Note: Descriptions are shown in the official language in which they were submitted.
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GRAPHENE REINFORCED POLYETHYLENE TEREPHTHALATE
PRIORITY
[0001] This application claims the benefit of and priority to U.S. Patent
Application No.
15/203,668 filed on July 6, 2016; and U.S. Patent Application No. 15/073,477
filed March 17,
2016 and U.S. Provisional Application, entitled "Injected Molded Poly(Ethylene
Terephthalate)-
Graphene Nanocomposites," filed on March 17, 2015 having application serial
number 62/134,482
and U.S. Provisional Application, entitled "Graphene Reinforced Polyethylene
Terephthalate,"
filed on July 8, 2015 having application serial number 62/190,193.
FIELD
[0002] The field of the present disclosure generally relates to polymer
composites. More
particularly, the field of the invention relates to a composition and a method
for graphene
reinforced polyethylene terephthalate.
BACKGROUND
[0003] Composites are defined as multiphase materials, which are found in
nature or may be
man-made. Man-made composites typically are formulated using one or more
materials so as to
achieve properties that are not available individually. Composites may be
classified based on type
of continuous matrix and dispersed phases, such as reinforcement. Composite
materials wherein
one of the constituent phases, primarily the dispersed phase, has at least one
dimension on the
order of 1-100 nanometers are referred to as "nanocomposites." Nanocomposites
may be further
classified based on category (e.g., organic or inorganic), as well as geometry
of nanoscale
reinforcement. A few well-known examples of naturally occurring nanocomposites
include
human bone, seashells, spider silk, and armored fish. As will be appreciated,
each of these
materials comprises a structural hierarchy (structure at multiple length
scales) which makes them
perfolin exceptionally well as compared with other materials of a similar
chemistry.
[0004] Material properties of composites are known to be dependent on
interactions between
the matrix and the dispersed reinforcement. Large surface areas per unit
volume at the nanoscale
generally cause nanomaterials to function differently than their bulk
counterparts. With increased
interactions between the matrix and the dispersed phase, nanocomposites are
considered relatively
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superior to conventional composites, providing advantageously new properties
without
compromising existing beneficial properties, such as strength or durability.
[0005]
Polyethylene terephthalate (PET) is an aromatic semi-crystalline thermoplastic
polyester, synthesized in the early 1940s. PET is well known for its strength
and toughness, high
glass transition and melting points, chemical resistance, and optical
properties. PET is commonly
used for commodity and engineering applications also due to its relatively low
cost. PET
characterized by a microstructure wherein longitudinal stretching forms strong
fibers with high
molecular chain orientation, as well as bi-axial stretching forming strong
films. Linear PET is
naturally semi-crystalline. Thermal and mechanical history, such as rate of
cooling and stretching,
respectively, can drive PET to be amorphous or more crystalline, and thus
influence its mechanical
properties. Although PET is utilized in industries such as fiber, packaging,
filtration, and
thermoforming industries, the use of PET is constrained due to a slow
crystallization rate and a
limited barrier performance as compared to other polyesters, such as PBT, PTN,
and the like.
[0006]
As will be appreciated, there is a long felt need to develop lightweight
materials for use
across a range of industries, such as packaging, automotive, and aerospace,
thus promoting
attempts to improve material properties through better control of material
processing and an
addition of reinforcements. For example, increasing the crystallinity of PET
improves its
mechanical and barrier properties. Restrictions with the material, however,
such as crystallization
rate, and industrial processes in maximizing crystallinity, such as cooling
rate, cycle time, and
stretching process, have limited attempts to improve the material properties
of PET. Progress in
the field of nanomaterials, however, has led to a development of PET
nanocomposites which have
improved the physical properties of PET, thus making PET more effective for
applications within
the automotive, aerospace, and protective apparel industries.
Different types of
nanoreinforcements (Clay, CNF, CNT, Graphene, Si02, etc.) have been found to
improve the
material properties of PET, such as mechanical, thermal, barrier, electrical,
fire retardation, optical,
surface properties, crystallization kinetics of PET, and the like.
[0007]
Exfoliation of nanoreinforcements into individual entities and their uniform
dispersion
into a polymer matrix is essential for the success of polymer nanocomposites.
Uniform dispersion
of nanoreinforcements in polymers may be achieved by way of various
approaches, including, but
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not limited to, melt-compounding, in-situ polymerization, surface treatment of
the
nanoreinforcements, and the like. Carbon nanomaterials, such as carbon
nanofibers, carbon
nanotubes (CNTs), and graphene generally are advantageous due to their
superior material
properties and simple chemistry. Multi-fold property improvements can be
achieved through the
dispersion of carbon nanomaterials into polymers
[0008] Graphene is a relatively new nanomaterial which comprises a single
layer of carbon
atoms similar to an unzipped single walled carbon nanotube. Single layer
graphene generally is
twice as effective as CNTs in reinforcing polymers since graphene has two
surface for polymer
interaction whereas a CNT comprises only one exterior surface for polymer
interaction. It will be
appreciated that a development of graphene synthesis methods in conjunction
with an introduction
of new graphene-based nanomaterials, such as graphene oxide, expanded
graphite, and graphene
nanoplatelets, has made graphene commercially viable. However, limited
information on the
effectiveness of graphene-based nanomaterials has limited their application in
fabricating polymer
nanocomposites. Thus, there is a need for investigating the influence of
graphene nanomaterials
in reinforcing polymers.
[0009] Melt-compounding and in-situ polymerization have been the most
studied techniques
for preparing PET-Graphene nanocomposites. Although in-situ polymerization is
effective in
dispersing graphene, the use of in-situ polymerization is limited due to
difficulties in attaining a
desired molecular weight and a need for expensive reactors. Melt-compounding
is a straight-
forward approach involving shear mixing, but that alone has not been found to
be effective in
dispersing graphene in the several polymer systems tested. As will be
appreciated, achieving a
homogenous dispersion of the nanoplatelets in PET is critical for improving
bulk properties.
Dispersing graphene in PET is nontrivial, however, as PET generally is highly
viscous (500¨ 1000
Pas) with a melting temperature of 260 C - 280 C. Thus, selecting a process
that can allow
working at high temperatures and with highly viscous materials is necessary.
[0010] Another important aspect for the implementation of polymer
nanocomposite
applications is an ability to predict their material properties so as to
provide flexibility in designing
manufacturing processes and to reduce developmental costs. Traditional
composite models are
not accurate in predicting the properties of nanocomposites. Although
micromechanical models
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based on continuum theory have been found to be effective in estimating short
fiber composites,
few studies have reported an applicability of these models to nanocomposites.
[0011] What is needed, therefore, is an effective process whereby graphene
nanoplatelets
(GNP) may be uniformly dispersed in PET so as to reinforce bulk PET, and
micromechanical
models whereby the material properties of reinforced bulk PET may be
predicted.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The drawings refer to embodiments of the present disclosure in
which:
[0013] Figure 1 is a chemical formula illustrating a molecular structure of
polyethylene
terephthalate in accordance with the present disclosure;
[0014] Figure 2 is a graph illustrating a relationship between particle
interface and size,
according to the present disclosure;
[0015] Figure 3 is a table listing properties of graphene obtained through
different methods,
according to the present disclosure;
[0016] Figure 4 illustrates unique structure of carbon allotropes in
accordance with the present
disclosure;
[0017] Figure 5 is a micrograph illustrating carbon black nanoparticles
used for reheat
performance of PET, according to the present disclosure;
[0018] Figure 6(a) is a micrograph of graphene nanoplatelets, according to
the present
disclosure;
[0019] Figure 6(b) is a micrograph showing a presence of multiple
nanoplatelets in an
agglomerate in accordance with the present disclosure;
[0020] Figure 7 is a chemical formula illustrating a molecular structure of
nanoplatelets
(xGnP), according to the present disclosure;
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[0021] Figure 8 is a table listing properties of PET and master-batch
pellets in accordance with
the present disclosure;
[0022] Figure 9 is a schematic illustrating an ultrasound assisted twin-
screw extrusion system
in accordance with the present disclosure;
[0023] Figure 10 is a schematic illustrating a process for preparation of
ethylene glycol-
graphene nanoplatelets in accordance with the present disclosure;
[0024] Figure 11 is a schematic illustrating a reactor setup for an ester
interchange step,
according to the present disclosure;
[0025] Figure 12 is a chemical formula illustrating an ester interchange
reaction between
dimethyl terephthalate (DMT) and ethylene glycol (EG) to form the PET monomer
in accordance
with the present disclosure;
[0026] Figure 13 is a schematic illustrating a reactor setup for a
polycondensation step in
accordance with the present disclosure;
[0027] Figure 14 is a chemical formula illustrating formation of PET
polymer chain from
monomer, in accordance with the present disclosure;
[0028] Figure 14(a) is a table listing reaction times and methanol yield
for respective
polymerization batches, according to the present disclosure;
[0029] Figure 15 is a cross-sectional view illustrating an injection
molding compatible tensile
specimen, according to the present disclosure;
[0030] Figure 16(a) illustrates a PET and master-batch pellet mixture from
feed throat 0.6%
loading from Set B processing, according to the present disclosure;
[0031] Figure 16(b) illustrates a PET and master-batch pellet mixture for 0
USM ultrasound
treated batch in accordance with the present disclosure;
[0032] Figure 16(c) is a table listing details of PET nanocomposite samples
obtained by way
of injection molding in accordance with the present disclosure;
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[0033] Figure 16(d) is a table illustrating a comparison of process
pressures between PET and
nanocomposites from ultrasound treated master-batches, according to the
present disclosure;
[0034] Figure 17 (a) and (b) illustrates visual signs of poor mixing, as
observed for 0.5% GNP
nanocomposites, in accordance with the present disclosure;
[0035] Figure 18(a) illustrates a micro-compounder with co-rotating twin
screws, in
accordance with the present disclosure;
[0036] Figure 18(b) illustrates a micro-injection molding system and
transfer device, in
accordance with the present disclosure;
[0037] Figure 19(a) illustrates a dual dog bone mold used for making
tensile samples in
accordance with the present disclosure;
[0038] Figure 19(b) illustrates molded PET tensile bars, according to the
present disclosure;
[0039] Figure 19(c) is a table listing process parameters for tensile bars
made by way of a
micro-injection molding system in accordance with the present disclosure;
[0040] Figure 20 is a schematic illustrating a capillary viscometer in
accordance with the
present disclosure;
[0041] Figure 21(a) illustrates testing of a nanocomposite tensile bar in
accordance with the
present disclosure;
[0042] Figure 21(b) illustrates a tube testing fixture, according to the
present disclosure;
[0043] Figure 21(c) illustrates tube testing, according to the present
disclosure;
[0044] Figure 21(d) illustrates testing of tensile bar from a micro-
injection molding system, in
accordance with the present disclosure;
[0045] Figure 22 is a schematic illustrating a parallel plate geometry and
a polymer melt in
accordance with the present disclosure;
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[0046] Figure 23 is a schematic illustrating a sample geometry with respect
to an instrument
geometry, accompanied by a 2D X-ray diffraction frame, according to the
present disclosure;
[0047] Figure 24 illustrates a location of samples collected for nano-
tomography and
diffraction analysis, according to the present disclosure;
[0048] Figure 25 is a schematic illustrating a CT scanner and a process for
X-ray computed
tomography in accordance with the present disclosure;
[0049] Figure 26 is a graph illustrating a weight average molecular weight
of PET and PET
nanocomposite pellets in accordance with the present disclosure;
[0050] Figure 27 is a graph illustrating an intrinsic viscosity measured
for PET and ultrasound
treated PET, according to the present disclosure;
[0051] Figure 28 is a graph illustrating a comparison of intrinsic
viscosity for PET and PET
nanocomposites, according to the present disclosure;
[0052] Figure 29 is a graph illustrating a viscosity of pellets obtained by
way of in-situ
polymerization in accordance with the present disclosure;
[0053] Figure 30 is a graph illustrating engineering stress-strain curves
for PET and PET-GNP
nanocomposites, according to the present disclosure;
[0054] Figure 31 is a graph illustrating Young's modulus and tensile
strength of
nanocomposite tensile bars in accordance with the present disclosure;
[0055] Figure 32(a) illustrates a PET tensile bar, according to the present
disclosure;
[0056] Figure 32(b) illustrates a PET-15% GNP tensile bar after testing in
accordance with the
present disclosure;
[0057] Figure 32(c) illustrates PET-GNP tensile tubes stretched and a
brittle failure, according
to the present disclosure;
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[0058] Figure 33 is a graph illustrating modulus and tensile strength of
PET and
nanocomposite tensile tubes in accordance with the present disclosure;
[0059] Figure 34 is a graph illustrating engineering stress-strain curves
of nanocomposite
tensile tubes compared with tensile bar, according to the present disclosure;
[0060] Figure 35 is a graph illustrating Young's modulus and tensile
strength of ultrasound
treated PET (horizontal axis - ultrasound amplitude) compared with PET control
in accordance
with the present disclosure;
[0061] Figure 36 is a graph illustrating ultimate tensile strength of
ultrasound treated PET
(horizontal axis ¨ ultrasound amplitude) compared with PET control, according
to the present
disclosure;
[0062] Figure 37 is a graph illustrating modulus and strength of ultrasound
processed
nanocomposites with 2% GNP, according to the present disclosure;
[0063] Figure 38 is a graph illustrating modulus and strength of ultrasound
treated
nanocomposites with 5% GNP compared with PET control and twin-screw compounded
nanocomposite, according to the present disclosure;
[0064] Figure 39 is a graph illustrating Young's modulus and strength data
for in-situ
polymerized PET and nanocomposites in accordance with the present disclosure;
[0065] Figure 39(a) is a table listing tensile strength and specific
strength for nanocomposite
tensile bars, in accordance with the present disclosure;
[0066] Figure 39(b) is a table listing tensile strength and specific
strength for nanocomposite
tensile tubes, according to the present disclosure;
[0067] Figure 39(c) is a table listing tensile strength and specific
strength of nanocomposite
tubes from an ultrasound master-batch, according to the present disclosure;
[0068] Figure 40(a) is a micrograph illustrating voids on a fracture
surface of nanocomposite
tensile bars with 5% GNP weight fraction, according to the present disclosure;
