. Model adequacy plots (experimental vs. predicted) for responses (WR: weight reduction, SG: solid gain, WL: water loss,
RR: rehydration ratio, SH: shrinkage, OA: overall acceptability).
ables. The model was also used to locate the optimum conditions.
Mass transfer properties
At the beginning of the process, due to high
osmotic driving force between the concentrated sol-
ution and the fresh sample, the rate of water removal
and solid gain was relatively high. The osmosis effect
increased with the increasing sugar concentration
from 30-45 °Brix (Figure 2a-b). Increase in solution
concentration up to 45 °Brix resulted in an increase in
the osmotic pressure gradients and hence, higher
553
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Figure 2. Response surface plots for different mass transfer parameters (WL: water loss, WR: weight reduction, SG: solid gain) during
osmotic dehydration of amla cubes.
water loss (and solid uptake) values throughout the
osmosis period were obtained. When the osmotic solution concentration was increased, water loss and
solid gain took place in parallel mode; the rate of
water loss is always higher than the solid gain. In
osmotic dehydration, the concentration gradient
between the intracellular fluid and osmotic solution
create a difference of osmotic pressure, which leads
554
to diffusion of water and solid molecules through the
semi-permeable membrane of this fruit to achieve
osmotic equilibrium. Thus, the increase in solute concentration led to increases in SG and WL. Further increase of sugar concentration reduced the water loss
that might have led to sugar gain by the fruits, which
was not desirable [24]. This is attributed to the diffusion of water from dilute medium to concentrated
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
solution (hypertonic solution) through a semi-permeable membrane until the concentration equilibrium
was reached. The driving force in this process is the
water activity gradient caused due to the osmotic
pressure. For solute concentrations of above 50 ºBrix
and below 30 °Brix, there was impregnation and crystallization of sugar and poor moisture removal respectively. This strongly suggested that for optimal
osmotic dehydration, the sugar concentrations should
be in the range of 40-50 °Brix.
High temperatures combined with high concentration of osmotic solution were shown to facilitate
osmotic dehydration. Increase in temperature (up to
45 °C) led to more water loss than solid gain, which
caused an increase in the weight reduction. This
phenomenon is attributed to the diffusion difference
between water and solutes as related to their molar
masses [25-28]. Further increase in temperature
affects the semi-permeability of the cell walls and
reduces the rate of osmosis. This may be due to reduction in viscosity of hypertonic solution and increase
in diffusion coefficient of water increased at high temperature [29,30].
Osmotic treatment time is one of the most influential variables during osmotic dehydration of fruits,
which is due to the fact that the WL, WR and SG were
based on the time. From the results, it was observed
that increasing time (0 to 135 min) resulted in an initial increase of the WL, WR (Figure 2c-d) and SG
(Figure 2e-f), followed by a decrease. This can be
explained by the ionization characteristics and low
molecular weight of sugar that allow it to diffuse easily
into the product and increase the driving force for
dehydration. On the other hand, SG increased in the
early stages, remained almost constant for a short
period of time and finally showed a decreasing trend.
This declining trend in SG at the end of the process
could be attributed to the loss of some original solids
in amla due to the osmotic driving force between the
amla and the surrounding sugar solution [31]. But in
this study, osmotic dehydration time did not statistically have a significant effect of the process (p <
< 0.05, Table 3).
Increasing the volume of osmotic media increases the mass transfer rate. More solution volume
could increase the rate of water loss and solid gain
but it has some adverse effects also. Increasing the
volume of solution causes an increase in operating
costs. At the same time, solid gain is increased and
the overall mass transfer could lower the product quality by altering the taste of the product due to more
migration of natural substances to the osmotic media.
Therefore, the weight ratio of solution to sample
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
should be optimized. From the results, it was observed that, increasing sample to solution ratio from
1:5 to 1:13 caused a major increase of WL, WR and
SG which is due to an appreciable degree of dehydration achieved by the contact of the fruit pieces with
sufficient level of osmotic syrup to prevent dilution
and resulted in steady water-solute transfer. Beyond
1:13 ratio, mass transfer properties of amla during
osmotic dehydration had decreased and increased
the operational cost of the process. This result is compliance with other researchers’ observations [32-34].
Quality characteristics
Rehydration ratio
The effect of osmotic dehydration on rehydration
ratio increased linearly with the increase of the process variables (Figure 3a and b) up to sugar concentration of 45 °Brix, process time of 120 min, solution
temperature of 45 °C and FL ratio of 1:12. This is due
to the fact that the rehydration ratio is inversely related to the solute gain during osmotic dehydration
process, which has to be leached out during rehydration process.
