Original article
On effect of chemical-assisted
mechanical blending of barium
titanate and graphene in PVDF
for 3D printing applications
Ravinder Sharma1, Rupinder Singh2
Journal of Thermoplastic Composite
Materials
1–27
ª The Author(s) 2020
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/0892705720945377
journals.sagepub.com/home/jtc
and Ajay Batish1
Abstract
The polyvinylidene difluoride þ barium titanate (BaTiO3) þgraphene composite (PBGC)
is one of the widely explored thermoplastic matrix due to its 4D capabilities. The
number of studies has been reported on the process parameters of twin-screw extruder
(TSE) setup (as mechanical blending technique) for the development of PBGC in 3D
printing applications. But, hitherto, little has been reported on chemical-assisted
mechanical blending (CAMB) as solution mixing and melt mixing technique combination for preparation of PBGC. In this work, for preparation of PBGC feedstock filaments,
CAMB has been used. Also, the effect of process parameters of TSE on the mechanical,
dimensional, morphological, and thermal properties of prepared filament of PBGC have
been explored followed by 3D printing. Further, a comparative study has been reported
for the properties of prepared filaments with mechanically blended composites. Similarly,
the mechanical properties of 3D printed parts of chemically and mechanically blended
composites have been compared. The results of tensile testing for CAMB of PBGC show
that the filament prepared with 15% BaTiO3 is having maximum peak strength 43.00 MPa
and break strength 38.73 MPa. The optical microphotographs of the extruded filaments
revealed that the samples prepared at 180 C extruder temperature and 60 r/min screw
speed have minimum porosity, as compared to filaments prepared at high extruder
temperature. Further, the results of the comparative study revealed that the filaments of
CAMB composites show better mechanical properties as compared to the filaments of
mechanically mixed composites. However, the dimensional properties were almost
similar in both cases. It was also found that the CAMB composites have better properties
at low processing temperature, whereas mechanically blended composites show better
1
Department of Mechanical Engineering, Thapar Institute of Engineering and Technology, Patiala, India
Department of Mechanical Engineering, National Institute of Technical Teachers Training and Research,
Chandigarh, India
2
Corresponding author:
Rupinder Singh, National Institute of Technical Teachers Training and Research, Chandigarh 160019, India.
Email: rupindersingh@nitttrchd.ac.in
2
Journal of Thermoplastic Composite Materials XX(X)
results at a higher temperature. While comparing 3D printed parts, tensile strength of
specimens fabricated from CAMB was more than the mechanically blended PBGC.
Keywords
Polyvinylidene difluoride, barium titanate, graphene, 4D printing, twin-screw extruder,
fused deposition modeling, differential scanning calorimetry
Introduction
Additive manufacturing (AM)/3D printing is based on the principle of layer manufacturing.1–3 The 3D printing started with the creation of a 3D model on a computer using
computer-aided design software. This 3D model is saved in standard tessellation language
file format, which is further sliced in the layers by slicing software.4–6 It has been widely
reported that AM has numerous applications in the field of biomedical engineering,
aeronautics, automotive industries, food technology, dentistry, jewelry electronics,
robotics, and pharmaceuticals.7–10 Some studies reveal that as compared to traditional
manufacturing techniques, 3D printing produces complex shapes very easily. The generation of complex structures with multimaterials helps to enhance the application domain
of 3D printing.11
Commercially smart materials like shape memory material, electroactive polymer
material (EAP) has become an interest at global level for various applications in the field of
textiles, nanotechnology, biomedical and electronic sensors.12–16 Shape memory alloys
(SMA), shape memory polymers (SMP), and EAP are from the family of smart materials.
The shape memory effect of SMA and SMP shows the unique capability of smart materials
to remain in the desired shape and retains their original shape when triggered by external
stimuli from environment.17 This functional property of SMA and SMP enhances their role
in the field of AM, such as automatic assembly and disassembly (where the fasteners made
up of such materials can perform auto disassembly under the effect of external stimuli).18 On
the basis of active disassembly, a comparative study was performed on the SMP and SMP
composites using finite-element analysis. The results of simulation conducted by considering mechanical and thermal testing show that SMP composite gave a better performance
than the SMP.19 The high amount of flexibility, light in weight, low cost of processing, and
ease of deformation makes these polymers highly useful for various innovative applications,
such as smart devices in the sector of microelectronics, robotics, and biotechnology.20,21
These cross-functional smart material-based devices show significant variations in a
controllable manner when triggered artificially or environmentally. Similarly, piezoelectric materials produce a voltage when comes under the effect of some mechanical
stress known as direct piezoelectric effect (DPE), whereas the reverse of this process is
known as converse piezoelectric effect (CPE).22 The DPE plays a vital role in the pressure
sensors, vibrational energy scavenging, structural health monitoring, and energy harvesting.23 On the flip side, CPE is used in shape control, actuation, and ultrasonic motors.
The piezoelectric devices-based energy harvesting techniques open the doors to develop
autonomous and self-actuated electronic devices.24 Piezoelectric ceramics and quartz
Sharma et al.
3
have been extensively used in electronic applications from a long time. The zinc oxide
(ZnO) and lead zirconate titanate (PZT) are majorly used piezoelectric materials in
electromechanical systems and transducers.25,26 Among the above said piezoelectric
materials, PZT attained much attention for its high value of piezoelectric coefficient.