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[0069] Figure 40(b) is a micrograph illustrating voids and a crack
initiation point on a fracture
surface of nanocomposite tensile bars with 10% GNP weight fraction, according
to the present
disclosure;
[0070] Figure 41(a) is a micrograph illustrating a fracture surface of 2%
nanocomposite tensile
tube with a highlighted area showing signs of "ductile fracture," in
accordance with the present
disclosure;
[0071] Figure 41(b) is a micrograph illustrating a failure of the micro
fibril formed from
elongation within the highlighted area of Fig. 41(a), according to the present
disclosure;
[0072] Figure 42(a) is a micrograph illustrating a nanocomposite tensile
bar failure surface at
2% weight fraction, according to the present disclosure;
[0073] Figure 42(b) is a micrograph illustrating a nanocomposite tensile
bar failure surface at
5% weight fraction in accordance with the present disclosure;
[0074] Figure 42(c) is a micrograph illustrating a nanocomposite tensile
bar failure surface at
10% weight fraction, according to the present disclosure;
[0075] Figure 42(d) is a micrograph illustrating a nanocomposite tensile
bar failure surface at
15% weight fraction, according to the present disclosure;
[0076] Figure 43 illustrates ultrasound micrographs of PET and PET
nanocomposite tensile
bars wherein an arrow indicates an injection flow direction, according to the
present disclosure;
[0077] Figure 44 is a graph illustrating GNP weight fraction vs. glass
transition temperature
(Tg), melting temperature (T,71), and crystallization temperature (T,), with
an error on temperature
measurements of 0.5oC in accordance with the present disclosure;
[0078] Figure 45 comprises a left-hand graph illustrating crystallization
half-time of PET
nanocomposites, measured within 0.05 min, and a right-hand graph illustrating
percent
crystallinity of PET nano composites, accordance with the present disclosure;
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[0079] Figure 46 is a graph illustrating crystallization exotherms for PET
and twin-screw
compounded PET nanocomposite pellets, in accordance with the present
disclosure;
[0080] Figure 47 comprises graphs illustrating glass transition and melting
temperatures for
ultrasound treated PET and PET nanocomposite pellets in accordance with the
present disclosure;
[0081] Figure 48 is a graph illustrating melting curves (second heat) of
ultrasound treated PET,
according to the present disclosure;
[0082] Figure 49 comprises a left-hand graph illustrating crystallization
half-time (measured
within 0.05 min) for ultrasound treated PET and PET + 5% GNP pellets, and a
right-hand graph
illustrating crystallinity for ultrasound treated PET and PET + 5% GNP pellets
in accordance with
the present disclosure;
[0083] Figure 50 comprises graphs illustrating crystallization temperature
and percent
crystallinity for in-situ polymerized samples, according to the present
disclosure;
[0084] Figure 51 is a graph illustrating storage modulus of PET and PET
nanocomposites with
respect to angular frequency in accordance with the present disclosure;
[0085] Figure 52 is a graph illustrating shear modulus vs. GNP weight
fraction and a suggested
percolation threshold in accordance with the present disclosure;
[0086] Figure 53 is a graph illustrating storage modulus of ultrasound
nanocomposites
compared with PET and twin-screw nanocomposite in accordance with the present
disclosure;
[0087] Figure 54 is a graph illustrating a dynamic sweep of storage moduli
for different PET
samples, according to the present disclosure;
[0088] Figure 55(a) illustrates a transmission micrograph of 15%
nanocomposite in
accordance with the present disclosure;
[0089] Figure 55(b) illustrates a transmission micrograph of 15%
nanocomposite in
accordance with the present disclosure;
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[0090] Figure 56(a) illustrates a transmission micrograph of 5%
nanocomposite, showing few
layer graphene, in accordance with the present disclosure;
[0091] Figure 56(b) illustrates a transmission micrograph of 5%
nanocomposite, showing few
layer graphene, in accordance with the present disclosure;
[0092] Figure 57(a) illustrates a transmission electron micrograph of 15%
PET-GNP
nanocomposite, according to the present disclosure;
[0093] Figure 57(b) is a binarized micrograph suitable for analyzing
interparticle distances,
according to the present disclosure;
[0094] Figure 58 is a graph illustrating interparticle distance vs. GNP
weight fraction with a
dashed line representing a comparison of experimental data with theoretical
trend in accordance
with the present disclosure;
[0095] Figure 59 is a graph illustrating X-ray diffraction patterns for
GNPs, PET, and
nanocomposite tensile bars in accordance with the present disclosure;
[0096] Figure 60(a) illustrates an X-ray diffraction scan along a cross-
section of a PET tensile
bar, according to the present disclosure;
[0097] Figure 60(b) is a graph illustrating X-ray diffraction patterns of
the line diffraction scan
of Fig. 60(a), according to the present disclosure;
[0098] Figure 61 is a graph illustrating X-ray diffraction patterns at a
multiplicity of depths
within a 3-mm thick 15% nanocomposite tensile bar in accordance with the
present disclosure;
[0099] Figure 62(a) illustrates a reconstructed 3D volume of 15%
nanocomposite with a
boundary size of 240 im x 240 inn x 163 inn, according to the present
disclosure;
[00100] Figure 62(b) illustrates nanoplatelets within the nanocomposite of
Fig. 62(a) indicating
an orientation of platelets along an injection flow direction (Z-axis) in
accordance with the present
disclosure;
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[00101] Figure 63(a) illustrates a sample mounted onto a rotating pin wherein
a cross mark
indicates an injection flow direction, according to the present disclosure;
[00102] Figure 63(b) illustrates a distribution of nanoplatelets from an
inside edge of a 2%
nanocomposite tensile tube in accordance with the present disclosure;
[00103] Figure 64 is a graph illustrating Raman bands corresponding to C-C
stretching for PET
and PET nanocomposites, according to the present disclosure;
[00104] Figure 65 is a graph illustrating a shift in the Raman band
corresponding to C-C
stretching with an increase in GNP weight fraction in accordance with the
present disclosure;
[00105] Figure 66 is a graph illustrating predicted modulus of PET-Graphene
nanocomposites
as compared with experimental results in accordance with the present
disclosure;
[00106] Figure 66(a) is a table listing properties of GNP and PET for
micromechanical model
based predictions in accordance with the present disclosure;
[00107] Figure 67 is a graph illustrating a comparison of nanocomposite
experiment behavior
with theoretical predictions wherein Ell, is a matrix modulus, Er is a GNP
modulus, and Af is an
aspect ratio (diameter/thickness), according to the present disclosure;
[00108] Figure 68 is a graph illustrating load extension curves for ultrasound
treated PET
compared with a PET control in accordance with the present disclosure;
[00109] Figure 69 (a) and (b) is a schematic illustrating a doubling of
nanoplatelets of the same
size affecting a polymer matrix, according to the present disclosure;
[00110] Figure 70 is a graph illustrating an increase in elastic tensile
modulus with respect to
GNP weight fraction in accordance with the present disclosure;
[00111] Figure 71 is a graph illustrating an elastic region of stress-
strain curves for
nanocomposite tensile bars, according to the present disclosure; and
[00112] Figure 72 is a graph illustrating a comparison of Young's modulus for
PET-GNP
nanocomposites with and without ultrasound treatment in accordance with the
present disclosure.
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[00113] While the present disclosure is subject to various modifications and
alternative forms,
specific embodiments thereof have been shown by way of example in the drawings
and will herein
be described in detail. The invention should be understood to not be limited
to the particular forms
disclosed, but on the contrary, the intention is to cover all modifications,
equivalents, and
alternatives falling within the spirit and scope of the present disclosure.
DETAILED DESCRIPTION
[00114] In the following description, numerous specific details are set forth
in order to provide
a thorough understanding of the present disclosure. It will be apparent,
however, to one of ordinary
skill in the art that the invention disclosed herein may be practiced without
these specific details.
In other instances, specific numeric references such as "first process," may
be made. However,
the specific numeric reference should not be interpreted as a literal
sequential order but rather
interpreted that the "first process" is different than a "second process."
Thus, the specific details
set forth are merely exemplary. The specific details may be varied from and
still be contemplated
to be within the spirit and scope of the present disclosure. The tern'
"coupled" is defined as
meaning connected either directly to the component or indirectly to the
component through another
component. Further, as used herein, the terms "about," "approximately," or
"substantially" for
any numerical values or ranges indicate a suitable dimensional tolerance that
allows the part or
collection of components to function for its intended purpose as described
herein.
[00115] In general, the present disclosure provides a composition and method
for graphene
reinforced polyethylene terephthalate (PET). Graphene nanoplatelets (GNPs)
comprising multi-
layer graphene are used to reinforce PET, thereby improving the properties of
PET for various new
applications. Master-batches comprising polyethylene terephthalate with
dispersed graphene
nanoplatelets are obtained by way of compounding. The master-batches are used
to form PET-
GNP nanocomposites at weight fractions ranging between 0.5% and 15%. In some
embodiments,
PET and GNPs are melt compounded by way of twin-screw extrusion. In some
embodiments,
ultrasound is coupled with a twin-screw extruder so as to assist with melt
compounding. In some
embodiments, the PET-GNP nanocomposites are prepared by way of high-speed
injection
molding. The PET-GNP nanocomposites are compared by way of their mechanical,
thermal, and
rheological properties so as to contrast different compounding processes.
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[00116] Polyethylene terephthalate (PET) is an aromatic semi-crystalline
polyester. PET is
synthesized through condensation polymerization, using Terephthalic acid (TPA)
and Ethylene
Glycol (EG), or Dimethyl Terephthalate (DMT) and Ethylene Glycol (EG) as raw
materials. A
multi-step polymerization process is used in the manufacture of PET so as to
achieve a desired
molecular weight and to minimize a formation of byproducts (e.g.,
Acetaldehyde). A molecular
structure of PET is shown in Fig. 1. As will be appreciated, a presence of a
rigid aromatic ring in
the molecular chain gives rise to high melting and glass transition
temperatures, as well as
stiffening the polymer. Further, the rigid aromatic ring also gives the
molecule a nearly planar
arrangement in the crystal structure. A combination of physical properties and
chemical inertness
makes PET suitable for applications such as fibers, packaging, and engineering
molding.
[00117] Although PET is limited in terms of crystallization rate and barrier
performance, PET' s
relatively low price drives an interest in improving the material properties
of PET by way of adding
fillers and reinforcements. Nanomaterials provide an advantage of reinforcing
PET while
minimizing a change in density of the obtained composite material.
Nanoreinforcements
[00118] Nanoreinforcements generally are categorized into three different
groups, based on
their geometry, namely: nanoparticles, nanotubes and nanoplatelets.
Nanoreinforcements are
advantageous over larger reinforcements. It will be recognized that the
smaller the particles, the
stronger and more effective the particles are in reinforcing the matrix as
compared with larger
counterparts. Another advantage is the available surface area for a unit
volume. In the case of
spherical particles, for example, a ratio of the surface area to volume is
inversely proportional to
the particle radius. Fig. 2 illustrates an increase in interface for different
types of reinforcements
ranging in size from microscale to nanoscale. As indicated in Fig. 2, a
surface energy available
per unit area will be high for nanoparticles, thereby making them chemically
active.
[00119] It will be appreciated that the selection of nanoreinforcements
depends on many factors
such as the polymer used, an intended application, target properties, a
desired form of interaction
with the polymer, material handling concerns, a processing method, as well as
cost. It will be
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further appreciated that the shape of the nanoreinforcement influences the
characteristics of the
polymer nanocomposite.
[00120] Nanoparticles may be classified as organic or inorganic, based on
their chemistry. A
number of nanoparticles have been used in polymer nanocomposites, such as
organoclays (MMT),
metal nanoparticles (e.g. Al and Ag), metal oxides (e.g. A1203, ZnO, and
silica), cellulose
nanocrystals, and carbon derivatives (CNT's, Fullerenes, Graphite oxide, and
Graphene).
Carbon Nanoreinforcement and Graphene
[00121] Carbon is an interesting element of the periodic table possessing
unique hybridization
properties and an ability to manipulate its structure. Carbon finds
applications in several industries
and processes commonly in the form of graphite, amorphous carbon, and diamond.
At the
nanoscale, carbon materials are also interesting, showing unique properties
and structures, as
shown in Fig. 4, such as fullerene, carbon nanotubes (CNTs), and graphene.
[00122] Graphene is defined as a single layer of carbon atoms with a two-
dimensional structure
(sp2 hybridization, planar hexagonal arrangement with a C¨C bond distance of
0.142 nm). A
thickness of a single graphene sheet is estimated to be substantially 0.335
nm. One of the first
two-dimensional materials available, graphene has a potential to replace many
contemporary
materials used for different applications. During the course of graphene
research, researchers have
developed different graphene-based materials, such as single layer graphene
sheets (SLGS), few-
layer graphene (FLG), multi-layer graphene (MLG), and exfoliated graphene
platelets.
[00123] Graphene is superior over other carbon-based nanoreinforcements, such
as CNTs,
CNFs, and expanded graphite (EG), in terms of its aspect ratio, flexibility,
transparency, thermal
conductivity and low coefficient of thermal expansion (CTE). The density of
single layer graphene
was calculated at 0.77 mg 111-2. Graphene is regarded as the strongest
material with appreciable
size. A Young's modulus of 1.02 0.03 TPa (0.2 TPa for 4130 steel) and a
strength of 130 10
GPa (0.7 GPa for 4130 steel) have been measured for a single layer graphene
sheet suspended over
open holes, by means of an atomic force microscope (AFM) nanoindentation
technique. Graphene
is found to exhibit a negative coefficient of thermal expansion, a = ¨ 4.8 1.0
x 10-6 K-1 through
the 0-300 K temperature range and a very high thermal conductivity (K) of 3000
W mK-1
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comparable to that of CNTs. Further, graphene sheets have been found to be
hydrophobic and
have a surface energy at room temperature of 46.7 mJ
[00124] The abovementioned properties are for a high quality single layer
graphene sheet.
Properties of multi-layer graphene are different than the properties of single
layer graphene. Thus,
the number of layers ("n") comprising the graphene influences the properties
of the graphene. A
single layer graphene sheet exhibits up to 97.7% transparency (2.3%
absorption) and decreases
linearly as the number of layers increases. It is been shown that the thermal
conductivity of
graphene drops by more than 50% as the number of layers increases from 2 to 4
and is comparable
to that of bulk graphite when the number of layer is greater than 8. Further,
it has been found that
the modulus of graphene sheets decreases with an increase in temperature and
with an increase in
13C isotope density, but increased with an increase in the number of layers.