Shrinkage
The magnitude of the effect of process variables
is shown in Figure 3c and d, indicating a linear decrease in shrinkage with increase of osmotic solution
temperature and concentration at 180 min of process
duration. All the process parameters (except osmotic
time and interaction of solution concentration and
osmotic time) showed significant effect on the shrinkage of amla cubes statistically based on the p-value
(Table 3). The increase in shrinkage with increase in
temperature is that higher temperatures seem to promote faster water loss through swelling and plasticizing of cell membranes as well as the better water
transfer characteristics on the product surface due to
lower viscosity of the osmotic medium [35]. The rapid
loss of water, especially in the beginning of OD, and
the temperature of the osmotic solution account for a
great proportion of shrinkage. Beyond that, decrease
in shrinkage of the product with the advancement of
process duration was observed, which may be due to
the attainment of the saturated conditions. The solid
gain, even in small amounts, can reinforce the
strength of the solid material, creating more resistance to water removal and reduced shrinkage of the
material.
Overall acceptability
Overall acceptability is useful to select the best
quality of osmotically dehydrated product with maximum consumer perception. The sensory attributes
555
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Figure 3. Response surface plots for different quality parameters (RR: rehydration ratio, SH: shrinkage, OA: overall acceptability) during
osmotic dehydration of amla cubes in sugar solution.
are affected by different process variables and the
results are shown in Figure 3. All the process parameters (except osmotic time and interaction of solution concentration and osmotic time) showed significant effect on the overall acceptability of amla
cubes statistically based on the p-value (Table 3).
The maximum acceptance was noticed for the product osmotically dehydrated under process condition
556
of temperature of 45 °C, concentration of 46 °Brix, FL
ratio of 1:11.5 g/ml and time of 120 min. The overall
acceptability is achieved due to the prevention of
enzymatic and oxidative browning as the fruit pieces
were surrounded by sugar and making it possible to
retain good consumer observation. Similar results
were observed in the osmotic dehydration of sweet
anola flakes [36].
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Optimization and validation of the optimized
conditions
The second-order polynomial models obtained
in this study were utilized for each response in order
to determine the specified optimum conditions. These
regression models are valid only in the selected experimental domain. Therefore, the operating region was
determined considering some economical, industrial
and product quality-related constraints. In this study,
sucrose concentration, FL ratio and immersion temperature were selected in the range of 30-50 °Brix,
1:5-1:15 g/ml and 30-50 °C. Considering the costs
involved to increase the process time and also immersion time (X4) was not statistically significant for all
responses in ANOVA table, the immersion time was
fixed at 30 min. By applying the desired function
methodology, the following optimized conditions were
obtained: solution concentration of 43 °Brix, FL ratio
of 1:10 g/ml, temperature of 30 °C and time of 30 min.
At this optimum point, WR, SG, WL, RR, SH and OA
found to be 27.5, 12.32, 32.68, 9.2, 7.3 and 7.16%,
respectively.
Microstructure
The microstructural changes during osmotic
dehydration are important in order to understand the
changes that occurred in the compositional changes
of fruits. Images of transversal cross-sections of
treated and untreated samples are presented in
Figure 4. Figure 4a shows the control sample of amla
tissue, which did not receive any treatment other than
the preparation for SEM. The bright regions in the
micrograph are mainly the cytoplasmic membrane
and the cell walls. The cells appeared torn and irregular in shape, with the presence of many empty
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
regions (regions which were not occupied by cells,
Figure 4a).
Figure 4b shows that osmotic dehydration process (at optimal condition) changes the tissue structure compared to the untreated sample. In fact, the
cells appeared shrunk and distorted and their contour
appeared irregular and wrinkling. This fact was probably due to the solubilization of polysaccharides
(cellulose, hemicellulose and pectin) that compose
the cells walls, the water loss and the pre-concentration of sucrose on the surface of the tissue during
the process [26,37-39]. Moreover, water loss induces
the plasmolysis of cells and solid gain gives consistency to the tissues. There are several experimental
findings in the literature that are consistent with our
claims regarding the occurrence of cell structure
modification during osmotic processing [38-40].
CONCLUSION
Box-Behnken response surface design was successfully employed in this study to evaluate and
identify the optimal osmotic condition in order to prepare osmotically dehydrated amla cubes using sugar
solution as an osmotic agent. From the experimental
results, second order polynomial models were developed for the responses (water loss, solid gain, weight
reduction, rehydration ratio, shrinkage and overall
acceptability). The results exhibited that osmotic solution concentration, FL ratio and temperature have
significant effects on the osmotic dehydration process
of amla. The optimal conditions were found to be:
sugar concentration of 50 °Brix, solution temperature
of 30 °C, fruit to liquid ratio of 1:5 g/ml, and immersion
time of 133 min.
Figure 4. SEM images of amla cubes a) raw and b) osmotically treated sample at optimal condition (sugar concentration of 50 °Brix,
solution temperature of 30 °C, fruit to liquid ratio of 1:5 g/ml and immersion time of 133 min).