Nevertheless, the brittleness and toxicity become a constraint in application domain of
PZT.27 Thus, to minimize their impact on environment and health, researchers made
intensive efforts to develop lead-free piezoelectric materials.28 But the problem faced was
to control the composition of the layer precisely. Some researchers have developed
nanowires of ZnO to generate a sufficient amount of power to lighten a light-emitting
diode. However, the length of these nanowires was up to few micrometers only which
restricts their energy generation capacity.29 From the past two decades, the researchers are
trying to employ piezoelectric polymers as sensors, actuators, and many more applications
in the field of electronics and biomedical engineering. The major advantages of using
piezoelectric polymers are their thermal, mechanical, electrical, chemical, and surface
properties that can be easily tailored by applying different processing conditions.30,31
Moreover, polymer-based piezoelectric materials offer nontoxic, nonbrittle, lower stiffness, and high tensile strength, which could be another possible approach for energy
harvesting.32 The piezoelectric property of polyvinylidene difluoride (PVDF) was found
in 1969, which opened the possibility for the creation of relatively a new class of elastic
polymers with low dielectric constant.33 The piezoelectric properties of the EAP receive
an acute interest from the industrial research to produce low-cost energy harvesting
devices. But low actuation and low power generation capacity of EAP restrict their
applications. Therefore, to get better results, ceramic fillers, such as lead titanate, barium
titanate (BaTiO3), and PZT, have been reinforced in the PVDF polymer matrix.34 However, the addition of ceramics put worse effects on the flexibility of the base polymer
matrix.35 Some researchers worked on the addition of carbon powders (carbon nanotubes
(CNT) and graphene (Gr)) in the polymer matrix to improve the mechanical and electrical
properties with relatively low filler to base material ratio.36,37 Few studies have been
reported on the use of PVDF-based composite reinforced with CNT and BaTiO3 for 3D
printing via fused deposition modeling (FDM). It has been observed that 1% of CNT and
12% BaTiO3 as filler provide better mechanical toughness in the 3D printed parts.38 Thus,
the use of FDM with the smart polymer-based composites for possible 4D applications is
one of the acceptable solutions. FDM is one of the low-cost 3D printing processes in which
a thermoplastic filament is extruded and deposited in semimolten form to print a 3D
object. In FDM, size, strength, and other properties of the filament play a prominent role in
successful printing of 3D parts.39 After three decades of its invention, it is still one of the
highly acceptable AM processes and continuous studies are being reported on the
development of different polymers-based FDM feedstock filaments (by reinforcement of
metallic and ceramic powders).40 The addition of fillers in the polymer matrix plays a
prominent role to improve the properties of the base material. Earlier, a single screw
extruder was used for the fabrication of feedstock filament, but it does not provide proper
mixing of fillers in the base material.41 Thus, researchers started working on twin-screw
extruder (TSE) for blending and extrusion process. TSE is mainly known for providing a
high degree of dispersion of fillers in the polymer matrix. In one of the reported studies,
4
Journal of Thermoplastic Composite Materials XX(X)
TSE was used for the development of filament acrylonitrile butadiene styrene reinforced
with 10% ferrous particles to improve its mechanical properties.42 In one of similar
research works, ferrous particles were reinforced in the nylon matrix with the TSE for the
development of filament.43 It has been reported that the process parameters, such as
temperature and screw speed, affect the properties of extruded filaments.44–47
In the past one decade, significant work has been reported on preparation of smart/
electroactive polymer matrix (EAPM)-based feedstock filament with mechanical extrusion
process for FDM setup followed by its 3D printing. The PVDF þ BaTiO3 þ Gr composite
(PBGC) is one of the widely explored thermoplastic matrixes due to its 4D capabilities. The
reported literature reveals that some researchers have optimized the process parameters of
TSE setup (as conventional mechanical blending technique) for the development of filaments by blending/compounding of BaTiO3 and Gr in the PVDF matrix for FDM applications. But, hitherto, little has been reported on CAMB of PBGC. In this research work, for
the preparation of feedstock filaments, EAPM comprising of PBGC has been developed by
CAMB. The study has been performed in two stages. Initially, the effect of process parameters of TSE on the mechanical, dimensional, morphological, and thermal properties of the
prepared filament of PBGC has been explored. The filament with better mechanical and
thermal properties has been used on the FDM setup for 3D printing of standard tensile
specimens. The process parameters of FDM for mechanical properties of 3D printed parts
have been optimized in the second stage. Further, a comparative study has been reported for
the properties of these prepared filaments with feedstock filaments developed from
mechanically mixed composites. Similarly, the mechanical properties of 3D printed parts of
chemically and mechanically blended composites have been compared.
Experimentation
The polymer composites have been prepared by chemical mixing of the materials. Thin
films of composites in different proportions have been prepared by mixing the BaTiO3 and
Gr in the PVDF matrix in the presence of N-N-dimethylformamide (DMF) and dimethyl
sulfoxide (DMSO) solvent. The developed composite has been processed and extruded in
the form of filament on TSE. Further, to study and optimize the process parameters of TSE
for mechanical, dimensional, thermal, and morphological properties of the filament,
Taguchi approach has been used. The developed filament was used to run on open-source
FDM to print the standard tensile specimens. Further process parameters of FDM for
mechanical properties of 3D printed parts have been optimized. Finally, a study was
conducted to compare the properties of these prepared filaments with the properties of
feedstock filaments developed from mechanically mixed composites as an extension of
previous studies.23,30 Similarly, the mechanical properties of 3D printed parts of chemically and mechanically blended composites have been also compared.
PVDF is semicrystalline in nature and developed by polymerizing vinylidene fluoride. It consists of repeatedly added long polymeric chain of [–CF2–CH2]n (Figure 1). A
PVDF 6008/0001 grade procured from Deval Enterprises (Vadodara, India) was used in
this research work. The physical and mechanical properties of the selected grade of
PVDF (as per supplier data) are provided in Table 1.
Sharma et al.
5
Figure 1. Chemical structure of PVDF.
PVDF: polyvinylidene difluoride.
Table 1. Physical, mechanical, and thermal properties of PVDF.
Name of property
Physical properties
Density at 23 C
MFI at 2.16 kg
Water absorption (24 hours at 23 C)
Mechanical properties (tensile strength
(ISO 527–2, 50 mm/min))
Stress at yield
Stress at break
Elongation at yield
Elongation at break
Shore-D hardness
Thermal properties (DSC analysis)
Melting point
Heat of fusion (80 C to end of melting)
Crystallization point
Glass transition (Tg)
Unit
g/cm3
g/(10 min)
%
MPa
MPa
%
%
C
J/g
C
C
Value
Test method
1.75–1.80
5.5–11
<0.04
ASTM D792
ASTM D1238
ASTM D 570
50–60
30–50
5–10
20–300
73–80
ASTM
ASTM
ASTM
ASTM
ASTM
D638
D638
D638
D638
D 2240
170–175
58–67
134–144
40
ASTM
ASTM
ASTM
ASTM
D3418
D3418
D3418
D4065
PVDF: polyvinylidene difluoride; MFI: melt flow index; DSC: differential scanning calorimetry.
The BaTiO3 is a piezoelectric ceramic and mainly known for its lead free and inorganic
nature. Due to a large dipole moment, BaTiO3 is commonly used as a reinforcement in the
EAP to increase their piezoelectric properties. For this research work, BaTiO3 was procured from Ultra Nanotech Pvt Ltd (Bengaluru, Karnataka, India). Table 2 provides the
specifications of the BaTiO3 used in current research work (supplier data).
Gr was also used as a filler in the base polymer matrix. In this study, Gr was procured
from a local vendor (Platonic Nanotech Pvt Ltd, Mahagama, Jharkhand, India). The
specifications of the Gr are provided in Table 3 (supplier data).
Chemical blending of materials
Since this work is an extension of previously reported work in which both blending of
materials and extrusion of filament were performed with TSE,23 therefore, similar proportion of filler to base materials was taken to ascertain the effect of blending method on
the various properties of extruded filaments and 3D printed parts. The weight percentage
6
Journal of Thermoplastic Composite Materials XX(X)
Table 2. Specifications of the BaTiO3.
Name
Unit
Value /type
Particle size
Purity
Specific surface area
Density
Color
Morphology
Nm
%
m2/g
g/cm3
—
—
100
99.9
10.42
5.85
White
Spherical
BaTiO3: barium titanate.
Table 3. Specifications of the Gr.
Name
Unit
Value/type
Physical form
Color
Thermal conductivity
Electrical conductivity
Tensile modulus
Thickness
Length
Density
Number of layers
Surface area
—
—
W/m-K
Siemens/m
GPa
nm
mm
g/cm3
—
m2/g
Fluffy
Gray-black
3000
107
1000
5–10
5–10
3.1
4–8
200–210
Gr: graphene.
Table 4. Three different proportions of materials.
Composition/proportion (wt%)
A
B
C
X PVDF (98%) þGr (2%)
Y BaTiO3
90
85
80
10
15
20
PVDF: polyvinylidene difluoride; Gr: graphene; BaTiO3: barium titanate.
of Gr was kept fixed as 2% of weight of PVDF, whereas BaTiO3 was taken in the range of
10–20% of total weight. Thus, selected three proportions are provided in Table 4.
The composite proportion, as given in Table 4, has been used in this research work. For
20 g of the mixture, 2 g of BaTiO3 was sonicated in DMF for 2 h for complete dispersion.