It will be appreciated,
however, that structural mechanics based atomistic modeling of multi-layer
graphene structures,
molecular simulation of covalent and van der Waals interactions between
layers, and experimental
measurements indicate a decrease in the modulus with an increasing number of
layers. Mechanical
properties of graphene nanoplatelets such as stiffness and Poisson's ratio
have been shown to
decrease with an increase in the number of layers, based on molecular dynamics
simulations. The
stiffness of the nanoplatelets comprising five layers has been estimated to
decrease by 15% as
compared to single layer graphene, and the properties of the graphene differ
based on orientation.
It has been shown that an effective Young's modulus of multi-layer graphene
comprising 10 layers
is substantially 380 GPa, which is less than that of a graphite crystal. The
effective Young's
modulus is determined based on the stress transfer efficiency between layers
for a multi-layer
graphene. The effective Young's modulus deviates from the modulus of a single
layer graphene
when the multi-layer graphene is of more than 3 layers, at which point the
core layer(s) will not be
in contact with the polymer.
[00125] Single layer graphene may be obtained by way of "top down" or "bottom
up"
approaches. Separation of graphene sheets from graphite through mechanical
cleavage is a "top
down" approach. Although graphene obtained from this method is pristine and
useful for testing
purposes, it is not practical for acquiring significant quantities of
graphene. Alternatively,
graphene may be prepared by way of "bottom up" approaches wherein chemical
methods are used,
such as chemical vapor deposition (CVD), epitaxial growth, as well as
synthesis through colloidal
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suspension. Further, graphene may also be made from CNTs by way of chemical
etching and from
flash reduction of graphite oxide. The approach used to obtain graphene
influences the physical
properties of the graphene, thereby enabling graphene to be targeted for
different applications, as
shown in Fig. 3.
Processing of Nanocomposites
[00126] Composite manufacturing is an extensively studied field with a number
of processes
available based on the size and application of the final product.
Nanocomposite processing
involves a process for dispersion of the nanoreinforcement and forming
processes for the intended
final application. A feasibility of nanocomposites largely depends upon cost,
an availability of
nanoparticles, and suitable manufacturing processes. Manufacturing techniques
such as: injection
and compression molding, layer-by-layer (LBL) manufacturing, in-situ micro-
emulsion
polymerization, and spinning have been used for polymer nanocomposites. As
will be appreciated,
selection of the manufacturing process depends on the matrix resin and type of
the nanoparticles
to be used. It will be further appreciated that injection molding is the most
important of all plastic
processing techniques because of its, speed, scalability, and tolerance to a
wide range of materials.
Methods attempted for achieving uniform dispersion of nanoreinforcements in a
polymer are
discussed in the following section.
Dispersion of Nanoreinforcements
[00127] Achieving unifoun and homogenous dispersion, or an "exfoliated" state,
of
nanoreinforcements is vital for the success of polymer nanocomposites.
Nanomaterials possess a
high surface energy per unit area, and thus they tend to folin agglomerates so
as to minimize this
energy. The tendency to agglomerate makes it difficult to maintain the
nanomaterials' nanoscale
effective dimensions and disperse the nanomaterials into a polymer matrix.
Dispersion of
nanoreinforcements into the molten polymer depends on factors, such as
viscosity of the melt,
wetability of the reinforcement, energy imparted through the mixing process,
including breaking
agglomerates, and efficiency of the mixing process. Dispersion methods can be
broadly
categorized as mechanical-based and chemical-based. Several dispersion methods
have been
investigated under the mechanical-based category, such as melt compounding,
master-batch
processing, ultrasound-assisted compounding, chaotic advection blending, solid-
state shear
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pulverization (SSSP), solid state ball milling (SSBM), and acoustic mixing.
These dispersion
methods may be further categorized as "melt mixing" or "solid state mixing."
[00128] Melt compounding is the most commonly employed technique for
dispersing
nanoreinforcements in thermoplastic polymers. As described herein,
nanoreinforcements were
dispersed into a molten polymer by way of a mixing action of a single or twin-
screw extruder.
Solid state shear pulverization (SSSP) is another mechanical mixing technique,
developed for
blending immiscible polymers. However, distortion of the nanoplatelets during
the screw mixing
processes is of concern as that can reduce their effectiveness. Some other
techniques mentioned
above involving solid state mixing are SSBM and acoustic mixing. In SSBM the
nanoparticles
and the polymer mixture are milled to fine powders and then used as an input
for a secondary
process. Acoustic mixing is based on a generation of a unifolin shear field
throughout the mixing
chamber for high efficiency mixing.
[00129] A chemical approach to prevent agglomeration is to modify the surface,
or
functionalize the surface, of the nanoparticle, which reduces the surface
energy, changes their
polarity, and thereby prevents agglomeration. Through functionalization, the
surface of the
nanoparticle is covered with ions or molecules (i.e., surfactants) that are
compatible with a specific
polymer. As every polymer has a different chemistry and structure, choosing a
correct
functionalization is important.
[00130] Moreover, there are solvent mixing techniques such as sol-gel
processing, solution
mixing, sonication, shear mixing, and high speed mixing. These techniques are
mainly useful for
working with thermosetting resins and low temperature thermoplastics. They are
mainly reserved
for batch wise processing and pose handling and consistency issues for large
scale processing.
[00131] In a twin-screw extruder, the polymer melts between two rotating
screws and the
housing by undergoing shear deformation. As the nanoplatelets are bound with
Van der Waals
forces, they can be separated by an application of shear forces during mixing.
Shearing and mixing
of the reinforcements and the polymer melt can be achieved through mixing
screw's possessing a
large length-to-diameter ratio (L/D) and by an application of different screw
elements. Taking
advantage of this, twin-screws have been used for decades in compounding.
Since their inception
into polymer processing, different types of twin-screw extruders have been
developed. Basic
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differences are based on the shape and direction of screw rotation. There are
co-rotating, counter-
rotating, and intermeshing screws. In order to increase the efficiency of
mixing, segmented screws
with different replaceable elements (e.g. kneading elements) have also been
developed. It has
been found that nanocomposites show similar performance irrespective of the
type of screw
rotation, but using counter-rotating screws gives rise to better dispersion.
Further, it has been
found that the flow velocity in a co-rotating screw is higher at the screw
tip. This corresponds to
a higher shearing rate and is considered good for mixing.
[00132] As will be appreciated, the melt compounding method is the most
convenient and
industrially promising process to produce polymer nanocomposites. Master-batch
mixing is a
multi-stage approach whereby already mixed polymer-nanoreinforcement pellets
are melted again
and mixed at the same or reduced loading rate. Those skilled in the art will
recognize that master-
batch mixing is commonly used during polymer processing for adding specialized
additives or
dyes during primary processes such as injection molding and extrusion. Master-
batch pellets are
prepared using the same or a compatible base resin and the additive at high
loading rates. Further,
it has been found that nanocomposites from the master-batch process are
superior to those obtained
by way of melt processing. Having the secondary mixing helped in improving the
performance of
the nanocomposites through increased dispersion.
[00133] In case of the ultrasound-assisted extrusion, along with twin-screw
mixing, additional
energy is applied in the form of ultrasound waves. Ultrasound energy is used
for making
thermodynamically unstable emulsions and as an initiator for polymerization
reactions. As will
be appreciated, nanoparticle dispersion may be improved by way of combining
ultrasound with
twin-screw extrusion. Ultrasound energy applied to the polymer¨nanoparticle
mixture will lead
to cavitation, due to a development of a high temperature zone locally. As the
bubbles grow, they
help in breaking and separating the nanoparticles into the polymer matrix.
[00134] Dispersing single layer graphene into a polymer has intrigued
researchers for quite
some time. Graphene generally is difficult to wet and exhibits a lower
adhesion energy compared
to graphite and graphene oxide. In order to improve the adhesion and
reactivity of graphene for
certain applications, graphene sheets may be functionalized on both surfaces.
Functionalized
graphene is especially useful for bio-sensing applications. In some studies,
an effect of
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fluorination on graphene sheets has been researched. The resulting
fluorographene was found to
be an insulator, with similar theimal and mechanical behavior as that of
graphene.
[00135] Solvent dispersion of graphene gained much attention through
successful dispersion of
graphene in organic solvent N-Methyl-2-pyrrolidone (NMP). In some studies, an
effectiveness of
different solvents in exfoliation of graphene through sonication has been
researched. It has been
shown that graphene can be dispersed in water at high concentrations (0.7
mg/ml) by using
surfactants (Triton X-100) and a combination of low power and high power
sonication. As
graphene is hydrophobic, application of a dispersant with hydrophobic and
hydrophilic ends will
help in stabilizing the dispersion in an aqueous solvent. Strong 7E-7t
interaction between the
benzene ring in the surfactant (Triton X-100) and the aromatic structure of
graphene sheets aid in
the dispersion. Aqueous dispersed graphene obtained through a size selective
approach (i.e.,
selecting uniform diameter graphene through centrifuge) appears to be a
promising direction for
the preparation of polymer nanocomposites. Nevertheless, the cost and
complexity of the approach
may limit this route for commercial applications.
[00136] It has been found that the wetability and work of adhesion of graphene
is higher with
ethylene glycol (EG) as compared with water. Furtheimore, reduced graphene
oxide can be well
dispersed in ethylene glycol due to a presence of oxygen-containing functional
groups. Ethylene
glycol being one of the raw materials for the polymerization of PET makes
solution dispersion a
reasonable route for the development of nanocomposites.
PET Nanocomposites
[00137] As stated earlier, PET nanocomposites are being pursued with an
intention of
improving their properties and expanding to new applications. Currently, other
nanomaterials are
already being used and dispersed in the polymerization of PET. For example, as
shown in Fig. 5,
carbon black nanoparticles, having an average diameter 400 nm, are used at 6
ppm, or 0.0006%,
for improving the heat absorption capacity of PET. Carbon black dispersion
achieved through in-
situ polymerization, offers an energy savings even at this low 6 ppm loading.
Investigating
nanocomposite preparation through the in-situ approach, at a more significant
weight fraction may
help in understanding the effectiveness of this approach.
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[00138] High melting temperature and melt viscosity of PET make melt-
compounding a
relevant technique for the preparation of nanocomposites. As described herein,
the addition of
graphene to PET has been found to improve the mechanical, barrier, thermal,
and conductive
properties of PET. It is envisioned, however, that improving the dispersion of
graphene and
understanding the strengthening mechanisms at high loadings will lead to new
applications, such
as by way of non-limiting example, strain monitoring, electromagnetic
shielding, lightning strike
protection, reduced moisture absorption, and the like.
EXPERIMENTAL DETAILS
[00139] In some embodiments, commercially available PET of molecular weight
¨ 84,100
g/mol (0.81 dl/g intrinsic viscosity (I.V.)) may be obtained in the form of
pellets. As received, the
PET pellets are semi-crystalline, which may be verified by way of differential
scanning
calorimetry (DSC). As will be appreciated, PET is hygroscopic, and a presence
of moisture in the
polymer melt will lead to a loss of molecular weight through chain scission
(hydrolysis of ester
bonds). Therefore, the PET may be advantageously dried for 4-6 hours at 170 C
before each
process so as to minimize polymer degradation.
[00140] In some embodiments, commercially available graphene may be obtained
in the form
of graphene nanoplatelets (GNPs), having two different average surface areas.
In some
embodiments, graphene nanoplatelets (GNPs) with an average diameter of 5 Jtm,
thickness around
6 to 8 nm and an average surface area of 120-150 m2/g, (xGnPO-M-5 grade) may
be used in the
preparation of nanocomposites. In some embodiments, nanoplatelets with an
average diameter of
2 [tin, average surface area of 750 m2/g (xGnPO-C-750 grade) may be used for
in-situ
polymerization. In some embodiments, the nanoplatelets are initially in a dry
agglomerated
powder form, wherein each agglomerated platelet comprises several
nanoplatelets, as shown in
Fig. 6(a)-(b). As will be appreciated, the nanoplatelets generally are not
uniform across their
lengths and comprise zig-zag edges. Figure 7 illustrates a chemical structure
of the nanoplatelets.
The nanoplatelets are comprised of 99.5% carbon with very low oxygen and
hydrogen present in
the form of carboxyl and hydroxyl groups on the edges. It will be recognized
that the carboxyl
and hydroxyl groups are formed due to the exposure of raw carbon during the
fracture of the
platelets. In some embodiments, the nanoplatelets may be prepared by way of a
procedure wherein
acid intercalated graphite flakes were expanded by way of microwave
processing, as described in
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a Doctor of Philosophy Dissertation, entitled "Graphite Nanoreinforcements in
Polymer
Nanocomposites," Chemical Engineering and Materials Science, 2003, by H.
Fukushima, the
entirety of which is hereby incorporated by reference herein.
Preparation of PET-GNP Nanocomposites
[00141] In some embodiments, graphene nanoplatelets may be dispersed into the
PET matric
without forming agglomerates by compounding PET-Graphene master-batches
through twin-
screw and ultrasound-assisted twin-screw processes. In one embodiment,
graphene nanoplatelets
(GNPs) and PET resin were compounded into PET-xGnP master-batch pellets using
a Krauss
Maffei ZE-25 UTX laboratory extruder having co-rotating screws. Two different
sets of master-
batch pellets at 2%, 5%, 10% and 15% weight fraction were compounded using
this process. In
each set, 5.4 kgs (12 lbs) of master-batch was prepared for each of the weight
fractions.
[00142] In some embodiments, ultrasound may be used to assist twin-screw
compounding. In
one embodiment, PET-graphene nanoplatelets were processed using an ultrasound-
assisted twin-
screw extrusion system. The PET pellets were dried overnight in oven at 80 C
to remove moisture
and then compounded with graphene nanoplatelets at 5% weight fraction. The PET
and graphene
nanoplatelets were compounded using a co-rotating twin-screw micro-compounder
equipped with
an ultrasound horn operating at 40 kHz, as shown in Fig. 9. The ultrasound
horn was positioned
in the barrel region at a distance of 14.5 cm from the die entrance. The
vertical position of the
horn tip was adjusted such that it is in contact with the polymer melt. A flow
rate of 0.9 kg/hr (2
lbs/hr) was maintained throughout the process, with a set screw speed of 200
RPM, resulting in a
residence time of 9.2 seconds in the ultrasound treatment zone.