557
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
Nomenclature
[18]
G. Mazza, Int. J. Food Sci. Technol. 18 (1983) 113–123
WR - Weight reduction
WL - Water loss
SG - Solid gain
RR - Rehydration ratio
SH - Shrinkage
OA - Overall acceptability
RSM - Response surface methodology
BBD – Box–Behnken design
°Brix – Degree Brix
ANOVA - Analysis of variance
SEM - Scanning electron microscopy
FL ratio - Fruit to liquid ratio
[19]
J.E. Lozano, E. Rotstein, M.J. Urbicain, J. Food Sci. 45
(1980) 1403-1407
[20]
A.V.A. Resurreccion, Quantitative of quality attributes as
perceived by the consumer. In Consumer sensory testing
for product development, Aspen Publishers, New York,
1998
[21]
J.P. Maran, V. Sivakumar, K. Thirugnanasambandham,
R. Sridhar, J. Food Sci. Technol. 52 (2014) 3617-3626
[22]
J. Prakash Maran, V. Sivakumar, R. Sridhar, V.P. Immanuel, Ind. Crop. Prod. 42 (2013) 159-168
[23]
J.P. Maran, B. Priya, S. Manikandan, J. Food Sci. Technol. 51 (2014) 1938-1946
[24]
M.S. Rahman, J. Lamb, J. Food Sci. Technol. 27 (1990)
150-152
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th
D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC…
D.TIROUTCHELVAME1
V. SIVAKUMAR2
J. PRAKASH MARAN3
Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)
KINETIKA PRENOSA MASE U OSMOTSKOJ
DEHIDRATACIJI KOCKI INDIJSKOG OGROZDA
(Emblica officinalis L.) U RASTVORU ŠEĆERA
1
Department of Food Processing and
Engineering, Karunya University,
Coimbatore, Tamil Nadu, India
2
Department of Chemical Engineering,
AC Tech Campus, Anna University,
Chennai, Tamil Nadu, India
3
Department of Food Technology,
Kongu Engineering College,
Perundurai, Erode, Tamil Nadu, India
NAUČNI RAD
Box-Behnken dizajn sa četiri faktora na tri nivo je korišćen za optimizacije uticaja
različitih procesnih faktora (osmotska koncentracija, odnos voća i tečnosti, temperature i
vreme dehidratacije) na karakteristike prenosa mase kao što su smanjenje mase, količina rastvorka, gubitak vode, redehidratacioni odnos, smanjenje i ukupna asceptibilnost
osmotski dehidratisanih kocki ogrozda. Kocke jednake veličine (10 mm×10 mm×10 mm)
su potapane u šećerni rastvor različite koncentracije (30–50 °Brix) određeno vreme (30–180 min) na različitim temperaturama (30-50 °C) i pri različitim odnosima voće-tečnost
(1:5-1:15 g/ml). Rezultati pokazuju da procesni faktori imaju značajni uticaj na osmotsku
dehidrataciju. Definisani su sledeći optimalni uslovi: koncentracija šećera od 50 °Brix,
temperature rastvora 30 °C, odnos voće-tečnost 1:5 g/ml i vreme potapanja od 133 min.
Praćene su takođe mikrokristalne promene za vreme osmotske dehidratacije korišćenjem SEM metode.
Ključne reči: indijski ogrozd, osmotska dehidratacija, metodologija površine
odziva, mikrostruktura.
559
Journal of the
Association of Chemical Engineers of
Serbia, Belgrade, Serbia
CI&CEQ
Vol. 21
Contents: Issues 1–4
No. 1/I
Željka Kesić, Ivana Lukić, Miodrag Zdujić, Čedomir Jovalekić, Hui Liu, Dejan Skala, Mechanochemical synthesis
.
of CaO·ZnO K2CO3 catalyst: Characterization and
activity for methanolysis of sunflower oil ............................. 1
Sabina Kramar, Vilma Ducman, Mechanical and microstructural characterization of geopolymer synthesized from
low calcium fly ash............................................................. 13
Odivan Zanella, Isabel Cristina Tessaro, Liliana Amaral
Féris, Nitrate sorption on activated carbon modified with
CaCl2: Equilibrium, isotherms and kinetics ........................ 23
N.M. Nikačević, L. Thielen, A. Twerda, P.M.J. Van den Hof,
CFD analysis and flow model reduction for surfactant
production in Helix reactor ................................................. 35
Linfeng Zhang, Jun Ji, Yuanxin Wu, Oxidative carbonylation
of phenol to diphenyl carbonate by Pd/MFe2O4
magnetic catalyst ............................................................... 45
Vesna T. Tumbas Šaponjac, Gordana S. Ćetković, Slađana
M. Stajčić, Jelena J. Vulić, Jasna M. ČanadanovićBrunet, Sonja M. Djilas, Optimization of the bioactive
compounds content in raspberry during freeze-drying
using response surface method ........................................ 53
Milovan Janićijević, Milesa Srećković, Branka Kaluđerović,
Mirko Dinulović, Zoran Karastojković, Predrag Jovanić,
Zorica Kovačević, Evaluation of laser beam interaction
with carbon based material – glassy carbon ...................... 63
Đorđe B. Psodorov, Marijana M. Ačanski, Đura N. Vujić,
Jovana S. Brkljača, Dragan Đ. Psodorov, Homogeneity
of oil and sugar components of flour amaranth
investigated by GC-MS...................................................... 71
R. Teflanab, S.M. Ghoreishi, J. Safdari, M. Torab-Mostaedi,
Axial dispersion model in predictive mass transfer
correlation for random pulsed packed column................... 77
Young Ho Kim, Dong Won Lee, Eun Ji Jung, Jun Tae Bae,
Sang Gil Lee, Hyeong Bae Pyo, Kuk Hyoun Kang, Dong
Kyu Lee, Preparation and characterization of quercetinloaded silica microspheres stabilized by combined
multiple emulsion and sol-gel processes ........................... 85
M. García-Dopico, A. García, Modelling fluidized catalytic
cracking unit stripper efficiency ......................................... 95
Motasem N. Saidan, Improvement of linerboard compressive strength by hot-pressing and addition of
recovered lignin from spent pulping liquor ....................... 107
Laishun Shi, Meijie Sun, Na Li, Bochen Zhang, A novel betaine type asphalt emulsifier synthesized and investigated by online FTIR spectrophotometric method ......... 113
Qinghong You, Xiulian Yin, Hong Xu, Enhanced compoundenzymes--assisted extraction of polysaccharides from
Cornus officinalis ............................................................. 123
YEAR 2015
Violeta D. Jakovljević, Jelica D. Stojanović, Miroslav M.