The quantity of DMF was taken as 1 ml for 0.2 g of BaTiO3. Simultaneously, in another
vessel, a mixture of 360 mg Gr and 17.64 g of PVDF granules were dispersed in 100 ml of
DMF on a hot plate magnetic stirrer for 2 h. During the magnetic stirring, the temperature
of the base plate was kept constant at 50 C. Both solutions were mixed together and 2 ml of
Sharma et al.
7
Table 5. MFI values for different compositions/proportions.a
MFI g/(10 min)
Viscosity ()
Composition/
MFI
Viscosity () in
mechanically
in (Pa-s) of
proportion
Density
g/(10 min)
(Pa-s) mechanically
(wt%)
(r) g/cm3 CAMB sample CAMB sample blended sample23 blended sample
A
B
C
2.187
2.392
2.597
3.98
3.20
2.90
5924.31
8059.03
9654.85
3.11
2.68
2.32
7581.59
9622.73
12068.57
MFI: melt flow index; CAMB: chemical-assisted mechanical blending.
a
Three repeated observations were taken and average value has been quoted.
DMSO was added in it. This nanocomposite solution of PBGC was again stirred at the
same parameters for next 30 min. Some amount of Gr and BaTiO3 was settled down at the
bottom of liquid slurry. Hence, the solution was again put on ultrasonication for 20 min.
For complete evaporation of DMF solvent, slurry of mixture was poured over the glass
substrate and heated at 100 C for next 12 h inside the oven. A thin-film PVDF/Gr/BaTiO3
nanocomposite was formed over the glass substrate and can be easily removed from the
glass surface. The same procedure has been repeated by maintaining the same solute–
solvent ratio for all three compositions/proportions (Table 4).
Flow ability of the material plays a prominent role for uniformity and other
mechanical properties of the extruded filament. Thus, to characterize the rheological
properties of the chemically blended material, melt flow index (MFI) test was performed
as per the ASTM D-1238. MFI is basically the flow rate of material in grams for 10 min
under some applied pressure at prefixed temperature. Initially, the prepared composite of
PVDF þ Gr þ BaTiO3 was preheated at 230 C temperature for 3–5 min, and after that,
constant pressure (2.16 kg) was applied through piston to flow the material through a
standard die having a diameter of 2.0955 + 0.0051 mm and length of 8.000 + 0.025 mm
(in some cases, different orifice is used). The output values of MFI for all three proportions are provided in Table 5. Further, these values were compared with MFI values
of the mechanically blended composites having same proportions. The density of the
composite provided in Table 5 was calculated by ratio proportion method by taking the
values of density of materials mentioned (Table 1–3).
As observed from Table 5, CAMB for preparation of PBGC resulted into better MFI.
Further, the viscosity (m) has been calculated from shear stress (t) and shear rate (g). To
calculate the shear stress and shear rate, the following equations have been used48,49
t¼
r F
2 p R2 l
ð1Þ
4 Q
p r3
ð2Þ
g¼
where r is nozzle radius 0.105 cm, R is radius of piston 0.4737 cm, l is nozzle length 0.8
cm, F is test load L in kg 9.807 105 dynes (here, L is 2.16 kg).
8
Journal of Thermoplastic Composite Materials XX(X)
Since the geometry of melt flow indexer is fixed, thus, after putting the values of
radius of nozzle (r), test load (F), nozzle length (l), and radius of piston (R) in equation
(1), then, shear stress (t) is
t ¼ 9:13 104 L dynes
ð3Þ
whereas shear rate g depends on the volumetric flow rate Q (in cc/s). The volume flow
rate Q can be determined by dividing the volume V extruded during the time t and Q is
calculated as
Q¼
MFI
r 600
ð4Þ
From equations (2) and (4), shear rate can be calculated as
g¼
MFI
p r3 r 150
ð5Þ
After putting the values of MFI, radius of nozzle (r) and density (r) in equation (5) is
as follows
g¼
1:83 MFI
1=s
r
ð6Þ
To calculate viscosity, equation (3) is divided by equation (6)
m¼
9:13 10 4 L r
ðdynes sÞ
1:83 MFI
ð7Þ
9:13 10 4 L r
ðPa sÞ
1:83 MFI 10
ð8Þ
or
m¼
Equation (8) represents the viscosity in terms of MFI. After putting the values of MFI,
density, and load (L) in equation (8), the viscosity of particular composition can be
calculated, as given in Table 5. The graph of viscosity values at their respective compositions is shown in Figure 2.
After successful synthesis of nanocomposite films of all three proportions of PVDF/Gr/
BaTiO3, sheets were cleaved into small sizes. These cleaved parts of the sheets were put into
the TSE for the development of feedstock filament. The commercial TSE (Make: Thermo
scientific HAAKE, Germany) was used for the extrusion of filament. For available FDM
setup, the required diameter of the extruded feedstock filament should be in the range of 1.75
+ 0.05 mm, as the nozzle opening of existing FDM supports only this size of filament. The
temperature of the corotating screws and extruder’s barrel was set according to the melting
point of the material. The diameter of small opening of TSE can be adjusted by changing its
die. The process parameters of the TSE, such as r/min and temperature, directly affect the
various properties (mechanical, physical, and thermal) of the extruded filament. As this
study is extended part of previously conducted research work,23 thus, to do a comparison
9
Viscosity (103) (Pa-s)
Sharma et al.
14
12
10
8
6
4
2
0
A
B
C
Composition
CAMB
Mech. Blend
Figure 2. Viscosity versus composition.
Table 6. Control log of experiment.
Experiment no.
1
2
3
4
5
6
7
8
9
Temperature ( C)
r/min
Composition
180
180
180
190
190
190
200
200
200
40
50
60
40
50
60
40
50
60
A
B
C
B
C
A
C
A
B
between the output values of properties of chemically blended composite filaments with the
mechanically blended composite filaments, same experiment conditions were selected. The
range of barrel temperature was taken from 180 C to 200 C and rotation speed of screws
was taken in the range of 40–60 r/min. To optimize the process parameters of TSE, nine set
of experiments (with three repetitions) were performed at different settings of TSE, as per
Taguchi L9 orthogonal array (OA) (Table 6).
The PBGC prepared with chemical blending has been fed to TSE set up (as per Table 6).
The material extruded with TSE was collected. After the extrusion process, the filaments
were tested for their mechanical, dimensional, thermal, and morphological properties. For
ensuring mechanical properties, tensile testing was performed on a universal testing
machine (UTM) setup (Make: Shanta Engineering, Pune, Maharashtra, India), whereas, to
measure the diameter of the filaments, a Mitutoyo micrometers (as per ISO-3611-1978)
accurate up to three decimal places was used. To perform thermal analysis, extruded
filaments were subjected to differential scanning calorimetry (DSC) testing. Further to
optimize the tensile strength of filaments, MINITAB-17 software package was used. The
10
Journal of Thermoplastic Composite Materials XX(X)
Table 7. Selected FDM parameters for parametric optimization.
Input process variables of FDM (each at three levels)
Input parameters
IS (mm/s)
IA ( )
ID (%)
Level 1
Level 2
Level 3
50
0
60
70
45
80
90
90
100
FDM: fused deposition modeling; IS: infill speed; IA: infill angle; ID: infill density.
Table 8. A complete design of experiments.
Experiment no.
1
2
3
4
5
6
7
8
9
Parameters
IS (mm/s)
IA ( )
ID (%)
50
0
60
50
45
80
50
90
100
70
0
80
70
45
100
70
90
60
90
0
100
90
45
60
90
90
80
IS: infill speed; IA: infill angle; ID: infill density.
filament shown best mechanical strength and having diameter in the range of 1.75 + 0.05
mm was used to run on the existing open-source 3D printing machine.