[00143] Combined with the baseline composite master-batch, a total of four
sets of master-
batches were prepared including different ultrasound amplitudes: no ultrasound
(0 USM), 3.5 um
(3.5 USM), 5 um (5 USM), and 7.5 i_tm (7.5 USM). Further, to understand the
effect of ultrasound
treatment on PET alone, pure PET (no reinforcement) was also processed under
the same
conditions. Fig. 8 illustrates sizes and dimensions of several exemplary
embodiments of
compounded PET-Graphene in pelletized faun.
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[00144]
In-situ Polymerization
[00145] In some embodiments, in-situ polymerization may be employed in the
preparation of
polymer nanocomposites. As will be appreciated, in-situ polymerization
generally comprises two
steps. The first step comprises intercalating nanoscale reinforcements in the
solution phase using
compatible polymer precursors or solvents. In the second step, polymerization
is undertaken using
the nanoplatelet intercalated solution. Dispersing the nanoplatelets into a
chemically compatible
and low viscosity material is considered to be more efficient compared to
direct mixing with highly
viscous polymer melt.
[00146] As will be appreciated, since ethylene glycol (EG) is one of the raw
materials for the
polymerization of PET, EG may be advantageously used as a solvent for
dispersing graphene
nanoplatelets. In one embodiment, EG of reagent grade, having a 99% purity,
was used as a
solvent for dispersing graphene nanoplatelets. Graphene nanoplatelets were
added to the EG at a
concentration of 1 mg/ml (i.e., 0.1% weight fraction) and sonicated using a 40
kHz bath sonicator.
EG-GNP solutions were sonicated for 106 hours so as to ensure a homogenous
dispersion, as
depicted in Fig. 10. During the sonication process, solution beakers were
covered with aluminum
foil to prevent exposure to atmospheric oxygen. Dispersions were prepared
using both low (120
m2/g) and high (750 m2/g) surface area graphene nanoplatelets.
[00147] In one embodiment, in-situ polymerization of graphene nanoplatelets
dispersed in
ethylene glycol and dimethyl terephthalate was attempted using a 1 kg
polymerization reactor.
PET polymerization was performed through a two-step reaction. The first step
is an ester
interchange reaction (El), wherein the monomer is formed. In the second step,
the polymer is
formed through a polycondensation reaction (PC). Experimental setups used
along with the
undergoing reaction at each step are described below.
[00148] Fig. 11 is a schematic illustrating an exemplary embodiment of a
reactor and methanol
collection setup for performing the ester interchange reaction. In the
embodiment illustrated in
Fig. 11, powdered dimethyl terephthalate (DMT) was used for the
polymerization. EG with
dispersed GNPs and the powdered DMT were charged into the reactor under
nitrogen purge at a
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2.3:1 moles ratio, with an excess of EG. The catalysts for the ester
interchange reaction,
manganese acetate (Mn(CH3C00)2), and for the polycondensation reaction,
antimony trioxide
(Sb203), were added to the batch at 82 ppm and 300 ppm respectively, and
heated to 175 C under
constant stirring. As the batch temperature approached about 170 C, methanol
collection began
indicating that the ester interchange reaction had started and then the
nitrogen purge was closed.
There onwards the batch temperature was increased in steps of 15 C until the
temperature reached
235 C. As the reaction progressed, the temperature within the gooseneck
condenser increased
from room temperature to above 60 C. Once the methanol collection reached the
theoretical yield,
300 ml in this case, and the gooseneck condenser temperature dropped to below
60 C, the ester
interchange was considered finished. The gooseneck condenser was removed and
polyphosphoric
acid (H3PO4) was added at 38 ppm to the batch so as to terminate the ester
interchange reaction.
Fig. 12 illustrates a formation of ester interchange through the ester
interchange between DMT
and EG. The entire ester interchange reaction took around 3 hours to finish.
[00149] Fig. 13 is a schematic illustrating an exemplary embodiment of a
reactor and an excess
EG collection condenser setup for performing the polycondensation reaction.
During the
polycondensation reaction, the reactor temperature was increased to 285 C and
maintained under
vacuum (30 in Hg) until PET of a desired viscosity was obtained. Isophthalic
acid (C6H4(COH)2)
and stabilized cobalt were added at 20 grams and 65 ppm, respectively, to the
batch at a beginning
of the polycondensation reaction. It will be appreciated that isophthalic acid
limits the crystallinity
of PET, thus making the PET easier to process. The stabilized cobalt was added
so as to control a
final color of the PET. As illustrated in Fig. 14, during the polycondensation
reaction, the
molecular weight of PET increases and EG is released. During the
polycondensation reaction,
released EG was collected in a round flask and solidified using dry ice so as
to prevent the EG
from flowing into a vacuum pump. As will be appreciated, a change in the
viscosity of the batch
with increasing PET chain length will affect the stirring current. Thus, as
the reaction progressed,
an electric current passed to the stirrer was monitored for change at 15-
minute intervals. Once no
change in the electric current passed to the stirrer was detected at two
consecutive readings, the
reaction was stopped by cutting the vacuum. The resultant polymer melt was
then extruded from
an opening at the bottom of the reactor into an ice water bath and pelletized
using a strand chopper.
Fig. 14(a) illustrates reaction times and yields for three batch
polymerizations, including one
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control batch without graphene nanoplatelets that were performed by way of the
setups illustrated
in Figs. 11 and 13.
Injection Molding of Nanocomposites
[00150] In some embodiments, nanocomposite master-batches may be injection-
molded to
different final nanoplatelet loading fractions so as to facilitate
investigating their microstructural,
mechanical and thermal characteristics. In one embodiment, three different
injection molding
presses were used, comprising an oil cooled molder, a water cooled molder, and
a micro injection
molder. PET-graphene nanoplatelet master-batches obtained from the compounding
processes,
described above, were used for molding nanocomposites at different loading
fractions. The oil
cooled injection molding unit was used for molding nanocomposites at 2%, 5%,
10% and 15%
GNP weight fractions from master-batches (compounded pellets were injection
molded with no
dilution of graphene concentration using pure PET). Tensile bars were molded
with barrel
temperatures in the range of 260 C to 280 C. A standard tensile bar mold,
following ASTM D
638 type I specifications, was used.
[00151] Signs of crystallization, indicated by an opaque core, were observed
in the injection
molded PET, due to a slow rate of cooling. In another embodiment, a HyPET 90
RS45/38 injection
molding system which is designed for PET was utilized. Injection molding was
performed offsite
at a Niagara Bottling LLC, facility in Ontario, California. The HyPET 90
RS45/38 injection
molding system has a 90 ton clamping force and comprises a 38 mm screw
diameter and a chilled
water cooled mold. This enables processing of PET at higher cooling rates so
as to retain the
amorphous microstructure.
[00152] Moreover, a custom mold was developed so as to keep the injection
molding of the
nanocomposite similar to industry standard for processing PET. A tube specimen
prepared using
the custom mold, shown in Fig. 15, is designed for ease of mechanical testing.
As shown in Fig.
15, the tube specimen comprises a large gauge length with a uniform cross-
section. Thus, the
custom mold makes parts comprising a relevant size and processing window
(i.e., injection
pressures and cycle times) that are typical of industrial scale parts.
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[00153] Using the nanocomposite pellets obtained from the aforementioned
methods, samples
for mechanical testing were injection molded at different GNP concentrations.
For the purpose of
testing nanocomposites with low GNP weight fractions, the master-batch was
diluted by mixing
with PET and injection molded into nanocomposites with as low as 0.5% weight
fraction. Final
weight fractions of the nanocomposites were verified by measuring the
percentage of pellets in the
images collected from feed throat, as shown in Figs. 16(a)-(b). Upon using the
dimensions of the
pellets, as listed in Fig. 8, the actual weight fractions were calculated.
Nanocomposites from each
process run were collected for characterization studies, after the process was
stabilized.
Stabilization occurs when injection pressures and cycle time are steady for
more than 10 min. Fig.
16(c) presents the injection molded nanocomposite weight fractions associated
with each master-
batch.
Process Optimization
[00154] Polymer processing through injection molding is dependent on several
variables,
including barrel temperatures, injection pressure, hold and back pressures,
fill time, cooling time,
and the like. As will be appreciated, balancing all of these variables is
necessary to have a part
free of crystallinity and defects, such as voids. At the start of each process
run, the barrel was
flushed with baseline material to remove any residual material from previous
tests. It will be
recognized that flushing within baseline material enables starting the
processing with known
conditions and optimizing them as the PET-master-batch mixture occupies the
barrel.
[00155] The addition of graphene nanoplatelets affects the melt viscosity of
PET, and this will
reflect on fill pressures. It was observed that a maximum fill pressure
decreased when processing
the ultrasound master-batch, as shown in Fig. 16(d), while a hold pressure was
the same. As will
be appreciated, the hold pressure is important for keeping the mold closed
while the material
solidifies. Another important process variable is back pressure, which helps
homogenize the
material and remove voids from the melt. Effectiveness of the process, mixing
of PET, and the
master-batch inside the barrel can be checked through visual inspection. For
samples with lower
GNP weight fraction, visual signs of poor mixing include dark spots, marks,
and flow streaks, as
shown in Fig. 17.
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Micro-Injection Molding
[00156] In some embodiments, tensile samples may be prepare using a micro-
injection system
for the purpose of inspecting the effect of ultrasound treatment on PET
mechanical properties and
evaluating the improvement from graphene dispersion through ultrasound without
dilution. In one
embodiment, the tensile samples were prepared using a 5.5 cc capacity micro-
injection molding
unit in combination with a 5 cc micro compounding unit, as shown in Figs.
18(a)-(b). The micro-
injection molding unit of Figs. 18(a)-(b), comprising a mold shown in Fig.
19(a), was used for the
preparation of tensile bars shown in Fig. 19(b). The micro-compounder unit
equipped with a co-
rotating twin screw was used to melt the pellets and provide a homogenous melt
mixture, as
described herein. A transfer device shown in Fig. 18(b), was used to transfer
the polymer or the
nanocomposite melt from the compounder to the injection molder. The injection
molder injected
the polymer material into a conical mold by way of a plunger connected to high
pressure air (13.8
bar). As will be recognized, the micro-injection system provides control of
the mold temperature,
injection pressure, hold pressure, injection time, and hold time.
[00157] In one embodiment, a dual dog bone mold, shown in Fig. 19(a), was
designed according
to the ASTM D 638 Type V specimen L/D ratio for the gauge section, with a fill
volume of 2.1 cc.
During the compounding process, the material was heated to 270 C and
homogenized by opening
a recirculation valve for 1 min, after which the melt was collected into the
transfer device. The
tensile bars were made using an aluminum mold at room temperature. The
relatively large volume
of the aluminum mold acts as a heat sink and allowed for cooling of the
polymer melt during
injection. Fig. 19(c) lists the injection process parameters used for making
the PET nanocomposite
tensile bars.
[00158] In total, five different material sets, comprising PET control,
ultrasound treated PET,
nanocomposites pellets with 5% GNP weight fraction from twin-screw mixing,
ultrasound assisted
twin-screw mixing, and materials from in-situ polymerization, were processed
using the micro-
compounding system, and tensile bars were obtained for mechanical testing. In
the case of
nanocomposites, different mixing time periods were also investigated to
understand the effect of
mixing time on the nanocomposite properties. All the materials were dried in
small quantities (30
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grams) at 170 C for 2 hours in an oven before processing so as to avoid
degradation due to the
presence of moisture, or a drop in viscosity due to over-drying.
CHARACTERIZATION OF NANOCOMPOSITES
[00159] Comparison of the densities between the injection molded
nanocomposites will help in
identifying the difference in the samples due to process defects (e.g.,
voids). Relative densities
can be determined based on Archimedes' principle, using the following
equation:
m
P = Po
(1)
m¨ffi
[00160] Where, m is the mass of the sample in air, T71, is the mass of the
sample in liquid medium,
and po is the density of the medium used (i.e., water).
[00161] Amorphous PET has a density of 1335 kg/m3. PET a semi-crystalline
polymer, exhibits
a range of densities based on crystallinity. The theoretical density of the
amorphous
nanocomposite can be calculated using the relative density of PET (1335 kg/m3)
and GNPs (2200
kg/m3). Crystallinity of the control (PET) and nanocomposite samples can be
evaluated using the
equation given below.
xc = ( Pc )(Psample¨Pa)
(2)
Psample k, Pc¨Pa i
[00162] Where, X, is the crystallinity of the sample, pa is the density for
amorphous PET, pc is
the density for crystalline PET (1455 kg/m3), and nsample is the density of
the composite.
,
[00163] PET is known to undergo chain scission under high shear at melt
temperatures. Further,
the effects of ultrasound treatment on PET have not been previously
investigated. Therefore, to
evaluate the change in molecular weight of the ultrasound treated PET and PET
nanocomposite,
Gel Permeation Chromatography (GPC) was performed. Hexafluoroisopropanol
(HFIP) was used
as a solvent for dissolving PET at room temperature. For the composite
pellets, the nanoplatelets
were filtered out after the polymer was dissolved. GPC measurements were
performed at Auriga
Polymers. Polymer dissolved in the solvent (5 mg/ml) was pumped at a constant
flow rate through
a GPC column with specific pore sizes. The time taken by the polymer molecules
in a swollen
state to pass through the column (retention time) is based on the size of the
molecules. While the
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polymer solution passes through the column, the elution volume for the
different fractions (same
molecular weight), identified using a refractive index detector, was recorded.
Comparing this
elution volume against Polystyrene standards of known molecular weight, the
average molecular
weight for PET samples was obtained.
[00164] Intrinsic viscosity (I.V.) of PET and ultrasound treated PET pellets
was measured at
the Auriga Polymer facility, using their proprietary solvents that were
calibrated with respect to
the solvents recommended in ASTM D4603 standard. After dissolving the polymer
pellets in
solvent, that solution was passed through a glass capillary viscometer and the
flow time for the
solution as it drops from the higher to lower calibration mark (as shown in
Figure 20) was recorded.
The ratio of the average flow times for solution to the solvent gave the
relative viscosity (nr) of
the polymer. Intrinsic viscosity of the polymer was calculated using the
following equations:
rir = t/t0
(3)
11 = 0.25(l7r ¨1 + 3 lnrh.)/C
(4)
[00165]
Where, rir is the relative viscosity, t is the average solution flow time (s),
to is the
average solvent flow time (s), n is the intrinsic viscosity (dL/g), and C is
the polymer solution
concentration (g/dL).