Vrvić, The Potential application of fungus Trichoderma
harzianum Rifai in biodegradation of detergent
and industry ..................................................................... 131
No. 1/II
Ivana Jokić, Zoran Djurić, Katarina Radulović, Miloš Frantlović, Fluctuations of the number of adsorbed micro/
/nanoparticles in sensors for measurement of particle
concentration in air and liquid environments ................... 141
Renata Kovačević, Viša Tasić, Marija Živković, Nenad Živković, Amelija Đorđević, Dragan Manojlović, Milena
Jovašević-Stojanović, Mass concentrations and indooroutdoor relationships of PM in selected educational
buildings in Niš, Serbia .................................................... 149
Marija Živković, Milena Jovašević-Stojanović, Anka Cvetković, Ivan Lazović, Viša Tasić, Žana Stevanović, Ivan
Gržetić, PAHs levels in gas and particle-bound phase in
schools at different locations in Serbia ............................ 159
I. Deljanin, D. Antanasijević, M. Aničić Urošević, M. Tomašević, Z. Sekulić, A. Perić-Grujić, M. Ristić, Selected
trace element concentrations in ambient air and in
horse chestnut leaves in Belgrade .................................. 169
Ivan Lazović, Milena Jovašević-Stojanović, Marija Živković,
Viša Tasić, Žarko Stevanović, PM and CO2 variability
and relationship in different school environments ........... 179
Z. Gršić, S. Pavlović, D. Arbutina, S. Dramlić, D. Dramlić, D.
Nikezić, S. Dimović, J. Kaljević, M. Milinčić, Environmental impact assessment of the nuclear reactor in
Vinča, based on the data on emission of radioactivity
from the literature – A modeling approach ....................... 189
F. Hedayat, S. Stevanovic, B. Miljevic, S. Bottle, Z.D. Ristovski, Review – evaluating the molecular assays for
measuring the oxidative potential of particulate matter ... 201
A. Cvetković, M. Jovašević-Stojanović, S. Matić-Besarabić,
D.A. Marković, A.Bartoňová, Comparison of sources of
urban ambient particle bound PAHs between nonheating seasons 2009 and 2012 in Belgrade, Serbia ...... 211
N. Castell, C. Guerreiro, B.R. Denby, A. González Ortiz,
The role of air quality modelling in particulate matter
management in cities. results from the air implementation pilot ................................................................. 221
No. 2
Nazila Samimi Tehrani, Ghasem D. Najafpour, Mostafa
Rahimnejad, Hossein Attar, Performance of upflow
anaerobic sludge fixed film bioreactor for the treatment
561
CI&CEQ
Vol. 21
Contents: issues 1–4
of high organic load and biogas production of cheese
whey wastewater ............................................................. 229
YEAR 2015
No. 3
Seyed Majid Ataei Ardestani, Morteza Sadeghi, Babak Beheshti, Saeid Minaei, Naser Hamdami, Vibro-fluidized
bed heat pump drying of mint leaves with respect to
phenolic content, antioxidant activity and color indices ... 239
Nenad D. Nikolić, Đorđe P. Medarević, Jelena D. Đuriš,
Dragana D. Vasiljević, Comparison of drug release and
mechanical properties of tramadol hydrochloride matrix
tablets prepared with selected hydrophilic polymers ....... 369
Marija S. Petrović, Tatjana D. Šoštarić, Lato L. Pezo, Slavka
M. Stanković, Časlav M. Lačnjevac, Jelena V. Milojković, Mirjana D. Stojanović, Usefulness of ANN-based
model for copper removal from aqueous solutions using
agro industrial waste materials ........................................ 249
Saeid Shokri, Mohammad Taghi Sadeghi, Mahdi Ahmadi
Marvast, Shankar Narasimhan, Saeid Minaei, Naser
Hamdami, Integrating principal component analysis and
vector quantization with support vector regression for
sulfur content prediction in hydrodesulfurization
process ............................................................................ 379
Bore V. Jegdić, Biljana M. Bobić, Miloš K. Pavlović, Ana B.
