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Thermal Characterization of Clay Ceramics using Phoacoustic Technique
J. Alexandre, O.C. Gonçalves, B.C. Marques, L.H. Poley, F. Saboya, C. Salles,
M.S. Sthel, M.G. da Silva and H. Vargas
Universidade Estadual do Norte Fluminense
Centro de Ciência e Tecnologia
Av. Alberto Lamego, 2000, CCT Horto Campos dos Goytacazes, RJ, Brazil
CEP: 28015-620
mgs@uenf.br
ABSTRACT
In this paper we discuss the usefulness of the photoacoustic techniques to
characterize the thermal properties of kaolinite clays, which is a very abundant
mineral in some regions of Brazil. The results show strong evidence that there
is a marked temperature around 950 oC above and below which there are
different behaviour patterns of the measured properties of the kaolinite clay
samples. The implications of the results in the manufacturing of clay bricks are
briefly considered. It plays an important role in tropical regions where the
knowing of the thermal properties of material used in building construction
industry are highly desired.
Keywords: Photoacoustic spectroscopy, kaolinite, structure, thermal properties.
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INTRODUCTION
During the past few years the photoacoustic (PA) and photothermal (PT)
techniques have been gradually broadly used in different branches of science,
ranging from agricultural and medical sciences to environmental sciences. For a
comprehensive review on PT wave phenomenon and their applications we refer
to books by Bicanic 1, Mandelis2, Rosencwaig
3
and Almond 4, and to review
papers by Fork and Herbert5 and Vargas and Miranda 6.
The PA effect in solids was discovered by A.G. Bell in 1880. This effect
can be detected by enclosing a specimen in an airtight cell (PA cell) and
exposing it to a chopped light beam. As a result of the periodic heating of the
specimen, the pressure in the air chamber oscillates at the chopping frequency.
The resulting PA signal depends not only on the amount of heat generated in
the specimen (i.e.; on the specimen’s optical absorption coefficient and its lightinto-heat conversion efficiency), but also on how this heat diffuses through the
specimen and is exchanged with the surrounding gas of the cell. The quantity
that measures the rate of heat diffusion in the specimen is the thermal diffusivity
, whereas the specimen thermal effusivity e, measures essentially its thermal
impedance for heat exchange. These two quantities are defined as

k
,
c p
e  kc p
(1)
where:
k = specimen thermal conductivity
 = density
cp = heat capacity at constant pressure
In this paper we were concerned about the use of PA methodologies for
investigating the thermal properties of kaolinite clay, a mineral which is very
abundant in the northern Rio de Janeiro state in Brazil. This material, which
composition is mostly Al2O32SiO22H2O, is used in the fabrication of ceramics,
for example, brick and roof tile. The performance and efficiency of such materials in
addition to many other characteristics depend critically on the thermal and physical
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properties of the building construction raw material. Besides, kaolinite is one of the
most common clay mineral found in Brazil. During the manufacturing process of the
brick, the raw material is being heated at high temperatures, and, as a consequence,
changes in the chemical and physical properties of kaolinites will occur. Therefore,
changes in the mechanical and thermal properties are expected. The mechanical
behavour of the kaolinite after being fired at high temperatures is quite well known7.
However, the thermal properties resulting from heating is still to be investigated. These
thermal properties are of extreme importance in civil engineering industries mainly in
tropical regions due to the high temperatures reached by the sun rays towards the
building walls.
EXPERIMENTAL
Sample Preparation
The preparation procedure of the clay samples adopted in this work is
described in the Reference 8.
The thermal parameters were measured using a small piece of clay,
rubbed (with sand paper) to obtain samples heaving a smooth and flat surface,
approximately 300 m thick. The heat treatment procedure adopted in this work
consists in heating the sample for a given time in a specific temperature. All the
measurements were take at room temperature.
Apparent porosity and density
The percentual apparent porosity P was calculated using the usual
relation P(%)(P0 - Ps)/(P0 – Pi)100, where P0 is the moisture sample weight,
Ps is the dry sample weight and Pi is the immerse-in-water sample weight. To
calculate the density, we used the ratio of the dry sample weight to the sample
volume.
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Thermal diffusivity measurements: the open-cell detector
As detector it was used a commercial electret microphone 9. The
experimental arrangement (Fig. 1) consisted of a 25 mW He-Ne laser whose
beam was mechanically chopped and focussed onto the sample. The sample
was mounted in such a way as to cover the opening of the microphone. The
signal from the microphone was connected to a lock-in amplifier (PAR, model
5210) used to register both signal amplitude and phase. These were recorded
as a function of modulation frequency.
lens
chopper
light
microphone
sample
signal
reference
Lock-in
amplifier
Figure 1
- Experimental
arrangement
for
the
P.A.
thermal
diffusivity
measurements.
In the thermal diffusivity measurements using the OPC detector, the
pressure fluctuation p in the air chamber, for the rear-side illumination
configuration, Fig. 4, is predicted by the thermal diffusion model10 and given by:
p 
P0 l0  g  s 
2l g T0 k s f
1
2