[00166] Using the intrinsic viscosity (I.V.) data obtained by the
abovementioned procedure and
weight average molecular weight data from the GPC technique, Mark-Houwink
parameters for
relating PET I.V. to M were refined and used to calculate the viscosities for
ultrasound treated
nanocomposites:
[ii] = KM a
(5)
[00167] Where, 77 is polymer intrinsic viscosity (dL/g), M is the average
molecular weight
(g/mol), 'K' and 'a' are Mark-Houwink constants. While using weight average
molecular weight,
'K' and 'a' are respectively taken as 0.00047 and 0.68.
[00168] Nanocomposite samples with two different geometries were obtained from
the
injection molding process: tensile bars and tensile tubes. Both the
geometries, tensile bars and
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tubes were tested using a universal materials tester at a cross-head speed of
5 mm/min, following
the ASTM D 638 standard. A non-contact laser extensometer was used for
recording strain. The
laser extensometer records the displacement based on the reflections from self-
reflective tape, used
to mark the gauge length on the test samples, as shown in Fig. 21(a). Strain
values from the laser
extensometer and load from the load cell were simultaneously recorded at an
interval of 100 ms.
For the purpose of testing the nanocomposite tubes, a custom fixture shown in
Figs. 21(b) - 21(d),
was used. A minimum of 5 samples were tested for each process condition.
[00169] Differential scanning calorimetry (DSC) of the PET and nanocomposite
samples was
performed to understand the effect of graphene on thermal properties (glass
transition,
crystallization and melt temperatures) of PET. Thermographs of nanocomposites
were acquired
using a differential scanning calorimeter. Nanocomposite samples were heated
from ambient
temperature to 300 C at 10 C/min and held at 300 C for 1 min (first heating
cycle), then cooled
to 25 C at 10 C/min and held at 25 C for 1 min (first cooling cycle), and then
finally reheated to
300 C at 10 C/min (second heating cycle) under a nitrogen atmosphere.
Ultrasound treated PET
pellets were also analyzed for a change in thermal properties.
[00170] From the first heating cycle, melting parameters (temperature, heat of
fusion) and heat
of crystallization were obtained for determining the crystallinity PO. Melt
crystallization
temperature (ID and on-set temperature (T07,) were obtained from the first
cooling cycle, to
determine the crystallization half-time (t112). Crystallinity can be
calculated using the below
equation:
x = FAHf-mcd ( i )
x100
(6)
c
L Mg I 1_--wf
[00171] Where, Alif is the heat of fusion, Alicc is the heat of
crystallization (cold
crystallization), Ali is the heat of fusion for 100% crystalline polymer, for
PET - 140.1 J/g, and
wf is the weight fraction of the reinforcement phase in the nanocomposites.
[00172] Crystallization half-time was deteunined using the following equation:
(Ton-T)
t112- x
(7)
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[00173] Where, Trn, is the crystallization on-set temperature, 7', is the
crystallization
temperature, and X is the rate of cooling (here, 10 C/min).
[00174] Polymer flow behavior is known to be affected by the addition of
reinforcements (micro
or nano). Studying the flow properties of the nanocomposites is useful for
their processing. Melt
rheology was studied to understand the effect of graphene on the flow
properties of PET.
Rheographs for nanocomposite pellets were acquired using a rotational
Rheometer, equipped with
a 25 mm diameter parallel plate geometry and electronically controlled
heating. Samples were
dried in an oven at 170 C for 12 hours to eliminate moisture. PET and
nanocomposite pellets
placed between parallel plates were melt-pressed to 1 mm thickness (as shown
in Fig. 22) at 260 C,
under N2 atmosphere. The linear viscoelastic region (region where material
response is
independent of the deformation amplitude) of the samples was determined by
running a strain
sweep at a 1 Hz frequency. Dynamic frequency sweeps from 100 rad/s to 0.1
rad/s were acquired
for all the samples at 1% strain rate, within the linear viscoelastic region
for PET.
[00175] Dispersion of nanoparticles into the polymer matrix increases polymer
chain
entanglements through polymer-polymer and polymer-reinforcement interactions.
An increase in
entanglements stiffens the polymer and exhibits a solid like (rigid)
deformation behavior, which
is independent of the test frequency. Transition of the nanocomposite to a
rigid behavior occurs
at a critical weight fraction (percolation threshold), when a connecting
network of the
reinforcement is formed. Dynamic frequency sweeps of moduli provides
information from both
the polymer and reinforcement phase. Where the high frequency moduli are
dominated by the
polymer matrix and the low frequency response of the material is dominated by
the reinforcement.
Therefore, the percolation volume fraction can be obtained based on the low
frequency moduli of
the nanocomposite. The average aspect ratio of the reinforcement at the
percolation volume
fraction can be determined using the following equation.
Af =3 'sphere
(8)
20per
[00176] Where, (I)
Sphere is the percolation volume fraction for randomly packed overlapping
spheres (here, taken to be 0.30) and Oper is the percolation volume fraction
for the nanocomposite.
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[00177] Raman spectroscopy is the most widely used technique for
characterizing the quality
of graphene. For nanocomposites, several studies have reported the application
of Raman
spectroscopy for characterizing the interaction between a polymer-graphene
system and the quality
of graphene. A characteristic Raman spectrum of single layer graphene will
have peaks near 1580
cm-1 (G-band) corresponding to the C¨C stretching of sp2 carbon materials and
near 2680 cm-1
(G' -band), is the corresponding higher order mode. The presence of defects in
graphene can give
rise to a different Raman peak near 1350 cm-1 (D-band), which is useful in
analyzing the quality
of graphene. In the case of multi-layer graphene, number of layers up to n=7
for multi-layer
graphene can be estimated based on the intensity of G-band (-1580 cm-1) and
the shape of 2D-
band or G' -band (-2680 cm-1) can be used to identify up to n=4 layers. In the
current work, Raman
spectroscopy was used to evaluate the dispersion of graphene nanoplatelets and
also to ascertain
the it- it interactions between graphene layers and the phenyl ring in the PET
molecular chain.
Interaction of PET phenyl ring with graphene is found to show a shift in the
Raman band related
to C¨C stretching (1617 cm-1) of the phenyl ring.
[00178] Raman spectrum for PET and PET-GNP nanocomposites were collected using
a 532
nm (green light) laser excitation, at 2 mW laser power, with a 20 p.m spot
size. Change in the C¨C
(1617 cm-1) band position was evaluated by doing an individual peak fit
(Gaussian fit) on the
spectra collected for each GNP weight fraction.
Microstructure Analysis
[00179] As will be appreciated, imaging nanocomposites is imperative to
understand the role
of nanoparticles in improving polymer properties. Nanoreinforcements are
considered
advantageous because of the large extent of interactions possible with the
polymer matrix. Thus,
it is necessary to visualize the extent of interactions, which depend on the
level of dispersion. In
addition, the actual microstructural information is beneficial to model the
behavior of
nanocomposites and help in engineering materials. Electron microscopy and X-
Ray diffraction
are the most common techniques used for studying dispersion. Both of these
techniques are often
used in support of each other.
[00180] Graphene nanoplatelets inside the PET matrix were imaged by scanning
electron
microscopy (SEM). SEM micrographs of the fracture surfaces of the PET, and PET-
GNP
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nanocomposites were obtained. PET control and the nanocomposites with lower
graphene content
(up to 2%) were Au/Pt coated using a Balzers Union MED 010 coater.
[00181] Nanocomposite tensile bars were imaged with ultrasound to evaluate the
presence of
process defects (e.g. voids). Ultrasound 'Bulk Scans' for the nanocomposites
were acquired using
an acoustic microscope. Scanning was done at an ultrasound frequency of 30
MHz, with 0.5"
focal length and a spot size of 122 pm. During the scanning process a liquid
medium, such as
water, was used between the probe and sample, to maximize the ultrasound
transmission.
Ultrasound micrographs were recorded at a pixel pitch of 84 pm.
[00182] To analyze the exfoliation of graphene nanoplatelets, transmission
electron microscopy
(TEM) was performed. Nanocompo site thin sections (thickness of 70 nm) for 5%
and 15% GNP
weight fraction tensile bars were microtomed and imaged under a transmission
electron
microscope at an operating voltage of 200 kV. The difference in electron
densities between PET
and GNP provided a contrast in transmission electron micrographs. Due to the
higher density of
graphene nanoplatelets compared to PET, they can be recognized as the darker
regions in the
micrographs. Nanoplatelet parameters, thickness and length (diameter) were
obtained, by
measuring the number of pixels after calibrating the transmission electron
micrographs.
[00183] Transmission electron micrographs provide 2D dimensions of the
nanoplatelets.
However, this information alone is not sufficient to quantify their
distribution in the polymer
matrix. An 'interparticle distance (.1d)' parameter may be used to quantify
the exfoliation of
platelets, based on the information from TEM micrographs. Developed based on
the stereological
relations for relating the information from a 2D slice to 3D, interparticle
distance is the average
distance measured between particles in a straight line. Using the binarized
TEM micrographs, the
interparticle distance (ild) was determined based on Eq. (9), given below.
Interfacial area per unit
volume (Sv )P-G can be obtained by measuring the combined perimeter of the
nanoplatelets
present per unit area of the micrograph.
4(1-vv)
/Id =
(9)
(SIT )P-G
Sv = 4LA/7
(10)
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[00184] Where, Vv is the volume fraction of the nanoplatelets, (Sv )P¨G is the
polymer-
nanoplatelet interfacial area per unit volume of specimen, and LA is the total
perimeter of the
platelets per unit area of the 2D micrograph.
[00185] Considering the nanoplatelets are disk shaped, with known thickness
(t) and aspect
ratio (Af) dispersed in the polymer, theoretical interparticle distance can be
estimated using the
following equation, which may be obtained way of Eqs. (9) and (10):
t = 2aVv(Af + 2)42(1 ¨ Vv)Af]
(11)
[00186] Where, Vv is the volume fraction of the nanoplatelets, Af is the
nanoplatelet aspect
ratio, t is the nanoplatelet thickness, and Ad is the interparticle distance.
[00187] X-ray diffraction helps in understanding the dispersion state of
nanoplatelets within the
polymer matrix, by measuring the spacing between them. Single layer graphene
has a two-
dimensional (2D) hexagonal lattice. Graphene nanoplatelets with a 3D structure
similar to
graphite, exhibit "Graphene-2H" characteristic reflections corresponding to
the (002) and (004)
planes (26.6 and 54.7 20 for Cu Ka X-rays). PET with a triclinic crystal
structure, primarily
exhibits reflections corresponding to the (010), (110), (100), and (105) (17.5
, 22.5 , 25.60, and
42.6 20 for Cu Ka X-rays) planes [48]. Amorphous PET exhibits a broad halo at
about 20 20.
[00188] Diffraction patterns of the nanocomposites were collected using a 2D
detector and
micro diffraction and a 0.5 mm collimator in reflectance for crystallinity
measurements. Cu K,
X-ray radiation (2 = 1.54184 A) was used with a scan time of 60 sec. Percent
crystallinity can be
determined based on the amorphous and crystalline fractions using Eq. (11):
Ac
Xc% = Aa+Ac X 100%
(12)
[00189] Where, Ac is the crystalline contribution and Aa is the amorphous
contribution.
[00190] Sample geometry (I ¨ injection flow direction, Ti ¨ longer dimension
of the cross-
section, and T2 ¨ thickness) with respect to the instrument geometry is shown
in Fig. 23. A 2-D
diffraction frame showing the partial diffraction rings for PET and graphene,
indicating the
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presence of preferential orientation is shown in Fig. 23. Location of the
nanocomposite samples
used for diffraction and tomography are shown in Fig. 24.
[00191] As will be recognized, electron microscopy provides only two-
dimensional
microstructure information of the sample from a small area. In case of TEM the
sample size is
only 500 umx500 tun in area and 70 nm in thickness. Electron microscopy
combined with focused
ion beam (FIB) can be useful in attaining microstructure information along the
third direction.
Nevertheless, X-rays have certain advantages over electrons, in imaging
materials. Simplicity
with sample preparation, choice of ambient or in-situ environments, and less
induced damage to
the material are the major advantages. X-ray tomography is a non-destructive
imaging technique
that allows regenerating the 3D structural details of materials.
[00192] Tomography is the process of collecting cross-sectional information
either in
transmission or reflection mode, from an illuminated object. Material and
geometry information
is recorded (radiograph) based on the transmitted intensity of the X-rays, as
illustrated in Fig. 25.
This transmitted intensity can be related to the material information based on
the material's X-ray
absorption coefficient and density, according to the following equation:
/ = /0e Px
(13)
[00193] Where, I is the transmitted X-ray intensity, /0 is the initial X-ray
intensity, pni is mass
attenuation coefficient of the material, p is the material density, and x is
the material thickness.
Radiographs are reconstructed into cross-sectional slices (tomographs) using
Fourier transform
based algorithms. Developments in the field of X-ray and detector optics have
allowed focusing
the beam on a much smaller area, thereby attaining nanoscale resolution.
[00194] In the current work, X-ray nanotomography was attempted on two
different samples
(nanocomposite tensile bar and tensile tube) with the objective of
understanding nanoplatelet
distribution in three-dimensions. Nanotomography of the sample collected from
15% tensile bar
was performed on a SkyScan 2011 nano-CT instrument at 272 nm/pixel resolution.
For the tensile
tube sample of 2% weight fraction (ultrasound processed), wedge sections from
the inner and outer
surfaces were scanned on an Xradia 800 Ultra 3D X-ray Microscope at 150
nm/pixel resolution.
Reconstructed tomographs were visualized using 3D visualization software.
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Micromechanical Modeling of Nanocomposites
[00195] Continuous fiber composites are often designed or assessed based on a
simple empirical
formula, referred to as the "Rule of Mixtures". In the case of
nanoreinforcements, the Rule of
Mixtures poorly predicts the final properties. Along with the fact that these
are not continuous
fiber reinforcements, the differences are influenced by the low volume
fractions, significant
disparity of properties between the matrix and reinforcement, and aspect
ratio. For
nanocomposites, the spatial interaction between the nanoplatelets and matrix
is important in
determining their elastic behavior. High aspect ratios of the nanoplatelets
combined with
interactions at the matrix-reinforcement interface complicate nanocomposite
property estimation.
Therefore, traditional micromechanical models have been modified to estimate
the mechanical
properties for nanoparticles.