Alil, Slaviša S. Putić, Stress corrosion cracking resistance of aluminum alloy 7000 series after two-step
aging ................................................................................ 261
Aleksandra Petrovič, Marjana Simonič, The efficiency of a
membrane bioreactor in drinking water denitrification ..... 269
Dragutin M. Nedeljković, Marija P. Stevanović, Mirko Z.
Stijepović, Aleksandar P. Stajčić, Aleksandar S. Grujić,
Jasna T. Stajić-Trošić, Jasmina S. Stevanović, The possibility of application of zeolyte powders for the
construction of membranes for carbon dioxide separation ................................................................................. 277
Mile Veljovic, Sasa Despotovic, Milan Stojanovic, Sonja
Pecic, Predrag Vukosavljevic, Miona Belovic, Ida Leskosek-Cukalovic, The fermentation kinetics and physicochemical properties of special beer with addition of
Prokupac grape variety .................................................... 391
Najmi Ahmed Essawet, Dragoljub Cvetković, Aleksandra
Velićanski, Jasna Čanadanović-Brunet, Jelena Vulić,
Vuk Maksimović, Siniša Markov, Polyphenols and antioxidant activities of Kombucha beverage enriched with
®
Coffeeberry extract ........................................................ 399
Veselinka Grudić, Jelena Šćepanović, Ivana Bošković,
Removal of cadmium (II) from aqueous solution using
fermented grape marc as a new adsorbent ..................... 285
Nataša S. Tomović, Kata T. Trifković, Marko P. Rakin,
Marica B. Rakin, Branko M. Bugarski, Influence of compression speed and deformation percentage on
mechanical properties of calcium alginate particles ........ 411
Amal Juma Habish, Slavica Lazarević, Ivona Janković-Častvan, Branislav Potkonjak, Đorđe Janaćković, Rada Petrović, The effect of salinity on the sorption of cadmium
ions from aqueous medium on Fe(III)-sepiolite ............... 295
Radojica Pešić, Tatjana Kaluđerović Radoičić, Nevenka
Bošković-Vragolović,
Zorana
Arsenijević,
Željko
Grbavčić, Pressure drop in packed beds of spherical
particles at ambient and elevated air temperatures......... 419
Shaopeng Guo, Lina Lv, Jia Zhang, Xin Chen, Ming Tong,
Wanzhong Kang, Yanbo Zhou, Jun Lu, Simultaneous
removal of SO2 and NOx with ammonia combined with
gas-phase oxidation of NO using ozone.......................... 305
Marija A. Ilić, Franz-Hubert Haegel, Vesna M. Pavelkić,
Snezana J. Zlatanović, Zoran S. Marković, Aleksandar
S. Cvjetić, Unusually sluggish microemulsion system
with water, toluene and a technical branched alkyl polyethoxylate ........................................................................ 429
Jau-Kai Wang, Jir-Ming Char, Optimization study on hardness of gold film through supercritical electroplating
process by response surface methodology ..................... 311
Lawrence Koech, Ray Everson, Hein Neomagus, Hilary
Rutto, Dissolution kinetics of south african coal fly ash
and the development of a semi-empirical model to
predict dissolution ............................................................ 319
Zhuoni Hou, Xianrui Liang, Feng Su, Weike Su, Preparative
isolation and purification of seven compounds from
Hibiscus mutabilis L. leaves by two-step high-speed
counter-current chromatography ..................................... 331
Ruifang Zhao, Yulong Wang, Yonghui Bai, Yongfei Zuo,
Lunjing Yan, Fan Li, Effects of fluxing agents on gasification reactivity and gas composition of high ash
fusion temperature coal ................................................... 343