The filament comprising PBGC after CAMB with maximum mechanical strength was
used run on open-source FDM printer (Make: Divide by zero, Mumbai, Maharashtra,
India). To study the effect of process parameters of FDM, standard tensile specimens were
fabricated, as per ISO 527–2 (an International standard for tensile testing of reinforced
plastics). Three process parameters—infill speed (IS), infill angle (IA), and infill density
(ID)—were chosen on the basis of pilot experimentation and literature review (as these
three selected parameters mainly affect the properties of printed parts). The other fixed
parameters were nozzle diameter: 0.5 mm, temperature of bed: 85 C, fan output: 50%, and
fill pattern: rectilinear, and so on. For optimization process, each selected process variable
was further divided at three levels (Table 7).
To optimize the process parameters by performing a minimum number of experiments,
again, Taguchi L9 OA was used (Table 8). For all selected nine settings, 3D printing of
standard tensile specimens as per ISO 527–2 was performed with three repetitions.
The 3D printed dumbbell-shaped specimens of PBGC were subjected to destructive
tensile testing as per the ISO 527–2 (International standard for tensile testing of reinforced
plastics) at room temperature. Destructive testing of the specimens was performed on
UTM. The outputs peak strength (PS) and break strength (BS) were noted for tensile
testing. The stress–strain curves were plotted to understand the mechanism of deformation
of the material. To optimize the tensile strength of the 3D printed parts, analysis of variance (ANOVA), a statistical tool, has been used. Further, the tensile strength of standard
Sharma et al.
11
Figure 3. Stress–strain curve obtained from tensile testing of filaments.
Table 9. Results obtained from tensile testing and their corresponding SN ratios.
Experiment no.
1
2
3
4
5
6
7
8
9
PS (MPa)
31.41
35.69
42.80
34.86
34.03
38.10
26.63
22.84
29.37
+ 1.04
+ 1.75
+ 0.86
+ 0.75
+ 1.96
+ 1.25
+ 0.58
+ 0.95
+ 0.80
SN ratios PS
BS (MPa)
SN ratios BS
FT (MPa)
29.94
31.05
32.62
30.84
30.63
31.61
27.46
27.17
29.35
28.26 + 0.58
32.12 + 0.60
38.52 + 1.05
31.37 + 0.90
30.62 + 0.48
34.29 + 0.98
21.26 + 0.50
20.55 + 0.74
26.43 + 0.68
29.02
30.13
31.71
29.93
29.72
30.70
26.55
26.25
28.44
3.31
1.63
1.59
1.49
1.79
1.85
1.25
1.33
1.17
SN: signal-to-noise; FT: fracture toughness; PS: peak strength; BS: break strength.
specimens prepared from CAMB was compared with the tensile strength of parts made up
of mechanically blended composites.
Results and discussion
After the extrusion process (as per Table 6), filaments were subjected to tensile testing.
The results of tensile testing in the form of PS, BS, and fracture toughness (FT) (based on
area under stress–strain curve, Figure 3) are provided in Table 9. Further, the values of
signal-to-noise (SN) ratio have been calculated at larger the better type condition.
As observed from Table 9, the maximum value of PS (42.80 MPa) and BS (38.52
MPa) was noted in experiment no. 3; however, the minimum tensile strength was found
12
Journal of Thermoplastic Composite Materials XX(X)
Table 10. ANOVA for SN ratios (PS of filaments).
Factor
Temperature
r/min
Composition
Residual error
Total
DoF Sequential SS Adjusted SS Adjusted MS
2
2
2
2
8
19.516
4.718
2.181
0.090
26.505
19.516
4.718
2.181
0.090
9.76
2.36
1.090
0.045
F
%Age
p Value contribution
216.98
63.58
13.14
0.005
0.015
0.071
73.63
17.80
8.22
0.35
DoF: degree of freedom; SS: sum of squares; MS: mean of squares, F: Fisher’s value; ANOVA: analysis of
variance PS: peak strength.
Table 11. Response table of input parameters for PS of filaments.
Levels
Temperature
r/min
Composition
1
2
3
d
Rank
31.21
31.03
28.00
3.21
1
29.42
29.62
31.20
1.78
2
29.58
30.42
30.25
0.84
3
PS: peak strength.
in experiment no. 8. Therefore, the processing conditions of experiment no. 8 can be
rejected outrightly. Based on these observations for 3D printing, feedstock filament with
maximum tensile strength (experiment no. 3) may be selected for further processing.
Further, to optimize the processing condition of TSE for tensile strength (PS and BS),
ANOVA was performed (Table 10). As the probability (p) value of the first two selected
parameters (temperature and r/min) is less than 0.05 (Table 10), these two parameters
were considered significant at 95% confidence level. However, for third parameter
(composition), the value of p is not less than 0.05, thus considered as insignificant.
Based on Tables 9 and 10, rank table (Table 11) shows ranking of process parameters for
SN values of PS. As observed from Tables 10 and 11, first parameter (temperature) has most
effective role as it stood first, whereas r/min and composition of filament ranked second and
third, respectively. The main effect plot for SN ratios is shown in Figure 4, which represents
that the filament fabricated at 180 C of extruder temperature and speed of screw 60 r/min
and intermediate level of composition will have best mechanical properties.
The SN values obtained (Table 9) have been further used for the prediction of optimized value using equation (9)
hopt ¼ R þ ðRA RÞ þ ðRB RÞ þ ðRC RÞ
ð9Þ
where RA, RB, and RC are the maximum values of temperature, r/min, and composition
from Table 10 and R is the mean of SN values for PS
Sharma et al.
13
Figure 4. SN graph for PS of filaments.
SN: signal-to-noise.
R ¼ 30:08; RA ¼ 31:21; RB ¼ 31:20; RC ¼ 30:42
After putting these values in the equation (9)
hopt ¼ 32:67
Now,
yopt 2 ¼ ð10Þhopt = 10 ðf or larger the better type caseÞ
Yopt 2 ¼ ð10Þ32:67= 10
Yopt 2 ¼ 1849:27
Yopt ¼ 43:00 MPa
ð10Þ
Three repetitive confirmatory experiments were conducted at proposed settings and the
average value of observed PS is 43.18 MPa, which is very close to the calculated value,
that is, 43.00 MPa.
Based on the SN ratios of BS, the SN response graph at larger the better conditions is
shown in Figure 5.
Based on Table 9, ANOVA table for SN values of BS at 95% confidence level is
presented in Table 12.
Table 13 displays the rank of process parameters based on the SN ratios of BS. It has
been observed that the temperature puts a major effect on the BS followed by r/min and
composition with rank second and third, respectively.
The SN values of BS (Table 9) have been further used for the prediction of optimized
value using equation (3)
hopt ¼ R þ ðRA RÞ þ ðRB RÞ þ ðRC RÞ
ð11Þ
where RA, RB, and RC are the maximum values of temperature, r/min, and composition
from Table 13 and R is the mean of SN values for PS
R ¼ 29:16; RA ¼ 30:29; RB ¼ 30:29; RC ¼ 29:50
14
Journal of Thermoplastic Composite Materials XX(X)
Figure 5. SN graph for BS for filament.
SN: signal-to-noise; BS: break strength.
Table 12. ANOVA for SN ratios (BS for filament).