[00196] With the objective of understanding the effectiveness of graphene
nanoplatelets as
reinforcement, micromechanical models such as the Halpin-Tsai and the Hui-Shia
models were
used to determine the theoretical elastic mechanical performance of the PET-
GNP
nanocomposites. These models were simplified micromechanical relations of
continuum based
Mori-Tanaka and Hill's methods for predicting composite properties, both of
which models being
designed for unidirectional composites. Aspect ratio of the nanoplatelets
dispersed into the
polymer can be determined from the transmission electron micrographs. In the
Halpin-Tsai model,
the longitudinal modulus (Ell) of the composite is predicted using the
following equations:
Eli1-1-2Afnop
7-in = ____________________________________________________________________
(14)
1
1-no
Er-1
(15)
17 = Er+2Af
[00197] Where Af is the aspect ratio of the nano-reinforcement (D/t), (/) is
the volume fraction
of the reinforcement, Er is the ratio of reinforcement modulus to matrix
modulus (Ern).
[00198] In the case of the Hui-Shia model, modulus predictions are made using
the following
equations:
ih -1
EL = E7,[1 ¨ Ll
(16)
e
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ET = ¨ 42(1 + ¨3 )r
(17)
4
= + ____ + 3(1 0) {(1-9)a2-9/21
(18)
EE
in fm
A = (1 ¨ 0)
[3(a2+0.25)g-2a21
(19)
a2-1
a
2_ 3/2 L J [col a2 ¨ 1¨ cosh' al a > 1
(a1)
g
(20)
a
(1_,)3/2 [ aV1¨ a2 + cosh-1 a] a < 1
[00199] Where, 0 is the volume fraction of the reinforcement, a is the inverse
aspect ratio (t/D),
En, is the Young's modulus of the matrix (PET), and Ef is the Young's modulus
of the
reinforcement phase (graphene nanoplatelets).
RESULTS
[00200] With the objective of improving the properties of PET, graphene
nanoplatelets were
compounded with PET and injection molded into nanocomposites of specific
loading rates.
Nanocomposites obtained from this process were evaluated for their mechanical,
thermal, and
rheological properties to understand the effectiveness of graphene
nanoplatelets.
Average Molecular Weight
[00201] The average molecular weight was obtained from Gel Permeation
Chromatography
(GPC), for the following samples: control PET, ultrasound treated PET,
ultrasound treated
nanocomposite master-batch (5% GNP), and twin-screw compounded master-batch
with 5% GNP
weight fraction. Comparing master-batches with similar GNP weight fraction can
be helpful in
understanding changes that occurred due to the presence of graphene.
[00202] Based on the weight average molecular weight (Mw), shown in Fig. 26,
the following
observations were made. First, the average molecular weight changes with twin-
screw processing,
irrespective of ultrasound treatment. A decrease in the molecular weight
through ultrasound
treatment alone is less significant compared to the drop from twin-screw
compounding.
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[00203] In addition to the above observations, it is also noticed that the
drop in molecular weight
increased with the presence of graphene. From the molecular weight
measurements, ultrasound
treated samples have shown a polydispersity index (ratio of weight average to
number average
molecular weight) of 1.8 and 1.9 for nanocomposites with 5% GNP.
Intrinsic Viscosity
[00204] Intrinsic Viscosity (I.V.) is the most commonly denoted number in
reference to
discussions comparing properties of polyethylene terephthalate. Therefore, the
intrinsic viscosity
of PET and ultrasound treated PET samples, shown in Fig. 27, were obtained by
capillary
viscometer using polymer dissolved solvents.
[00205] Correlating the experimentally obtained viscosities with the
viscosities calculated by
means of the weight average molecular weight, using Equation 5, Mark-Houwink
parameters 'K'
and 'a' were optimized to the respective values 0.00047 and 0.658. Using the
new constants,
intrinsic viscosity for the nanocomposite samples was obtained. Calculated
viscosity values for
both PET and PET nanocomposite samples are presented in Fig. 28.
[00206] Intrinsic viscosities for the in-situ polymerized PET and
nanocomposite pellets,
collected experimentally are shown in Fig. 29, all of which are showing
viscosities in the range of
0.6 dL/g.
Mechanical Behavior
[00207] Stress-strain curves for the tensile bar samples are presented in Fig.
30. Young's
modulus was obtained from the initial region of the stress-strain curve.
Young's modulus and
strength data for the nanocomposite tensile bars (Set-A) are presented in Fig.
31. A decrease in
strength of the nanocomposites when compared with the control PET was
observed. Further,
nanocomposites had a brittle failure with a loss in elongation, compared with
the control PET
sample.
[00208] Using a custom fixture, PET and nanocomposite tensile tubes and bars,
shown in Figs.
32(a) ¨ (b), were tested for their mechanical properties. Young's modulus and
the tensile strength
of PET and nanocomposites are shown in Fig. 33. The PET modulus from the
tensile tube was
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found to be less than the tensile bar samples (difference of 0.2 GPa), as the
tensile bars exhibited
thermal crystallinity due to slower cooling (19%). The modulus of the
nanocomposites increased
with increasing GNP content. However, the strength of the nanocomposites
remained the same as
PET, except in the case of a 2% sample. Stress-strain curves for PET tensile
bar (2% GNP) and
nanocomposite tensile tubes of low GNP weight fractions (0.6% and 1.2% GNP)
are compared in
Fig. 34. Fig. 34 shows that the nanocomposites are tougher (area under the
stress-strain curve)
than PET. The Young's modulus for the 2% nanocomposite was identical from the
two different
injection molding processes used (3.1 GPa). However, nanocomposite tubes with
2% GNP
loading deviated in the type of failure with respect to lower weight
fractions. At 2% GNP loading,
nanocomposites exhibited only 1% strain which is significantly lower compared
to failure strain
for 1.2% GNP loading (400%).
[00209] Tensile bars of PET and ultrasound treated PET obtained from the micro
injection
molding process were tested for their mechanical properties. Fig. 35 compares
the Young's
modulus and strength data for ultrasound treated PET with control PET. It was
observed that the
ultrasound treatment of PET did not have a significant effect on its modulus
and strength.
However, the ultimate tensile strength (tensile strength at breaking) for the
ultrasound treated PET
increased significantly (by 24%), as shown in Fig. 36.
[00210] Using the ultrasound treated master-batch pellets; nanocomposite
tensile tubes at 2%
GNP loading were prepared and tested for comparison with nanocomposites from
twin-screw
compounding. Nanocomposites prepared from compounded pellets treated with
different
ultrasound amplitudes show improvement in Young's modulus and tensile
strength. Improvement
in modulus for nanocomposites with 3.5 gm ultrasound amplitude was higher (2.7
GPa ¨ 12%
improvement) compared with other ultrasound treatments, as shown in Fig. 37.
Nevertheless, the
increase in modulus for ultrasound treated 2% nanocomposites is lower compared
with the twin-
screw compounded nanocomposites at 2% GNP (3.1 GPa ¨ 24% improvement).
Ultrasound
treated nanocomposites displayed yielding behavior similar to PET, but with
only 3% maximum
improvement in strength.
[00211] Nanocomposites prepared through dilution of ultrasound treated master-
batch did not
provide conclusive evidence to understand the change in mechanical properties.
Therefore, tensile
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bars with 5% GNP weight fraction were obtained from micro injection molding
system, using the
ultrasound treated master-batch pellets (with no dilution of GNP weight
fraction). The Young's
modulus and the tensile strength of the 5% GNP nanocomposite tensile bars were
compared with
control PET and tensile bars prepared using 5% pellets from twin-screw
compounding process, as
shown in Fig. 38. While the strength data indicate a recovery in tensile
strength with increase in
ultrasound amplitude, the modulus data points out that the improvement from
ultrasound treatment
is not significant compared to the regular twin-screw mixing.
[00212] Tensile bars of PET control and nanocomposites with 0.1% GNP weight
fraction
obtained from the polymerization process were tested for their mechanical
properties. Fig. 39
compares the Young's modulus and strength data for PET and nanocomposites with
0.1% GNP of
different surface areas. While there is no significant difference in the
modulus of the
nanocomposites, strength exhibited two different trends. Ultimate strength of
the nanocomposites
shows significant (minimum 16%) improvement over the PET control. On the
contrary, tensile
strength of the nanocomposites decreased slightly (by 5%) over PET.
Density Measurements
[00213] Densities for the nanocomposites were measured using Archimedes'
principle. The
densities of the nanocomposites were different from the theoretical values
estimated based on
amorphous PET and graphene. Comparison of densities between the molded PET
tensile bars and
tensile tubes, indicate that the tensile bars were semi-crystalline (19%
crystallinity), based on Eq.
2. Density measurements from the nanocomposite samples deviate from
theoretical values, based
on the Rule of Mixtures. In order to make a better comparison of the strength
of nanocomposites,
densities were collected for samples before testing and used to estimate their
specific strength, as
presented in Figs. 39(a)-(c). Specific strength values presented in Figs.
39(a)-(c) show no
significant loss or improvement in strength of PET with GNPs, except for the
nanocomposite
tensile tubes with 2% GNP weight fraction.
Scanning Electron Microscopy
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[00214] Comparing the stress-strain curves of nanocomposites with PET shows
that the failure
strain (elongation) of the nanocomposite tensile bars decreased. To understand
the type and
reasons for the failure of nanocomposites, scanning electron micrographs were
collected. Fracture
surface micrographs show the presence of micro voids, as shown in Figs. 40(a)
and 40(b).
Moisture present in the pellets can give rise to voids during their
processing. Therefore, the
increase in the stress concentration near the voids contributed in lowering
the strength of the
nanocomposite tensile bars. Initiation of the crack from the void, as shown in
the fracture surface
micrographs, Fig. 40(b), confirms this observation.
[00215] Similar observations were made from the micrographs of the fracture
surface of
nanocomposite tensile tubes with 2% GNP weight fraction. Nanocomposite tensile
tube showed
signs of "ductile fracture", as shown in Figs. 41(a) and 41(b). Voids observed
in this set of samples
are very small < 10 pm in size, pointed with arrows in Fig. 41(a). Localized
ductile deformation
of the polymer matrix through fibril stretching, surrounding the micro voids
can increase the local
stress concentration. This increase in the stress concentration can initiate
cracks, which lead to the
brittle fracture of the nanocomposite.
[00216] At higher magnification, graphene nanoplatelets were observed on the
fracture
surfaces. Nanoplatelets, as pointed out in the SEM micrographs shown in Figs.
42(a)-(d), are
projecting out of plane to indicate they were exposed during the failure and
were part of load
sharing. At higher nanoplatelets content (15%), the microstructure of the
nanocomposite is
different from others with more local fractures. One difficulty with the
nanocomposite is the
ability to make clear amorphous samples. Having clear PET tensile bars helps
eliminate defects
caused by poor processing, such as voids. Since these nanocomposites are dark
the voids must
generally wait to be visually observed by destructive methods.
Ultrasound Imaging
[00217] A nondestructive alternative to imaging voids is ultrasound imaging.
Ultrasound
micrographs of the tensile bars from the ultrasound "Bulk Scan" are shown in
Fig. 43. These
micrographs show the presence of voids along the length of the tensile bar.
Based on the
micrographs, it was inferred that the voids are a result of processing.
Further, densities of the
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ultrasound imaged samples were compared with the mechanical tests to confirm
that the deviation
in the densities is due to the presence of voids.
Thermal Analysis
[00218] The melt and crystallization behavior of the nanocomposites was
analyzed through
DSC measurements. Fig. 44 presents the glass transition (Tg) and melting
temperatures (T) from
the second heating cycle and crystallization temperature (To) from the first
cooling cycle, plotted
with respect to the GNP weight fractions for twin-screw compounded pellets.
While the melting
temperature shifted to higher values with increasing GNPs, the glass
transition showed a decreased
trend except for at 15% weight fraction. A decrease in the glass transition
temperature as shown
in Fig. 44 can be due to the agglomeration of nanoplatelets inside the PET
matrix. Agglomerated
platelets can act as plasticizers and affect the glass-transition temperature.
[00219] Both crystallization and melt temperatures increased with increasing
GNP content. The
melting temperature of PET is dependent on the crystal shape and size. As
shown in Fig. 44, the
addition of GNPs increases the melting temperature. This can be due to the
formation of larger
and more perfect crystals indicated by the higher (10 C to 18 C)
crystallization temperature and
expected with the presence of nucleation sites (i.e., nanoplatelets). While
the change in melting
temperature is small, the crystallization temperature increased with
increasing GNP content.
Increases in the crystallization temperature are due to a nucleation effect
from the presence of
GNPs which become stronger with the increasing GNP weight fraction. The change
in
crystallization temperature and shape of the exothermic peak with GNP weight
fraction is shown
in Fig. 46.
[00220] Using the crystallization exotherms for nanocomposite pellets,
presented in Fig. 46, on-
set temperatures (Ton) were obtained to determine the crystallization half-
time (tv2) by way of Eq.
(7). It was observed that with an increase in the GNP content, the
crystallization half-time (inverse
of crystallization rate) increased. A decrease in the crystallization rate
indicates that with an
increase in the GNP content, PET chain mobility is affected. As a result, the
crystallinity of the
nanocomposites decreased at higher graphene loadings, as shown in Fig. 45.
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[00221] The percentage crystallinity presented in Fig. 45 (right), for the as
received injection
molded tensile bars was measured through Differential Scanning Calorimetry
(DSC). The
crystallinity measured for the injection molded nanocomposites shows a similar
trend to the non-
isothermal crystallinity obtained through DSC. This confirms the above
observation that an
increase in GNP allows early nucleation of PET, but restricts chain mobility.
[00222] Ultrasound treated PET and PET-5% GNP nanocomposite pellets were
analyzed for
their change in theimal properties. Glass transition and melting temperatures
are presented in Fig.
47. The glass transition temperature of PET decreased with the addition of
GNPs for the no
ultrasound condition (0 USM). Ultrasound treatment was observed to have an
effect on the glass
transition temperature (Tg) of both PET and PET nanocomposites. For PET, the
glass transition
followed a decreasing trend except for at the 7.5 gm amplitude. The change in
`Tg' for PET points
towards polymer softening with increase in ultrasound amplitude. The glass
transition temperature
for nanocomposites increased with the ultrasound amplitude. However, the `Tg'
of the
nanocomposite was still lower than PET. Crystallization temperatures for PET
and PET-5% GNP
pellets remained constant regardless of the ultrasound amplitude, at 194 C and
214 C respectively.
[00223] Multiple melting peaks were observed in the melting endotherm for
ultrasound treated
PET, as demonstrated in Fig. 48. Multiple melting peaks indicate the presence
of different crystals
sizes, potentially indicating at a broader molecular weight distribution.