Veselinka V. Grudić, Nada Z. Blagojević, Vesna L. Vukašinović-Pešić, Snežana R. Brašanac, Kinetics of degradation of ascorbic acid by cyclic voltammetry method....... 351
Ahmet Ozan Gezerman, Burcu Didem Çorbacıoğlu, Effects
of sodium silicate, calcium carbonate and silicic acid on
ammonium nitrate degradation and analytical investigations of the degradation process on an industrial
scale ................................................................................ 359
Shifeng Li, Yanming Shen, Dongbing Liu, Lihui Fan, Zhe
Tan, Zhigang Zhang, Wenxiu Li, Wenpeng Li, Experimental study of concentration of tomato juice by CO2
hydrate formation............................................................. 441
Aleksandar R. Mladenović, Milka B. Jadranin, Aleksandar
D. Pavlović, Slobodan D. Petrović, Saša Ž. Drmanić,
Milka L. Avramov Ivić, Dušan Ž. Mijin, Liquid chromatography and liquid chromatography-mass spectrometry
analysis of donepezil degradation products .................... 447
Jiajia Dai, Benfang H. Ruan, Ying Zhu, Xianrui Liang, Feng
Su, Weike Su, Preparation of nanosized fluticasone
propionate nasal spray with improved stability and
uniformity ......................................................................... 457
No. 4
Jun Tan, Xiaoyan Wei, Yuxia Ouyang, Rui Liu, Ping Sun,
Juhong Fan, Evaluation of insoluble xanthate and
crosslinked
starch-graft-polyacrylamide-co-sodium
xanthate for the adsorption of Cu(II) in aqueous
solutions .......................................................................... 465
Ogbemudia Joseph Ogbebor, Felix Ebhodaghe Okieimen,
David Ehioghilen Ogbeifun, Uzoma Ndubuisi Okwu,
Organomodified kaolin as filler for natural rubber............ 477
Vesna M. Pavelkić, Tanja P. Brdarić, Marija P. Petrović,
Gavrilo M. Šekularac, Milica G. Košević, Lato L. Pezo,
562
CI&CEQ
Vol. 21
Content: issues 1–4
Marija A. Ilić, Application of Peleg model on mass
transfer kinetics during osmotic dehydratation of pear
cubes in sucrose solution ................................................ 485
Rongyan Shen, Fang Liu, Te Li, Xia Xu, Yuting Liang, Xingqing Zhao, Wenyi Zhang, Treatment of 2-diazo-4,6-dinitrophenol wastewater using TiO2/SiO2 composite
film in a photocatalytic reactor ......................................... 493
Milutin M. Milosavljević, Ivan M. Vukićević, Veis Šerifi, Jasmina S. Markovski, Ivana Stojiljković, Dušan Ž. Mijin,
Aleksandar D. Marinković, Optimization of the synthesis
of N-alkyl and N,N-dialkyl thioureas from waste water
containing ammonium thiocyanate .................................. 501
Sheng Fang, Li-Ping Wang, Ting Wu, Mathematical modeling and effect of blanching pretreatment on the drying
kinetics of Chinese Yam (Dioscorea opposita) ................ 511
YEAR 2015
Zorana Arsenijević, Tatjana Kaluđerović Radoičić, Mihal
Đuriš, Željko Grbavčić, Experimental investigation of
heat transfer in three-phase fluidized bed cooling
column ............................................................................. 519
Vesna S. Cvetković, Luka J. Bjelica, Nataša M. Vukićević,
Jovan N. Jovićević, Alloy formation by Mg underpotential deposition on Al from nitrate melts.................... 527
Rajamohan Natarajan, Jamila Al-Sinani, Saravanan Viswanathan, Performance evaluation and kinetic studies on
removal of benzene in up-flow tree bark based biofilter .. 537
D. Tiroutchelvame, V. Sivakumar, J. Prakash Maran, Mass
transfer kinetics during osmotic dehydration of Amla
(Emblica officinalis L.) cubes in sugar solution ................ 547
Contents: Vol. 21, Issues 1–4, 2015 ....................................... 561