Factor
DoF
Sequential
SS
Adjusted
SS
Adjusted
MS
2
2
2
2
8
20.529
5.729
0.185
0.090
26.533
20.529
5.729
0.185
0.090
10.26
2.86
0.092
0.045
Temperature
r/min
Composition
Residual error
Total
F
p Value
216.19
63.43
13.11
0.005
0.016
0.071
%Age
contribution
77.37
21.59
0.70
0.34
SN: signal-to-noise; DoF: degree of freedom; SS: sum of squares; MS: mean of squares, F: Fisher’s value;
ANOVA: analysis of variance; BS: break strength.
Table 13. Response table of input parameters for BS for filament.
Levels
Temperature
r/min
Composition
1
2
2
d
Rank
30.29
30.12
27.08
3.21
1
28.50
28.70
30.29
1.78
2
28.66
29.50
29.33
0.84
3
BS: break strength.
After putting these values in equation (11)
hopt ¼ 31:76
Sharma et al.
15
Peak strength (MPa)
Peak Strength variation
50
45
40
35
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
9
Experiment No.
PS (MPa) (mech. mixing) 19.57 22.34 26.5 23.59 28.15 21.9 29.57 22.92 24.57
PS (MPa) (Chem. mixing) 31.41 35.69 42.8 34.86 34.03 38.1 26.63 22.84 29.37
Figure 6. Comparison of PS for filaments (mechanically extruded and CAMB composites).
CAMB: chemical-assisted mechanical blending; PS: peak strength.
Now,
yopt 2 ¼ ð10Þhopt = 10 ðf or larger the better type caseÞ
Yopt 2 ¼ ð10Þ31:76= 10
Yopt 2 ¼ 1499:68
Yopt ¼ 38:73 MPa
ð12Þ
A total of three repetitive confirmatory experiments were conducted at proposed settings and the average value of observed BS was 38.80 MPa, which is very close to the
calculated value, that is, 38.73 MPa.
A comparison was made between the tensile properties of extruded filaments of
chemically and mechanically blended composites.
The values of PS of the filaments of mechanically blended composites (taken from
previously reported study23) and PS of the filaments of CAMB are shown in bar graph
(Figure 6).
In both cases, the extrusion of filaments was performed at similar experimental condition. It should be noted that the methods of preparation of composites were different.
Thus, it has been revealed from the bar graph that the filaments of chemically mixed
composites have higher PS as compared to filaments of mechanically blended composites.
Moreover, the best parametric settings of the TSE are also different in both cases. As in
case of chemically mixed composites, the optimized settings to fabricate the filament
shown in maximum tensile strength were 180 C of extruder temperature, 60 r/min screw
speed, and 15% of BaTiO3. However, for mechanically mixed composites, the optimized
settings are 200 C processing temperature, 50 r/min screw speed, and 20% BaTiO3.
Similar to PS, a comparison was also made between the BS of filaments prepared via
chemically/mechanically mixed composites, as shown in Figure 7.
Since the main purpose of this study is to develop a smart polymer-based feedstock
filament comprising PBGC for FDM process. The existing FDM setup supports only the
filament having a diameter within the range of 1.75 + 0.05 mm. Thus, it was necessary
16
Journal of Thermoplastic Composite Materials XX(X)
Break Strength variation
Break strength (MPa)
45
40
35
30
25
20
15
10
5
Experiment No. 0
1
2
3
4
5
6
7
8
9
BS (MPa) (mech. mixing) 17.21 20.4 24.8 21.24 25.69 18.28 26.5 19.8522.37
BS (MPa) (Chem. mixing)28.26 32.12 38.52 31.37 30.62 34.29 21.26 20.55 26.43
Figure 7. Comparison of BS for filaments of mechanically blended and CAMB composites.
CAMB: chemical-assisted mechanical blending; BS: break strength.
Table 14. Measured dimensions of the extruded filaments.
Parameter (A)
Temperature
Experiment no.
( C)
1
2
3
4
5
6
7
8
9
180
180
180
190
190
190
200
200
200
Parameter
(B) r/min
Parameter (C)
composition
wt%
Ø1
Ø2
Ø
Ø
Ø3 Average (required) DØ
40
50
60
40
50
60
40
50
60
A
B
C
B
C
A
C
A
B
1.68
1.76
1.77
1.67
1.75
1.71
1.83
1.78
1.82
1.72
1.72
1.74
1.69
1.70
1.75
1.95
1.81
1.78
1.69
1.72
1.78
1.72
1.69
1.70
1.90
1.85
1.79
1.70
1.73
1.76
1.69
1.67
1.72
1.70
1.63
1.68
1.75
1.75
1.75
1.75
1.75
1.75
1.75
1.75
1.75
0.05
0.02
0.01
0.06
0.08
0.03
0.05
0.12
0.07
to perform the dimensional analysis of the extruded filaments. Therefore, after the
extrusion of feedstock filaments as per the different processing parameters, they were
subjected to dimensional measurement. To minimize the experimental error, a total of
three readings were taken at three different places over the total span length of the
filaments. The average diameters (Ø) of three measured dimensions were compared with
the required standard diameter of the filament. Measured dimensions of the filament and
their comparison with the standard dimensions are provided in Table 14. It has been
observed that the filament extruded as per experiment no. 3 has a minimum deviation,
whereas the filament extruded as per experiment no. 8 has a maximum deviation. These
observations are in line with the results of mechanical testing.
To make a comparison of the measured dimensions of filaments of CAMB of PBGC
with the dimensions of filaments of mechanically mixed composites, line graph has been
used (Figure 8).
After the mechanical and dimensional testing of all fabricated filaments, it has been
observed that the filament extruded as per experiment no. 3 (prepared at 180 C processing
Sharma et al.
17
Dia. of filament (mm)
Dimensional variations
1.95
1.90
1.85
1.80
1.75
1.70
1.65
1.60
1.55
1.50
1.45
1
2
3
4
5
6
7
8
9
Experiment No.
dia( mm) chem mix 1.69 1.74 1.76 1.69 1.71 1.72 1.89 1.81 1.80
dia (mm) mech. Mix 1.68 1.65 1.62 1.72 1.77 1.79 1.74 1.76 1.78
Figure 8. Dimensional measurements of filaments (CAMB/mechanically blended composite).
CAMB: chemical-assisted mechanical blending.
temperature, 60 r/min, and composition/proportion “B”) has shown the best mechanical
properties, and filament extruded as per experiment no. 8 resulted into poor mechanical
properties. Further, to ascertain the effect of processing condition on the surface properties
(such as porosity/voids and surface roughness) of the extruded filaments, morphological
analysis was performed. A metallurgical microscope was used to capture the photomicrographs of the samples at 100 magnification. The surface porosity (F) of the
samples was measured as per ASTM B-276 by commercially available metallurgical
image analysis software. Figure 9 shows the photomicrographs of the surfaces of the
filaments with the percentage of F on the surface. The red zone is selected area for analysis
of percentage porosity. It has been observed from the photomicrograph’s filament shown
maximum tensile strength has less porosity (F ¼ 1.53%) on its surface as compared to the
other filaments, whereas the filament having poor mechanical properties is having maximum percentage of porosity (F ¼ 5.58%) among all the samples.
Further to ascertain the surface roughness of the extruded filaments, the photomicrographs of filaments captured at 100 were processed on image processing software
to get 3D rendered images and surface roughness profile at cutoff length of 0.04 mm
(Figure 10). It has been observed from the surface roughness profiles that parts with
maximum tensile strength are having minimum roughness over its surface. It should be
noted that the FDM setup supports the filament having a high surface finish. The results of
surface roughness testing suggested that the filament having less surface roughness and
more mechanical strength could be more suitable for the 3D printing process.