[00224] The crystallization half-time (ti/2) for PET decreased with ultrasound
treatment. With
the addition of GNPs the `tin' increased for all the ultrasound amplitudes, as
shown in Fig. 49.
The increase in the crystallization half-time for the 5 gm amplitude condition
nanocomposite was
less compared to other ultrasound amplitudes. Non-isotheimal crystallinity for
the ultrasound
treated PET increased with the increase in amplitude, except for the case of
7.5 gm amplitude.
Presence of graphene increased the crystallinity, however maximum change in
crystallinity was
observed only in the case of 7.5 gm amplitude.
[00225] Tensile bars of ultrasound treated PET and PET nanocomposites obtained
from micro
injection molding were evaluated for percentage crystallinity. Under similar
conditions,
ultrasound treated PET samples have 8% crystallinity and ultrasound treated
nanocomposites have
11 to 13% crystallinity.
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[00226] PET control and nanocomposites obtained from in-situ polymerization
were evaluated
for their crystallization behavior. At 0.1% loading, graphene nanoplatelets
with a higher average
surface area (750 m2/g) had a stronger nucleation effect compared to
nanoplatelets with lower
average surface area (120 m2/g). Crystallization temperature and the non-
isothermal crystallinity
are higher for high surface area graphene, as shown in Fig. 50.
Dispersion Studies
[00227] Melt rheology of the nanocomposites was studied to understand the
extent of
nanoplatelet dispersion in PET. Dynamic frequency sweeps for the nanocomposite
pellets from
twin-screw compounding along with control PET are presented in Fig. 51. The
shear storage
modulus (G') of PET decreased linearly with frequency. The addition of
graphene nanoplatelets
to PET improved its modulus (G'). In the case of PET-2% GNP nanocomposite
pellets, the
modulus (G') transitioned from a linear region (dependent) to a plateau
(independent of the angular
frequency) below 0.3 rad/s. This transition point for 5% nanocomposite moved
up to 64 rad/s
frequency. Nanocomposites with 10% and 15% GNP weight fractions, exhibited
rigid behavior
even when tested at 320 C with a gap of 1.6 mm (melt thickness between
parallel plates). The
percolation threshold (Opõ) for twin-screw compounded PET-GNP nanocomposites
was
determined to be 1.75 %wt. (1.1 %vol.), based on the linear regression of the
G' values at 0.1
rad/s for 2% and 5% samples, as illustrated in Fig. 52. The nanoplatelet
aspect ratio at the
percolation threshold was evaluated as 40, based on Eq. (8).
[00228] Ultrasound assisted compounding of PET and graphene nanoplatelets
showed more
linear response compared to twin-screw compounding for the same weight
fraction (5%), as
demonstrated in Fig. 53. At low frequencies, nanocomposites with a lower
ultrasound amplitude
exhibited higher storage moduli. This indicates that increasing the ultrasound
amplitude has an
effect on nanoplatelet dispersion. As the moduli at higher frequencies are an
indication of the
polymer behavior, a decrease in the moduli compared to the PET control hints
at change in the
polymer structure. Comparing the ultrasound processed PET with the PET
control, as shown in
Fig. 54, indicates that the shear modulus of PET at higher frequencies
increased for lower (3.5 vun
and 5 i_tm) ultrasound amplitudes. Additionally, the modulus at lower
frequencies increased for
samples without (0 i_tm) and at 7.5 [tm ultrasound amplitude conditions. Based
on the data shown
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in Figs. 53 and 54, the ultrasound amplitude of 5 i.tm was found to have less
effect on PET, while
also indicating an improvement in the dispersion of graphene nanoplatelets.
[00229] Transmission micrographs were collected for nanocomposite tensile bars
of 5% and
15% weight fraction. Even though there are few layered graphene, as shown in
Figs. 56(a) and
(b), transmission micrographs of the nanocomposites indicate that the graphene
nanoplatelets are
not completely exfoliated in the PET matrix. Micrographs shown in Figs. 55(a)
and (b) indicate
that the nanoplatelets are distributed in the matrix, with regions of high
concentration.
[00230] Average dimensions (thickness and length) of the nanoplatelets
obtained from TEM
micrographs were used as input parameters to evaluate micromechanical models.
The interparticle
distance for graphene nanoplatelets inside the PET matrix was determined using
binarized TEM
images. Converting the micrographs to binary images allowed separating the
nanoplatelets (darker
regions) from the polymer matrix, as shown in Fig. 57. Interparticle distance
for 5% and 15%
nanocomposites were determined as 2800 nm and 520 nm respectively, as shown in
Fig. 58. This
change in the interparticle distance can be because of the increase in
concentration of graphene
nanoplatelets, which can affect the dispersion. Theoretical interparticle
distance for graphene
nanoplatelets of known aspect ratio 40 (obtained from rheological
measurements), were plotted
against the calculated values based on TEM, as shown in Fig. 58.
[00231] Diffraction patterns acquired from the graphene nanoplatelets, PET,
and PET-GNP
nanocomposite tensile bars are shown in Fig. 59. Peak broadening observed for
the graphene peak
at 26.6 20 is indicative of the presence of platelets with different d-
spacing. The intensity of the
graphene peak at 26.6 20 increased with weight fraction of the nanoplatelets.
However, no peak
shift was observed as in the case of an exfoliated nanocomposite. PET and
nanocomposite tensile
bars exhibit a broad amorphous halo around 19.2 20.
[00232] Diffraction scans indicate that the PET tensile bar is amorphous.
However, density
measurements and visual observations contradict this. Therefore, diffraction
scans were collected
across the cross-section of the PET tensile bar, to confirm the presence of a
crystalline core with
an amorphous outer layer. Slower cooling rates during the oil cooled injection
molding process
result in the formation of a significantly different skin and core
microstructure. Data from the
diffraction line scan along the thickness are presented in Figs. 60(a)-(b). In
order to have a better
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understanding on the microstructure of the nanocomposites, a similar line scan
was performed
along the thickness of the 15% tensile bar, presented in Fig. 61. It was
observed that intensity of
the graphene peak changes along the thickness of the sample, with higher
intensity at the center.
Further, crystallization of PET was also observed towards the core of the
sample, as denoted by
arrows labeled "PET" in Fig. 61.
[00233] Diffraction analysis on the nanocomposite tensile tubes indicate a
completely
amorphous microstructure and addition of GNPs did not increase the
crystallization of PET. 2D
diffraction frames indicate that the GNPs are oriented at the surface due to
the injection flow
stresses.
[00234] Using the reconstructed tomographs for the sample collected from the
15%
nanocomposite tensile bar, the distribution of nanoplatelets inside the PET
matrix was visualized
as shown in Figs. 62(a)-(b). Based on observations from the reconstructed
volume, nanoplatelets
were found to be oriented along the flow direction about 200 i_tm in depth
from surface (along the
Y-axis direction). Nanoplatelets with random orientation and curved platelets
as well were
observed from this data.
[00235] 3D X-ray microscopy of the samples (wedge shape) collected from the
nanocomposite
tensile tube has shown that the extent of nanoplatelet orientation was smaller
than in the tensile
bar. Figs. 63(a)-(b) shows the 3D distribution of the nanoplatelets on the
inside surface of the
tensile tube. As seen from the picture, nanoplatelets are oriented in the flow
direction, parallel to
the surface only up to 15.6 [un in thickness. For the outside surface,
alignment with the flow was
limited to a 7.5 i_tm thickness.
[00236] Raman spectrum for PET and PET nanocomposites were collected to
analyze the
dispersion of graphene nanoplatelets. The Raman spectrums indicate that the
nanoplatelets
dispersed in to the PET matrix are multi layered. As stated earlier, Raman
spectroscopy can also
be used to determine the presence of 7-7 interactions between PET and graphene
layers. Fig. 64
shows the Raman bands (-1617 cm-1) corresponding to C¨C stretching for PET and
nanocomposites with increasing GNP content. A change in the band positions
determined from
peak fits can be observed in Fig. 65. This shift in the Raman band (-1617 cm-
1) corresponding to
C¨C stretching in the phenyl ring of PET is an indication of the interaction
with graphene. Further,
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the full width at half maximum for the Raman band corresponding to C=0
stretching (-1730 cm-1)
was evaluated to understand the effect graphene has on PET chain mobility.
Peak broadening for
the 1730 cm-1 Raman band (C=0 stretching), perceived to be an indicator for
chain mobility in
amorphous PET was not observed here. This can be due to the highly oriented
structure at the
surface of the tensile bars obtained from injection molding. Even though the
surface is amorphous
for these nanocomposites, the highly oriented structure will reduce the
probability of having
multiple chain rotations thereby limiting the band width. In accordance
therewith, Fig. 66(a)
shows a table listing properties of GNP and PET for micromechanical model
based predictions in
accordance with the present disclosure.
Micromechanical Modeling
[00237] Single layer graphene is known for its high strength and stiffness.
Nevertheless,
dispersing graphene nanoplatelets solely into single layer graphene was not
realized here. Some
fraction of the mixture is likely single layer, but a majority was not.
Studies on multi-layer
graphene have shown that when the number of layers is less than 10, properties
are similar to that
of a single layer. In the case of nanoplatelets with more than a few layers,
its mechanical behavior
has been found to be similar to a graphite flake. For that reason, the modulus
of the graphene
nanoplatelet was considered to be 0.795 TPa, similar to highly oriented
graphite.
[00238] Improvement in the properties of a nanocomposite depends on the extent
of
nanoplatelet dispersion. Based on the measurements from TEM micrographs,
graphene
nanoplatelets with different length (diameter of the platelets) and thickness
were observed. Figure
66 shows the average size of the platelets with minimum and maximum values.
Predicted moduli
of the nanocomposite from Halpin-Tsai and Hui-Shia micromechanical models are
plotted against
the experimental results, as shown in Fig. 66. In order to compare with the
moduli from
nanocomposite tensile bars, modulus of semi-crystalline PET obtained from PET
tensile bars was
used as the model input properties. Using the average platelet properties and
their standard
deviations, modulus limits for the nanocomposites were calculated. Upper and
lower limits for
the predicted modulus are presented in Fig. 66 by means of error bars.
Comparison of the modulus
data from with experimental data indicate that Hui-Shia model predictions are
close to the
experimental values.
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[00239] Using the Hui-Shia model for nanoplatelets loaded along the length
(i.e., in direction
'1 or 2') of the nanoplatelets, the nanocomposite modulus with respect to
platelet aspect ratios may
be plotted as shown in Fig. 67. Modulus data for nanoplatelet aspect ratios
from TEM
measurements (average and the upper limit), melt rheology, and for an ideal
dispersion condition
(single layer graphene) were plotted. Based on the micromechanical model, it
was observed that
the predicted properties are more sensitive to nanoplatelets aspect ratio than
their properties. For
ideal dispersion condition, modulus of graphene single layer 1.02 TPa was
used. Modulus of
amorphous PET obtained from injection molded tensile tubes was used for the
model data shown
in Fig. 67.
[00240] Comparing the experimental modulus with the predicted modulus indicate
that the
nanocomposites with lower GNP weight fractions have higher aspect ratios. For
nanocomposites
(0.5%, 0.6%, and 1.2%) prepared through a dilution of the master-batch (as
mentioned in Fig.
16(c)), it was observed that master-batches with low GNP content yielded
higher aspect ratios.
This can be explained by considering the gentler processing seen when diluting
a master-batch
which was done with a single screw rather than a twin screw.
DISCUSSION
[00241] Polyethylene terephthalate ¨ graphene nanoplatelet nanocomposites were
prepared
through injection molding. Master-batch pellets from twin-screw compounding
and ultrasound-
assisted twin-screw compounding were characterized for their mechanical and
thermal properties.
In this chapter, the effect of ultrasound on PET properties, the type of
interaction between graphene
and PET, the mechanics behind the property change, the effect of compounding
and injection
molding, and the applicability of micromechanical models in evaluating the
nanocomposites are
discussed.
Effect of Ultrasound Treatment on PET
[00242] Ultrasound-assisted extrusion was used in the current study to
disperse graphene
nanoplatelets in the PET matrix. With no literature available to understand
the effect of ultrasound
on PET, ultrasound treated PET was also analyzed here. During ultrasound-
assisted extrusion,
energy applied (in the form of ultrasound waves) to the polymer can increase
the melt temperature
locally as a result of acoustic cavitation. Cavitation will not only aid in
exfoliating the
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nanoplatelets, but can also potentially change the polymer. The average
molecular weight from
the GPC measurements on ultrasound treated PET indicates that the molecular
weight decreased
with increasing ultrasound amplitude.
[00243] Nevertheless, the molecular weight for PET with no ultrasound
treatment also
decreased. Based on the data, it is understood that the decrease in molecular
weight is primarily
from the extrusion process (15%) and ultrasound treatment has a minimal (5%
drop) effect on the
molecular weight.
[00244] Mechanical testing of the ultrasound treated PET did not show a
significant difference
in Young's modulus and tensile strength. Nevertheless, ultrasound treated
specimens did show an
improvement in ultimate strength (strength at break) and exhibited higher
toughness compared to
PET control, as may be seen by way of Figs. 36 and 68.
[00245] PET degradation involves three different processes; they are:
hydrolysis, thermal
degradation and oxidation. During the extrusion process, polymer degradation
can take place
through one or more abovementioned processes and result in chain scission.
Some condensation
reaction can also occur, which lengthens the chain. An increase in the
toughness of PET from
ultrasound treatment indicates ultrasound indeed altered the PET molecular
chains. Thermal
analysis (DSC and Rheology) of the ultrasound treated PET hint at entanglement
through
branching of PET. Entanglement of polymer chains results in an increase in the
shear modulus
(G') at lower frequencies as observed in Fig. 54. This also explains the
increase in the `Tg' for
PET treated at 7.5 gm amplitude. Polymer with lower molecular weight (shorter
chain length)
exhibits a lower glass transition temperature, when compared with a high
molecular weight grade.