 
 exp jt   2 



 sinhls s 



(2)
where  is the air heat capacity ratio, P0(T0) is the ambient pressure
(temperature), I0 is the radiation intensity, f is the modulation frequency and li, ki
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and i are the length, thermal conductivity and thermal diffusivity of medium i,
respectively. Here, the subscript i denotes the absorbing sample (s) and the air
(g), respectively.  i  1  j ai , ai  f  i  is the complex thermal diffusion
12
coefficient of material i. In arriving at eqn. (2) we have assumed that the sample
is optically opaque to the incident radiation and that the heat flux into the
surrounding air is negligible. The optical opaqueness condition means that all
the radiation is
absorved at the outer sample surface. Eqn.(2) is further
simplified for thermally thick samples, namely l s a s  1 , it reduces to:
p 
P0 l 0  g  s 
l gT0 k s

1
2

 exp  l f  1 2
s
s


f



 exp j t   2  l s a s 
 


(3)
Eqn.(3) means that, for a thermally thick sample, the amplitude fo the PA signal


decreases exponentially with the modulation frequency as 1 f  exp af 1 2 ,

where a  l s2  s

12
. In this regime s can be obtained by fitting the
experimental data with the coefficient b, by using eqn.(3) in the form:
 A
S    exp bf 1 2
f


(4)
The constant A, in the measured signal S, apart from geometric factors,
includes all other factors such as the gas thermal properties, and so on. We
thus have two adjustable parameters A and b to describe the PA monitoring of
the thermal diffusivity of the sample.
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Measurements of heat capacity, cp
The heat capacity per unit of volume, cp, was measured using the
temperature rise method, under continuous white light illumination. The
experimental arrangement is shown in Fig. 2.
vacuum
holder
nylon
glass window
termocouple
light
sample
Figure 2
- Experimental
arrangement
used
for
thermal
conductivity
measurements.
The samples were sprayed on both surfaces with a very thin film with
black paint. A light-absorbing surface and the same heat-transfer coefficient
were thus assured for each side of the sample. The samples were suspended in
a Dewar flash, which an entrance glass window through which the continuous
white-light beam was focused onto one of the sample surfaces. A thermocouple
was used to monitor the temperature evolution. Since the sample thicknesses
are typically on the order of 300 m and much smaller than their widths (e.g.,
0.6 cm), the simple one-dimensional heat diffusion equation with radiation
losses could be applied to our measurements. Solving the one-dimensional
heat equation, it can be shown that the long-term time evalution (i.e., for times
greater than the heat diffusion time  l2/, where l is the sample thickness and 
the thermal diffusivity) of the back surface temperature rise is given by:
T   I 0  / lc p 1  e  t