The PVDF is known for its high thermal resistance, however, to study the effect of
reinforced materials on the thermal properties of the polymer matrix, thermal analysis was
performed. Thermal properties of the material play a very effective role for the use of
material in a particular application. The results of mechanical testing suggested that the
filament extruded at 180 C processing temperature, 60 r/min, and composition “B” has
maximum tensile strength. For thermal analysis of the filaments, a DSC (Make: Mettler
Toledo (Laboratory Analytical Instruments Mettler-Toledo India Private Limited,
Mumbai, Maharashtra, India), Swiss with STARe (SW 14.00) software) was used. In this
18
Journal of Thermoplastic Composite Materials XX(X)
Figure 9. Optical photomicrographs with variation of percentage porosity (as per Table 6). (a) F
¼ 4.57%, (b) F ¼ 5.58%, and (c) F ¼ 4.31%.
present study, two samples were prepared for thermal analysis; first sample was taken
from the filament shown best mechanical strength, and the second sample was taken from
the filament with the worst mechanical strength. Thermal analysis was performed in the
presence of N2 gas.
Thermal graphs for two samples are shown in Figure 11. The curve 1 is for the filament
with maximum tensile strength (prepared at 180 C processing temperature, 60 r/min and
composition/proportion “B”), whereas curve 2 is of filament with poor mechanical
properties (prepared as per settings suggested in Table 6). For thermal analysis, each
sample faced two repetitive heating–cooling cycles by keeping the temperature range of
30 C to 250 C. The samples were heated at the rate of 10 K/min. As observed from curve
1, it clearly depicts that the melting of the material starts at 164 C and ends at 177 C. The
melting point of composite material is 174 C and the solidification of the material starts at
Sharma et al.
19
Figure 10. (a) 3D rendered images and (b) surface roughness profile of prepared filaments (as per
Table 6).
20
Journal of Thermoplastic Composite Materials XX(X)
Figure 11. DSC graphs of composites developed as per the settings shown best and worst
mechanical properties.
DSC: differential scanning calorimetry.
146 C and ends at 140 C. Almost similar trend has been observed in the second cycle of
heating and cooling. Thermal cycles for the curve 2 also show almost same values of the
temperature for melting and solidification of the material. Hence, it is ascertained that the
addition of Gr and BaTiO3 does not affect the liquification and solidification of the PVDF
matrix even in CAMB. Moreover, the similar trends obtained from both cycles of thermal
analysis justify the thermal consistency of the material.
However, there is a difference in the energy absorption rate of both the samples. The
curve 1 of the sample having more BaTiO3 absorbed 26.43 J/g energy, whereas the sample
having minimum BaTiO3 absorbed less energy, that is, 25.56 J/g. However, the second
thermal cycles of the samples show that both the samples absorbed more energy than their
respective first thermal cycles. Thus, it represents that the developed smart polymerbased composite is not only thermally stable for its reusability but also acts as a thermodynamic sink.
Mechanical testing of 3D printed parts
To ensure whether the extruded filament runs smoothly on the low-cost open-source FDM,
standard tensile specimens as per ISO 527–2 were fabricated. A total of nine specimens
fabricated as parametric settings (with three repetitions) are provided in Table 8. The 3D
printed parts were further subjected to destructive tensile testing on UTM. Results of
tensile testing in the form of peak load (PL), break load (BL), PS, and BS are provided in
Table 15. The stress–strain curves obtained from the mechanical testing of 3D printed
tensile specimens are shown in Figure 12.
The output values of tensile testing show that the maximum PS was observed in the
part fabricated at lowest IS (50 mm/s) and having maximum ID (100%) by depositing
Sharma et al.
21
Table 15. Output values of tensile strength of 3D printed parts.
Experiment
no.
1
2
3
4
5
6
7
8
9
IS
(mm/s)
IA
( )
ID
(%)
50
50
50
70
70
70
90
90
90
0
45
90
0
45
90
0
45
90
60 792.0 + 3.61 730.0 + 4.58 41.25 +
80 848.6 + 4.37 768.4 + 4.72 44.2 +
100 1058.7 + 4.05 950.4 + 4.88 55.14 +
60 686.6 + 3.86 617.5 + 4.25 35.76 +
80 919.7 + 3.48 808.3 + 2.76 47.9 +
100 585.6 + 2.31 541.1 + 1.58 30.5 +
60 732.5 + 1.80 675.8 + 3.90 38.15 +
80 427.2 + 3.29 387.1 + 3.65 22.25 +
100 548.9 + 4.67 500.7 + 4.90 28.59 +
PL (N)
BL (N)
PS (MPa)
0.19
0.23
0.21
0.20
0.18
0.12
0.09
0.17
0.24
BS (MPa)
PS
(SN)
BS
(SN)
38.02 + 0.19
40.02 + 0.23
49.5 + 0.21
32.16 + 0.20
42.1 + 0.18
28.18 + 0.12
35.2 + 0.09
20.16 + 0.17
26.08 + 0.024
29.905
33.574
34.720
32.073
35.335
28.986
33.164
29.461
30.301
28.992
32.657
33.705
31.238
34.639
28.076
32.369
28.543
29.390
IS: infill speed; IA: infill angle; ID: infill density; PL: peak load; BL: break load; PS: peak strength; BS: break
strength.
Figure 12. Stress–strain curves of tensile tested parts.
the material at 90 IA. It might be due to proper positioning of the material at lower
speed and bonding might be also more at 100% ID. However, the part with worst
mechanical properties was built as per experiment no. 8 (Table 8), in which IS was put
as maximum and IA was kept 45 and having an intermediate level of ID. For these
mechanical properties, the SN at larger the better type case is provided in Table 15.
Further, to optimize the parametric settings of FDM for tensile strength of the printed
parts, ANOVA for SN values of PS is provided in Table 16. As the probability (p) value
of first and third parameter (IS and ID) is less than 0.05 (Table 16), these two parameters are significant at 95% confidence level. However, for second parameter (IA),
the value of p is not less than 0.05, thus, found insignificant. Moreover, the value of
residual error is only 1.71% of the total value, supporting that optimization model is
significant.
Based on Table 16, the rank table (Table 17) shows ranking of process parameters for
SN values of PS. The main effect plot for SN is shown in Figure 13, which represents that
the part printed at the first level of IS by keeping the IA 0 and 100% ID resulted into best
mechanical properties.
22
Journal of Thermoplastic Composite Materials XX(X)
Table 16. Analysis of variance for SN ratios (PS).
Factor
IS
IA
ID
Residual error
Total
DoF Sequential SS Adjusted SS Adjusted MS
2
2
2
2
8
25.456
0.476
21.064
0.820
47.816
25.456
0.476
21.064
0.820
12.73
0.24
10.53
0.41
F
31.00
0.58
25.65
p Value %Age contribution
0.031
0.633
0.038
53.24
1.00
44.05
1.71
IS: infill speed; IA: infill angle; ID: infill density; SN: signal-to-noise; DoF: degree of freedom; SS: sum of squares;
MS: mean of squares, F: Fisher’s value; PS: peak strength.
Table 17. Response table of input parameters for PS.
Levels
IS (m/s)
IA ( )
ID (%)
1
2
2
d
Rank
33.35
31.45
29.23
4.12
1
31.67
31.15
31.21
0.51
3
29.65
31.03
33.36
3.71
2
IS: infill speed; IA: infill angle; ID: infill density; PS: peak strength.