Author Index, Vol. 21, 2015.................................................... 565
563
Journal of the
Association of Chemical Engineers,
Belgrade, Serbia
CI&CEQ
Vol. 21
Author Index
A
Ć
Ačanski M. Marijana (1/I) 71
Al-Sinani Jamila (4) 537
Alil B. Ana (2) 261
Amal Juma Habish (2) 295
Aničić Urošević M. (1/II) 169
Antanasijević D. (1/II) 169
Arbutina D. (1/II) 189
Arsenijević Zorana (3) 419, (4) 519
Avramov Ivić L. Milka (3) 447
Ćetković S. Gordana (1/I) 53
B
Babak Beheshti (2) 239
Bartonova A. (1/II) 211
Belović Miona (3) 391
Benfang H. Ruan (3) 457
Bjelica J. Luka (4) 527
Blagojević Z. Nada (2) 351
Bobić M. Biljana (2) 261
Bošković Ivana (2) 285
Bošković-Vragolović Nevenka (3) 419
Bottle S. (1/II) 201
Brašanac R. Snežana (2) 351
Brdarić P. Tanja (4) 485
Brkljača S. Jovana (1/I) 71
Bugarski M. Branko (3) 411
YEAR 2015
Č
Čanadanović-Brunet M. Jasna (1/I) 53; (3) 399
D
Dai Jiajia (3) 457
Deljanin I. (1/II) 169
Denby B.R. (1/II) 221
Despotović Saša (3) 391
Dimović S. (1/II) 189
Dinulović Mirko (1/I) 63
Dramlić D. (1/II) 189
Dramliić S. (1/II) 189
Drmanić Ž. Saša (3) 447
Ducman Vilma (1/I) 13
Dj
Djilas M. Sonja (1/I) 53
Djordjević Amelija (1/II) 149
Djurić Zoran (1/II) 141
Djuriš D. Jelena (3) 369
Djuriš Mihal (4) 519
C
F
Castell N. (1/II) 221
Char Jir-Ming (2) 311
Corbacioglu Didem Burcu (2) 359
Cvetković Anka (1/II) 159, 211
Cvetković Dragoljub (3) 399
Cvetković S. Vesna (4) 527
Cvjetić S. Aleksandar (3) 429
Feng Su (2) 331; (3) 457
Feris Amaral Liliana (1/I) 23
Frantlović Miloš (1/II) 141
G
Garcia A. (1/I) 95
Garcia-Dopico M. (1/I) 95
565
CI&CEQ
Vol. 21
Gezerman Ahmet Ozan (2) 359
Ghasem D. Najafpour (2) 229
Ghoreishi S.M. (1/I) 77
Gonzalez Ortiz A. (1/II) 221
Grbavčić Željko (3) 419, (4) 519
Gršić Z. (1/II) 189
Grudić V. Veselinka (2) 285, 351
Grujić S. Aleksandar (2) 277
Gržetić Ivan (1/II) 159
Guerreiro C. (1/II) 221
Guo Shaopeng (2) 305
H
Haegel Franz-Hubert (3) 429
Hedayat F. (1/II) 201
Hein Neomagus (2) 319
Hong Xu (1/I) 123
Hossein Attar (2) 229
Hui Liu (1/I) 1
Hyeong Bae Pyo (1/I) 85
I
Ilić A. Marija (3) 429; (4) 485
J
Jadranin B. Milka (3) 447
Jakovljević D. Violeta (1/I) 131
Janaćković Djordje (2) 295
Janićijević Milovan (1/I) 63
Janković-Častvan Ivona (2) 295
Jegdić V. Bore (2) 261
Jokić Ivana (1/II) 141
Jovalekić Čedomir (1/I) 1
Jovanić Predrag (1/I) 63
Jovašević-Stojanović Milena (1/II) 149, 159,
179, 211
Jovićević N. Jovan (4) 527
Juhong Fan (4) 465
Jun Ji (1/I) 45
Jun Lu (2) 305
Jun Tae Bae (1/I) 85
Jun Tan (4) 465
566
Author Index
YEAR 2015
Jung Ji Eun (1/I) 85
K
Kaljević J. (1/II) 189
Kaludjerović Branka (1/I) 63
Kaludjerović Radoičić Tatjana (3) 419, (4) 519
Kang Wanzhong (2) 305
Karastojković Zoran (1/I) 63
Kesić Željka (1/I) 1
Koech Lawrence (2) 319
Košević G. Milica (4) 485
Kovačević Renata (1/II) 149
Kovačević Zorica (1/I) 63
Kramar Sabina (1/I) 13
Kuk Hyoun Kang (1/I) 85
L
L.Thielen (1/I) 35
Lačnjevac M. Časlav (2) 249
Lazarević Slavica (2) 295
Lazović Ivan (1/II) 159, 179
Lee Kyu Dong (1/I) 85
Dong Won Lee (1/I) 85
Leskošek-Čukalović Ida (3) 391
Li Fan (2) 343
Li Shifeng (3) 441
Li Wenpeng (3) 441
Li Wenxiu (3) 441
Liu Fang (4) 493
Liu Dongbing (3) 441
Lihui Fan (3) 441
Lukić Ivana (1/I) 1
Lv Lina (2) 305
M
Mahdi Ahmadi Marvast (3) 379
Maksimović Vuk (3) 399
Manojlović Dragan (1/II) 149
Maran Prakash J. (4) 547
Marinković D. Aleksandar (4) 501
Markov Siniša (3) 399
Marković A.D. (1/II) 211
CI&CEQ
Vol. 21
Marković S. Zoran (3) 429
Markovski S. Jasmina (4) 501
Matić-Besarabić S. (1/II) 211
Medarević P. Djordje (3) 369
Meijie Sun (1/I) 113
Mijin Ž. Dušan (3) 447, (4) 501
Milinčić M. (1/II) 189