(5)
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where I0 is the intensity of the incident light   lc p ( 2 H ) is the rise time. Here,
H  4T03 is the radiative heat-transfer coefficient, where  is the Stefan-
Boltzmann constant and T0 is the ambient temperature. The parameter  is
determined by fitting the experimental data with eqn. (6). The thermal
conductivity k is readily obtained from the previous value of , calculated by
using k  c p .
RESULTS AND DISCUSSION
In Fig. 3 we show the PA amplitude as a function of the modulated
square root of the frequency for the a) 360 m thick sample (kaolinite clay)
heated at 950° C and b) 320 m thick sample of kaolinite clay heated at 600 °
C. The solid curves in Fig. 3, represent the fitting of experimental data to eqn.
(4). The resulting values of thermal diffusivity from the data fitting was  =
27.0x10-3 cm2/s for the kaolinite clay heated to 950° C and 1.33x10 -3 cm2/s for
the sample heated at 600° C. Note that within the frequency range from 20 to
70 Hz the samples were thermally thick, i.e., their thermal diffusion lengths
(/f)1/2 were much more smaller than their thickness. The same procedure was
applied to the other samples. In Table 1, we summarize the results of the
thermal diffusivity of our samples as a function of the heated temperature. The
density and the porosity of the samples as a function of the heated temperature
are also included. In Fig. 4 we show the thermal diffusivity as a function of the
heated temperature.At higher temperature the thermal diffusivity decreases as
shown in Fig. 4. The observed decrease in  may be attributed to an increase in
the density of our sample. In Table 1 we present the density of the samples as a
function of the heated temperature. Between 500 oC and 800 oC the density
increases which entails that  should decreases providing a constant ratio k/cp.
In this case the sample becomes amorphous and heat does not flow as easily
as for the sample heated with temperature above 800 oC.
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Table 1 - Values of the porosity density and crystallinity surements as a
function of the heat treatment
Temperature
Difusivity
Porosity
Density
cp
Conductivity
(oC)
(10-3cm2/s)
(%)
(g/cm3)
(J.cm-3.K-1)
(10-3W.cm-1.K-1)
300
1.54
0.50
1.152
0.43
0.66
500
1.11
0.69
1.220
0.44
0.49
600
1.33
0.74
1.247
0.44
0.59
700
2.68
0.70
1.303
0.45
1.21
800
1.17
0.65
1.311
0.46
0.54
850
6.60
-
-
0.43
2.84
900
15.40
0.58
1.332
0.62
9.55
950
27.05
0.49
1.381
0.42
1.14
1000
4.73
0.43
1.559
0.53
2.51
1050
-
0.26
1.842
-
-
0.08
2.586
0.41
1.89
1200
4.60
0.2
Amplitude/mV
0.1
(a)
(b)
0.015
4
5
6
f
Figure 3
1/2
7
8
1/2
(Hz )
- Dependence of the PA signal amplitude as a function of the
frequency square root for a) the 360 m thick sample heated at
950 oC and b) the 320 m thick sample heated at 600 oC. The
solid curves represent the fit of the experimental data to eqn. 4.
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30
20
15
-3
2 -1
 (10 cm s )
25
10
5
0
200
400
600
800
1000
1200
o
Heated Temperature ( C)
Figure 4
- Thermal diffusivity as a function of heated temperature.
Fig. 5 shows the back surface temperature rise as a function of time,
after commencement of illumination for a sample heated with 700 oC. This figure
also shows the cooling of the back surface of the sample when the illumination
is switched off. The solid line in Fig. 5 represents the result of the best fit of the
experimental data to eqn. (5) using  as an adjustable parameter. From the
values of  we got the experimental value of the thermal capacity, cP. We
found cp = 0.45 J.cm-3K-1 for the sample heated at 700oC. The same procedure
was applied to the other samples, and the values are given in Table 1.
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Temperature (K)
320
315
310
305
300
295
0
50
100
150
Time (s)
Figure 5 -
Back surface temperature evolution for kaolinite clay samples. The
solid line represents the result of the best fit of the experimental
data to eqn. (5) using  as an adjustable parameter.
It is known that both crystalline and amorphous phases of the same
compound have nearly equal heat capacity
11.
However, in the vicinity of a
phase transition, the behaviour is different. As can be observed in Table 1, the
heat capacity of the sample at 950 oC abruptly separates from the remainder of
the cp value. This result is consistent with the well known behavior of the heat
capacity at critical points. It is an obvious example of detection of a phase
transition from measurements of heat capacity per unit of volume.
Finally, the thermal conductivity k was determined using the measured
values of thermal capacity cP and the previously determined values of the
thermal diffusivity , eqn(1). The values are shown in Table 1. We observe that
the thermal conductivity k reaches a maximum at 950 oC. The analysis of this
phenomenon is essentially the same for the  values. A large amount of heat
flows per unit of time for the sample heated at 950 oC, which is the ideal
temperature to manufacture clay bricks.
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CONCLUSION
In
conclusion
we
have
investigated
kaolinite
clays
using
the
photoacoustic technique. We note that the PA–determined thermal diffusivity
and thermal conductivity are indeed sensitive parameters for monitoring the
amorphous-crystalline solid transformation occurring during the heating of the
kaolinite clay sample. A relatively simple experimental arrangement enable us
to discriminate different samples by means of thermal diffusivities, and may
serve as a quality indicator for the product. A clay with favorable thermal
properties can keep a mild room temperature, preventing both heat to flow in
and fresh air to flow out of the room. This is of particular importance in
development countries where the low-budget constructions and energy saving
plans play a fundamental social role.
ACKNOWLEDGMENTS
This work was partially financed by CNPq and FENORTE (RJ), whose
support is gratefully acknowledged.
REFERENCES
1 D. Bicanic, in Photocoacoustic and Photothermal Phenomena III, SpringerVerlag, Berlin and Heidelberg, 1992.
2 A. Mandelis , in Photoacoustic and Thermal Wave Phenomena in
Semiconductors, North Holland, New York, Amsterdam and London, 1987.
3 A. Rosencwaig, in Photoacoustic and Photoacustic Spectroscopy, J. Wiley &
Sons, New York, 1980.
4 D. P. Almond, and P. M. Patel, in Photothermal Science and Techniques,
Chapman & Hall, London, 1996.
5 D. C. Fork, , and S. K. Herbert, The apllication of the photoacoustic
Techniques to studies in photosyntehesis, Photochem. Photobiol., 1993, 57,
207.
6 H. Vargas, and Miranda L. C. M., Photoacoustic and related photothermal
techniques, Phys. Rep., 1988, 161, 43.
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7 P. Souza Santos, Ciência e Tecnologia de Argilas, 2ed. Edgard Blücher
Ltda, vol. I,II,III, 1989.
8 J. Alexandre, Caracterização das Argilas do Município de Campos dos
Goytacazes para a Utilização em Cerâmicas Vermelhas, Tese de Mestrado,
Campos, RJ.
9 G. M. Sessler, J. Acous. Soc. Am., 1963, 35, 1354.
10 A. Rosencwaig, and A. Gersho, J. Appl. Phys., 1976, 47, 46.
11 R. Zallen, in The Physics of Amorphous Solid, Wiley, New York, 1083, p.
20.