Figure 13. SN ratio graph for PS.
SN: signal-to-noise; PS: peak strength.
The SN values obtained (Table 17) have been further used for the prediction of
optimized value using equation (5)
hopt ¼ R þ ðRA RÞ þ ðRB RÞ þ ðRC RÞ
ð13Þ
where RA, RB, and RC are the maximum values of IS, IA, and ID from Table 17 and R is
the mean of SN values for PS.
Sharma et al.
23
Peak strength (MPa)
Peak Strength variation
70
60
50
40
30
20
10
0
1
2
3
4
5
6
7
8
9
Experiment No.
PS (MPa) (mech. mixing) 34.32 38.07 40.1 36.15 39.79 32.81 37.86 31.88 33.23
PS (MPa) (Chem. mixing) 41.25 44.2 55.14 35.76 47.9 30.5 38.15 22.25 28.59
Figure 14. Comparison of PS of 3D printed parts of mechanically and CAMB composites.
CAMB: chemical-assisted mechanical blending; PS: peak strength.
R ¼ 31:34; RA ¼ 33:35:21; RB ¼ 31:67; RC ¼ 33:36
After putting these values in equation (13)
hopt ¼ 35:69
Now,
yopt 2 ¼ ð10Þhopt = 10 ðf or larger the better type caseÞ
Yopt 2 ¼ ð10Þ35:69= 10
Yopt 2 ¼ 3706:81
Yopt ¼ 60:88MPa
ð14Þ
Three repetitive confirmatory experiments were conducted at proposed optimized
settings, and the average value of PS was 62.78 MPa, which is very close to the calculated value, that is, 60.88 MPa.
The tensile properties of 3D printed parts of mechanically mixed composites were
taken from our previously reported work30 to compare it with the tensile properties of 3D
printed parts of CAMB composites, fabricated under similar experimental conditions.
From both cases, the values of PS were chosen for comparison (Figure 14).
As observed from Figure 14 for experiment nos. 1, 2, 3, 5, and 7, PS is found more in
parts made up from CAMB composites. But, for remaining experimental conditions
(experiment nos. 4, 6, 8, and 9), the PS is found more in specimens of mechanically
blended composites. Moreover, in both the cases, the parts printed as per experiment no.
3 has shown maximum tensile strength.
Conclusions
In this present research work, EAP-based matrix of PVDF was reinforced with BaTiO3
and Gr to prepare PBGC for the fabrication of a feedstock filament for FDM (for possible
24
Journal of Thermoplastic Composite Materials XX(X)
4D applications). Based on the experimental results, followings are the outcomes of this
present study:
The significant improvement in rheological properties of CAMB-based PBGC
was observed in comparison to mechanically blended samples. Hence, the
CAMB-based PBGC can be used at higher production rate and for thin section
fabrication.
The results of ANOVA outline that as regards to PS and BS of feedstock
filament (of CAMB based PBGC) is concerned, temperature has maximum
contribution (73.63% and 77.37%) followed by screw speed (17.80% and
21.59%), whereas composition has been found insignificant. The feedstock
filament having composition as PVDF (83%) þ Gr (2%) þ BaTiO3 (15%)
and extruded at 180 C extruder temperature with screw speed 60 r/min
has shown maximum PS and BS (43.00 and 38. 73 MPa, respectively).
Filaments of CAMB composites show better results at low processing
temperature.
Further, for CAMB-based PBGC, the dimensional measurements resulted into
controlled process, which was at par with the mechanically blended samples.
The photomicrographs captured with metallurgical microscope concluded that
the feedstock filament with best mechanical properties is also having minimum
porosity (1.53%) and least surface roughness (Ra ¼ 2.89) among all the
extruded filaments. Further, thermal analysis performed on the filaments
obtained from DSC analysis illustrated the thermal consistency of the developed
composite over two thermal cycles.
The results of ANOVA for 3D printed parts outlined that the specimen fabricated at
50 mm/s IS, 0 IA at 100% ID has better mechanical properties (PS 62.78 MPa).
The IS contributed 53.24% followed by ID 44.05% and IA was found insignificant at 95% confidence level.
The comparison of 3D printed CAMB-based PBGC with mechanically blended
composite outlines that more tensile strength was observed for CAMB composites at best parametric settings.
In the present study, no comparison has been made for piezoelectric property of
CAMB-based PBGC. Further study may be conducted for the effect of piezoelectric coefficient or piezoelectric modulus, d33, to quantify the volume change
when a piezoelectric material is subject to an electric field.
Acknowledgments
The authors are thankful to Thapar Institute of Engineering and Technology, Patiala, Guru
Nanak Dev Engineering College, Ludhiana, and National Institute of Technical Teachers
Training and Research, Chandigarh, for providing technical support in this research.
Further, the financial support by AICTE New Delhi, File No. B-230/RIFD/RPS (POLICY-1)/2018-19, is gratefully acknowledged.
Sharma et al.
25
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iD
Rupinder Singh
https://orcid.org/0000-0001-8251-8943
References
1. Rayna T and Striukova L. From rapid prototyping to home fabrication: how 3D printing is
changing business model innovation. Technol Forecast Soc Change 2016; 102: 214–224.
2. Novakova-Marcincinova L and Kuric I. Basic and advanced materials for fused deposition
modeling rapid prototyping technology. Manuf Ind Eng 2012; 11(1): 24–27.
3. Pandey PM, Reddy NV and Dhande SG. Slicing procedures in layered manufacturing: a
review. Rapid Prototype J 2003; 9(5): 274–288.
4. Pandey PM, Reddy NV and Dhande SG. Real time adaptive slicing for fused deposition
modelling. Int J Mach Tools Manuf 2003; 43(1): 61–71.
5. Ford S and Despeisse M. Additive manufacturing and sustainability: an exploratory study of
the advantages and challenges. J Clean Product 2016; 137: 1573–1587.
6. Bechthold L, Fischer V, Hainzlmaier A, et al. 3D printing: a qualitative assessment of
applications, recent trends and the technology’s future potential (No. 17-2015). Studien zum
deutschen Innovations system. Berlin: Expertenkommission Forschung und Innovation (EFI)
- Commission of Experts for Research and Innovation, 2015.
7. Haleem A and Javaid M. 3D printed medical parts with different materials using additive
manufacturing. Clin Epidemiol Glob Health 2019; 8(1): 215–223.
8. Sharma R, Singh R, Penna R, et al. Investigations for mechanical properties of Hap, PVC and
PP based 3D porous structures obtained through biocompatible FDM filaments. Compos Part
B: Eng 2018; 132: 237–243.
9. Quanjin M, Rejab MRM, Idris MS, et al. Recent 3D and 4D intelligent printing technologies: a comparative review and future perspective. Procedia Comput Sci 2020; 167:
1210–1219.
10. Salagare S and Prasad R. (2020). An overview of internet of dental things: new frontier in
advanced dentistry. Wireless Pers Commun 2020; 110(3): 1345–1371.
11. Bradshaw S, Bowyer A and Haufe P. The intellectual property implications of low-cost 3D
printing. ScriptEd 2010; 7: 5.
12. Rupinder S, Ravinder S, and Nishant R. Four-dimensional printing for clinical dentistry.
Reference Module in Materials Science and Materials Engineering 2017. DOI: 10.1016/
B978-0-12-803581-8.10167-5.