Miljević B. (1/II) 201
Milojković V. Jelena (2) 249
Milosavljević M. Milutin (4) 501
Ming Tong (2) 305
Mladenović R. Aleksandar (3) 447
Mohammad Taghi Sadeghi (3) 379
Morteza Sadeghi (2) 239
Mostafa Rahimnejad (2) 229
Motasem N. Saidan (1/I) 107
N
Na Li (1/I) 113
Najmi Ahmed Essawet (3) 399
Naser Hamdami (2) 239; (3) 379
Nazila Samimi Tehrani (2) 229
Nedeljković M. Dragutin (2) 277
Nikačević M. Nikola (1/I) 35
Nikezić D. (1/II) 189
Nikolić D. Nenad (3) 369
O
Odivan Zanella (1/I) 23
Ogbebor Joseph Ogbemudia (4) 477
Ogbeifun Ehioghilen David (4) 477
Okieimen Ebhodaghe Felix (4) 477
Okwu Ndubuisi Uzoma (4) 477
P
Pavelkić M. Vesna (3) 429; (4) 485
Pavlović D. Aleksandar (3) 447
Pavlović K. Miloš (2) 261
Pavlović S. (1/II) 189
Pecić Sonja (3) 391
Perić-Grujić A. (1/II) 169
Pešić Radojica (3) 419
Petrovič Aleksandra (2) 269
Author Index
YEAR 2015
Petrović D. Slobodan (3) 447
Petrović P. Marija (4) 485
Petrović Rada (2) 295
Petrović S. Marija (2) 249
Pezo L. Lato (2) 249; (4) 485
Ping Sun (4) 465
Potkonjak Branislav (2) 295
Psodorov B. Djordje (1/I) 71
Psodorov Dj. Dragan (1/I) 71
Putić S. Slaviša (2) 261
R
Radulović Katarina (1/II) 141
Rajamohan Natarajan (4) 537
Rakin B. Marica (3) 411
Rakin P. Marko (3) 411
Ray Everson (2) 319
Ristić M. (1/II) 169
Ristovski D.Z. (1/II) 201
Rongyan Shen (4) 493
Rui Liu (4) 465
Rutto Hilary (2) 319
S
Saeid Minaei (2) 239; (3) 379
Saeid Shokri (3) 379
Safdari J. (1/I) 77
Sang Gil Lee (1/I) 85
Saravanan Viswanathan (4) 537
Sekulić Z. (1/II) 169
Seyed Majid Ataei Ardestani (2) 239
Shankar Narasimhan (3) 379
Sheng Fang (4) 511
Shi Laishun (1/I) 113
Simonič Marjana (2) 269
Sivakumar V. (4) 547
Skala Dejan (1/I) 1
Srećković Milesa (1/I) 63
Stajčić M. Sladjana (1/I) 53
Stajčić P. Aleksandar (2) 277
Stajić-Trošić T. Jasna (2) 277
Stanković M. Slavka (2) 249
Stevanović P. Marija (2) 277
Stevanović S. (1/II) 201
567
CI&CEQ
Vol. 21
Stevanović S. Jasmina (2) 277
Stevanović Žana (1/II) 159
Stevanović Žarko (1/II) 179
Stijepović Z. Mirko (2) 277
Stojanović D. Jelica (1/I) 131
Stojanović D. Mirjana (2) 249
Stojanović Milan (3) 391
Stojiljković Ivana (4) 501
W
Š
Xia Xu (4) 493
Xianrui Liang (2) 331; (3) 457
Xin Chen (2) 305
Šćepanović Jelena (2) 285
Šekularac M. Gavrilo (4) 485
Šerifi Veis (4) 501
Šoštarić D. Tatjana (2) 249
T
Tasić Viša (1/II) 149, 159, 179
Te Li (4) 493
Teflanab R. (1/I) 77
Tessaro Cristina Isabel (1/I) 23
Ting Wu (4) 511
Tiroutchelvame D. (4) 547
Tomašević M. (1/II) 169
Tomović S. Nataša (3) 411
Torab-Mostaedi M. (1/I) 77
Trifković T. Kata (3) 411
Tumbas Šaponjac T. Vesna (1/I) 53
Twerda A. (1/I) 35
V
Van den Hof P.M.J. (1/I) 35
Vasiljević D. Dragana (3) 369
Velićanski Aleksandra (3) 399
Veljović Mile (3) 391
Vrvić M. Miroslav (1/I) 131
Vujić N. Djura (1/I) 71
Vukašinović-Pešić L. Vesna (2) 351
Vukićević M. Ivan (4) 501
Vukićević M. Nataša (4) 527
Vukosavljević Predrag (3) 391
Vulić J. Jelena (1/I) 53; (3) 399
568
Author Index
YEAR 2015
Wang Jau-Kai (2) 311
Li-Ping Wang (4) 511
Wei Xiaoyan (4) 465
Weike Su (2) 331; (3) 457
X
Y
Yanbo Zhou (2) 305
Yan Lunjing (2) 343
Yanming Shen (3) 441
Yin Xiulian (1/I) 123
Ying Zhu (3) 457
Yongfei Zuo (2) 343
Yonghui Bai (2) 343
Young Ho Kim (1/I) 85
Yuanxin Wu (1/I) 45
Yulong Wang (2) 343
Yuting Liang (4) 493
Yuxia Ouyang (4) 465
Z
Zdujić Miodrag (1/I) 1
Zhang Bochen (1/I) 113
Zhang Jia (2) 305
Zhang Linfeng (1/I) 45
Zhao Ruifang (2) 343
Zhao Xingqing (4) 493
Zhang Wenyi (4) 493
Zhe Tan (3) 441
Zhigang Zhang (3) 441
Zhuoni Hou (2) 331
Zlatanović J. Snezana (3) 429
Ž
Živković Marija (1/II) 149, 159, 179
Živković Nenad (1/II) 149