13. Chan Vili YY. (2007). Investigating smart textiles based on shape memory materials. Text Res
J 2007; 77(5): 290–300.
14. Sun L, Huang WM, Lu HB, et al. Shape memory technology for active assembly/disassembly:
fundamentals, techniques and example applications. Assembly Autom 2014; 34(1): 78–93.
15. Qattawi A and Ablat MA. Design consideration for additive manufacturing: fused deposition
modelling. Open J Appl Sci 2017; 7(6): 291–318.
16. Ribeiro C, Sencadas V, Correia DM, et al. Piezoelectric polymers as biomaterials for tissue
engineering applications. Colloids Surf B: Biointerf 2015; 136: 46–55.
17. Leng J, Lan X, Liu Y, et al. Shape-memory polymers and their composites: stimulus methods
and applications. Prog Mater Sci 2011; 56(7): 1077–1135.
26
Journal of Thermoplastic Composite Materials XX(X)
18. Abuzied H, Senbel H, Awad M, et al. A review of advances in design for disassembly with
active disassembly applications. Eng Sci Technol Int J 2020; 23(3): 618–624.
19. Carrell J, Tate D, Wang S, et al. Shape memory polymer snap-fits for active disassembly.
J Clean Prod 2017; 19(17–18): 2066–2074.
20. Brousseau E and Eldukhri E. Recent advances on key technologies for innovative manufacturing. J Intell Manuf 2011; 22(5): 675–691.
21. Mangat AS, Singh S, Gupta M, et al. Experimental investigations on natural fiber embedded
additive manufacturing-based biodegradable structures for biomedical applications. Rapid
Prototype J 2018; 24(7): 1221–1234.
22. Uchino K. (2017). The development of piezoelectric materials and the new perspective. In:
Advanced Piezoelectric Materials. Sawston: Woodhead Publishing, 2017, pp. 1–92.
23. Sharma R, Singh R and Batish A. Study on barium titanate and graphene reinforced PVDF
matrix for 4D applications. J Thermopl Compos Mater 2019. DOI: 0892705719865004.
24. Kaur N, Mahesh D and Singamsetty S. An experimental study on piezoelectric energy harvesting from wind and ambient structural vibrations for wireless structural health monitoring. Adv
Struct Eng 2020; 23(5): 1010–1023.
25. Mishra S, Unnikrishnan L, Nayak SK, et al. Advances in piezoelectric polymer composites
for energy harvesting applications: a systematic review. Macromol Mater Eng 2019; 304(1):
1800463.
26. Jalali N. (2015). ZnO nanorods-based piezoelectric energy harvesters, Doctoral dissertation,
Queen Mary University of London.
27. Rahman MA and Chung GS. (2013). Synthesis of PVDF-graphene nanocomposites and their
properties. J Alloys Compd 2013; 581: 724–730.
28. Wang K, Hussain A, Jo W, et al. Temperature-dependent properties of (Bi 1/2 Na 1/2)
TiO 3–(Bi 1/2 K 1/2) TiO 3–SrTiO 3 lead-free piezoceramics. J Am Ceram Soc 2012;
95(7): 2241–2247.
29. Pearton SJ and Ren F. p-type doping of ZnO films and growth of tenary ZnMgO and
ZnCdO: application to light emitting diodes and laser diodes. Int Mater Rev 2014; 59(2):
61–83.
30. Sharma R, Singh R and Batish A. (2020). On mechanical and surface properties of electroactive polymer matrix-based 3D printed functionally graded prototypes. J Thermopl Compos
Mater 2020. DOI: 0892705720907677.
31. Ribeiro C, Sencadas V, Correia DM, et al. Piezoelectric polymers as biomaterials for tissue
engineering applications. Colloids Surf B: Biointerf 2015; 136: 46–55.
32. Taya M, Jenekhe S, Cao G, et al. Energy harvesting and storage systems for future AF
vehicles. United States: University of Washington, Department of Mechanical Engineering,
Seattle, United States, 2012.
33. Bae JH and Chang SH. PVDF-based ferroelectric polymers and dielectric elastomers for
sensor and actuator applications: a review. Funct Compos Struct 2019; 1(1): 012003.
34. Su J and Zhang J. Recent development on modification of synthesized barium titanate
(BaTiO3) and polymer/BaTiO3 dielectric composites. J Mater Sci Mater Electr 2019;
30(3): 1957–1975.
35. Shesan OJ, Stephen AC, Chioma AG, et al. Fiber-matrix relationship for composites preparation. In: BP António and AOF Fábio (eds) Renewable and sustainable composites. Intech
Open, 2019.
36. Ma Q, Hao B and Ma PC. Flexible sensor based on polymer nanocomposites reinforced by
carbon nanotube foam derivated from cotton. Compos Sci Technol 2020; 192: 108103.
Sharma et al.
27
37. Costa P, Nunes-Pereira J, Oliveira J, et al. High-performance graphene-based carbon nanofiller/polymer composites for piezoresistive sensor applications. Compos Sci Technol 2017;
153: 241–252.
38. Kim H, Wilburn BR, Castro E, et al. Multifunctional SENSING using 3D printed CNTs/
BaTiO3/PVDF nanocomposites. J Compos Mater 2019; 53(10): 1319–1328.
39. Weng Z, Wang J, Senthil T, et al. Mechanical and thermal properties of ABS/montmorillonite
nanocomposites for fused deposition modeling 3D printing. Mater Des 2016; 102: 276–283.
40. Singh R, Sharma R and Davim JP. Mechanical properties of bio compatible functional prototypes for joining applications in clinical dentistry. Int J Prod Res 2018; 56(24): 7330–7340.
41. Singh S, Ramakrishna S and Singh R. Material issues in additive manufacturing: a review. J
Manuf Proc 2017; 25: 185–200.
42. Kumar R, Singh R, Ahuja IPS, et al. Friction welding for the manufacturing of PA6 and ABS
structures reinforced with Fe particles. Compos Part B: Eng 2018; 132: 244–257.
43. Kumar S, Singh R, Singh TP, et al. Investigations for mechanical, thermal and magnetic
properties of polymeric composite matrix for four-dimensional printing applications. J Brazil
Soc Mech Sci Eng 2020; 42(4): 1–15.
44. Sharma R, Singh R and Batish A. On multi response optimization and process capability
analysis for surface properties of 3D printed functional prototypes of PVC reinforced with PP
and HAp. Mater Today: Proc 2020; 28: 1115–1122.
45. Singh R and Ranjan N. Experimental investigations for preparation of biocompatible feedstock filament of fused deposition modeling (FDM) using twin screw extrusion process. J
Thermopl Compos Mater 2018; 31(11): 1455–1469.
46. El Magri A, El Mabrouk K, Vaudreuil S, et al. Mechanical properties of CF-reinforced PLA
parts manufactured by fused deposition modeling. J Thermopl Compos Mater, 2019, DOI:
0892705719847244.
47. Bedi P, Singh R and Ahuja IPS. Multifactor optimization of FDM process parameters for
development of rapid tooling using SiC/Al2O3-reinforced LDPE filament. J Thermopl Compos Mater 2020; 33(5): 581–598.
48. Shenoy AV, Saini DR and Nadkarni VM. Melt rheology of polymer blends from melt flow
index. Int J Polym Mater 1984; 10(3): 213–235.
49. Mezger TG. TheRheology Handbook For users ofrotational and oscillatory rheometers3rd
revised edition. Hanover, Germany: Vincentz Network.