Then again, presence of entanglements (cross-linking or chain branching) will
restrict the chain
mobility, therefore increases the glass transition temperature. With the drop
in the molecular
weight at 7.5 mm amplitude is less significant compared to other amplitudes;
increase in the glass
transition temperature can be primarily due to the presence of entanglements
in PET molecular
chain.
[00246] Similar observations of an increase in the breaking strength has been
reported for PET
polymerized with low levels of branching agent trimethyl trimellitate (TMT).
At low levels (>
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0.4%) of branching agent, there is a significant increase (25%) in the break
strength even with no
signs of crosslinking from GPC measurements.
Wetability and Interaction of Graphene with PET
[00247] In the selection of nanoreinforcements, compatibility with the polymer
is one important
factor. Two polymers are considered compatible (or miscible to fouli
homogenous mixtures) when
the difference in their surface energies is small. An increase in the
difference in surface energies
can lead to phase separation. Likewise, similar surface energies between the
polymer and its
nanoreinforcement aids in dispersion. PET is slightly polar, due to the
presence of the C=0 bond
in the molecular chain. PET' s surface energy is 41.1 mJ/m2. Graphene's
surface energy is similar
at 46.7 mJ/m2. Though higher than PET and hydrophobic, graphene is much closer
than graphene
oxide (62.1 mJ/m2) and graphite (54.8 mJ/m2). This places graphene as a more
compatible
nanoreinforcement for PET. In general, graphene is considered difficult to
disperse as individual
sheets into any polymer matrix. It shows a tendency to agglomerate in order to
minimize surface
energy. Therefore, applying external energy through different mixing
techniques is necessary to
disrupt agglomerates and to distribute them into the polymer matrix. As
mentioned earlier, PET
is a highly viscous polymer with a high melting temperature. This drove the
selection of twin-
screw and ultrasound-assisted twin-screw mixing techniques for the dispersion
of graphene
nanoplatelets.
[00248] As stated previously, PET is chemically inert except for strong alkali
solvents.
Therefore, PET does not react with pristine graphene. Nevertheless, graphene
(similar to CNTs)
is known to have non-covalent interactions with aromatic compounds due to 7C-
7C stacking of
benzene with graphene. While graphene sheets inside graphite have similar
aromatic-aromatic (ir-
7r) interactions, their energy is estimated (-8 x1011 eV/cm2) to be lower than
that of a graphene
and benzene system (-8.4 x1014 eV/ cm2). Those skilled in the art will
recognize that the
magnitude of the 7E-7E interaction increases with an increase in the density
of hydrogen atoms in the
graphene-aromatic molecule system (i.e., stronger dipoles). This explains the
difference in binding
energy for the graphene-benzene interaction compared to a graphene-graphene
interaction.
[00249] PET is an aromatic polyester with a nearly planar molecular chain
configuration. This
makes it more favorable for the 7E-7E interaction with graphene nanoplatelets.
The presence of the
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71--71- interaction between PET and graphene nanoplatelets is detected in the
form of a shift in the
Raman peak corresponding to C¨C stretching in phenyl ring (Fig. 65). In
addition, graphene
nanoplatelets used in this work have a low concentration of polar functional
groups such as,
hydroxyl, carboxyl and ether on the edges (Fig. 7). Polar groups available
with the nanoplatelets
are likely to interact with polar groups of PET. The aforementioned
interactions between PET and
graphene are advantageous in influencing the properties of the nanocomposite.
Stress Transfer between PET and Graphene
[00250] PET-GNP nanocomposites showed an improvement in Young's modulus, as
demonstrated in Fig. 31. This increase in modulus of the nanocomposites takes
place because of
the effective transfer of stresses from PET to GNPs. For such a stiff
reinforcement, load transfer
between the polymer and reinforcement is governed by the strength of its
interface, which is
directly proportional to the thermodynamic work of adhesion (WO. Adhesion
energy between PET
and graphene was determined to be 84.6 mJ/m2 by way of Eq. (21) below. The
total surface energy
for graphene is 46.7 mJ/m2. The polar and non-polar components of PET surface
energy were
found to be 2.7 mJ/m2 and 38.4 mJ/m2.
wa = 2,\FL,pwy.gav + jyry:4gB
(21)
[00251] Where, Y LW is the Lifshitz-van der Waals (non-polar or dispersion)
component of
surface energy, y AB is the Lewis acid-base (polar) component of surface
energy, for polymer and
AB
graphene, and y = y LW + y
[00252] Those skilled in the art will recognized that the interfacial shear
strength has been
quantified to be 0.46 to 0.69 MPa, for a pristine single layer graphene in
contact with a PET
substrate (other surface of graphene in contact with air). As this value is
for contact between
pristine surfaces with no-polar group interactions, interfacial strength for
the nanocomposites in
this study will likely be higher than 0.69 MPa. Moreover, it has been found
that even though
graphene nanoplatelets have less interfacial adhesion with PET, compared to
clay, nanoplatelets
dispersed well in PET.
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[00253] An increase in weight fraction of GNPs resulted in a decrease of the
interparticle
distance, as quantified from TEM micrographs shown in Fig. 58. For
nanocomposite pellets with
15% loading, the interparticle distance was determined as 520 nm, which is
larger than the
interparticle distance of 200 nm, which has been reported for 2% graphene
(with higher surface
area, 750 m2/g).
[00254] As nanoplatelets get closer to each other, the number of polymer
chains influenced by
the presence of nanoplatelets will increase, as shown in Fig. 69. An increase
in the volume of
nanoplatelet affected polymers will stiffen the polymer. As may be observed by
way of Fig. 70,
with an increase in GNP weight fraction, the nanocomposite modulus increases
exponentially.
This behavior clearly depicts that load sharing of GNPs increases with
increase in weight fraction.
[00255] At higher weight fractions of GNPs, the stress-strain curves indicate
a more complex
yielding behavior, as indicated in Fig. 71. Platelet-platelet interaction is
not likely at low fractions.
Not only is the platelet volume fraction important, the platelet surface area
at that volume fraction
is important. At higher volume fractions a low surface area platelet is
expected to have a similar
benefit as a high surface area platelet at lower fractions. However,
eventually, the platelets begin
to interact across the matrix and that interaction will impact yielding
behavior. Platelet-platelet
bonding is much weaker than platelet-matrix bonds. In this case, we started to
see more
pronounced evidence of this interaction above 10% volume fraction platelets.
Nanocomposites Microstructure and Application of Micromechanical Models
[00256] Micromechanical models based on Hui-Shia formulae have closely
predicted the
nanocomposite properties compared to Halpin-Tsai. In the beginning they were
developed to
model the properties of semi-crystalline polymers, by considering the
crystalline domains as a
reinforcement phase in an amorphous matrix. These micromechanical models were
later adapted
to model micro-composites. Key assumptions for the abovementioned models are:
uniform
interface between the polymer and reinforcement, oriented in the loading
direction, and uniform
aspect ratio of the reinforcement. Nevertheless, nanoplatelets dispersed in
the nanocomposites are
not completely oriented along the loading axis (i.e., the injection
direction), as observed from
nanotomography illustrated in Figs. 62 and 63(b). For instance, in
nanocomposite tensile bars,
GNP orientation due to flow stresses was witnessed only to a 200 pm depth from
surface, and in
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the case of tensile tubes, this was even less (15 p.m depth from surface).
This shows that the bulk
core of the nanocomposite has more randomly oriented nanoplatelets. Increases
in the injection
molding speed and the cooling rate has resulted in limited nanoplatelet
orientation.
[00257] During injection molding, polymer melt flowing through the mold
channels
experiences shear forces. This shearing action is due to the temperature
gradient induced by the
low temperature mold walls. As the polymer melt starts solidifying (in
thickness), increasing shear
forces produce a layered structure along the thickness, with highly oriented
layers on the outer
surface. Some have speculated that this layer would be 0.1 mm thick. The rate
of cooling
determines the thickness of the oriented layers. Nanotomography allowed
quantifying the
thickness of the skin layers and this is a first of its kind observation of
this layer. As observed with
the tensile tube, the difference in the oriented layer thickness is likely due
to the more effective
cooling rate from the curvature of the surface and the mold design. Comparing
the tensile tube
data with the tensile bar data shows that the thickness of the oriented
surface layer is higher in the
tensile bar. This is consistent with the slower cooling and injection speed
compared to the tensile
tube.
[00258] One of the observations from nanotomography was that the aspect ratio
of platelets was
not uniform for the nanocomposite. The aspect ratio of the nanoplatelets from
rheological
measurements and transmission electron microscopy were determined to be 40 and
18.75. Taking
these as limits on the aspect ratios, moduli of the nanocomposites are
predicted. Comparing the
experimental data with predicted modulus trends for different aspect ratios,
as shown in Fig. 67,
has highlighted that the nanocomposites indeed have different average aspect
ratios and increased
with increase in GNP weight fraction.
[00259] Graphene nanoplatelets used in this work are of an average diameter
(length) 5 m. As
will be appreciated, this dimension is much lower than the size of 30 m for
pristine graphene,
which has been estimated to effectively reinforce polymethyl methacrylate
(PMMA). It will be
further appreciated that it has been indicated that graphene with reduced
stiffness (drop in modulus
from 1000 GPa to 100 GPa) will be less effective in reinforcing glassy
polymers (e.g. PET) as
compared to elastomers. As mentioned earlier, graphene with more than 10
layers can have
reduced stiffness. Aforementioned factors reinforce the need to have detailed
information on the
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microstructure of nanocomposites for the application of micromechanical models
to predict
properties.
Effect of Graphene Nanoplatelets on PET Properties and Molecular Chain
Mobility
[00260] The nanocomposite tensile bars from oil cooled molding exhibited
around 20%
crystallinity. Using a high-speed injection molding system with a faster
cooling rate,
nanocomposite tensile tubes were prepared with better control on the
crystallization of PET during
injection molding. Through this process, nanocomposites with GNP weight
fractions from 2% to
0.5% were prepared and tested. Comparing the modulus of nanocomposites with 2%
GNP,
indicated in Figs. 31 and 33, from both the processes (water cooled and oil
cooled injection
molding), shows an improvement in modulus with the change in process. For the
tensile tubes
with 2% GNP, the modulus increased from 2.5 GPa (amorphous modulus of PET) to
3.1 GPa (7%
higher than tensile bars). Another important observation was that the presence
of voids in the 2%
nanocomposite has little effect on its modulus. On the other hand, the
presence of voids (from
processing) resulted in premature failure and a reduction of strength. As
observed from the SEM
micrographs of nanocomposite fracture surfaces, shown in Figs. 40 and 41, the
voids acted as
stress concentration points and led to failure. The strength of the
nanocomposite tensile tubes at
low GNP weight fractions displayed a minimal increase, as shown in Fig. 33.
[00261] In general, the addition of GNPs to PET did not affect strength. This
is expected since
the weight fraction is low and the matrix will dominate flow behavior typical
for yielding. It is
also helpful to realize that the lack of chemical linkage (bonding) between
PET and GNP reduces
the GNP influence on yield and toughness. As discussed in earlier sections,
interfacial interactions
between PET and GNPs are favorable for initial stress transfer. With increase
in strain, interfacial
sliding starts between PET and GNPs, this precludes GNPs from sharing the
failure load. As
strength of the material depends on the weakest element, the nanocomposite
strength remained
similar to PET.
[00262] It is inferred from rheology and thermal analysis data that the
presence of graphene
nanoplatelets at higher weight fractions influences the mobility of PET
molecular chain. Higher
GNP weight fractions will result in the development of a continuous network,
as represented in
Fig. 69, that will change the deformation behavior of PET. As observed from
mechanical testing
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that up to 2% GNP weight fraction nanocomposites are tougher than PET, with
increased failure
strain. As PET failure takes place as a result of the through thickness
propagation of surface crazes,
the presence of graphene nanoplatelets in PET matrix can act against it
through crack deflection.
Nanoplatelets extending out of the fracture surface, as observed from the SEM
micrographs in Fig.
42, support the above observation. On the other hand, nanocomposites above 2%
GNP weight
fraction exhibited brittle failure. The graphene nanoplatelets weight fraction
at which this
transition was observed agrees with the percolation limit from Rheology
measurements.
[00263] Using Raman spectroscopy, it has been shown that an increase in
graphene
concentration restricts the mobility of PET chains. The Raman spectrum shown
in Fig. 5, did not
show change in peak width, as the nanocomposites from injection molding
exhibited highly
oriented amorphous surface layer. Oriented PET chains will limit the number of
chain
configurations possible, thereby restricting the rotation of C=0 isomers which
cause peak
broadening.
[00264] Thermal analysis of the nanocomposites showed that the addition of
GNPs affected
PET crystallization. Graphene nanoplatelets can act as nucleation sites and
promote
crystallization, with an increase in the crystallization temperature.
Nevertheless, reduced PET
chain mobility with an increase in the nanoplatelet fraction (confinement
effect), counters the
nucleation effect. A combination of these opposing effects led to the increase
in crystallization
half-time and decreased the amount of crystallinity, as indicated in Fig. 45.
As the interparticle
distance became smaller with an increase in the GNP weight fraction, chain
mobility becomes
more restricted. This elucidates the change in the failure type of PET
nanocomposites, as discussed
earlier for higher GNP weight fractions (above 2%). Similar observations have
been reported with
PET and high aspect ratio graphene at less than 2% weight fractions, wherein
it was found that
crystallization half-time decreased until graphene loading less than 2% and
started increasing at
2%.
Effect of Ultrasound Treatment on PET-Graphene Nanocomposites
[00265] Comparing the properties of nanocomposites prepared from twin-screw
and
ultrasound-assisted compounding, presented in Fig. 38, helps in identifying
the best mixing
approach. It was observed that the ultrasound amplitudes of 5 j_im and 7.5 [tm
showed the
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maximum improvement in terms of modulus. However, this improvement in modulus
is not
significantly different compared to nanocomposites from twin-screw compounded
material. This
indicates that the ultrasound treatment did not provide an advantage in
improving the dispersion
of graphene nanoplatelets. Molecular weight data for 5% graphene nanocomposite
pellets from
both the process indicate a similar drop in the PET average molecular weight,
as shown in Fig. 26.
Additionally, it is observed that the presence of graphene increased the drop
in molecular weight
from extrusion process. This could be due to the high thermal conductivity of
graphene
nanoplatelets, which allows faster heating of PET and cause chain damage under
regular heating
conditions.
[00266] Rheology of the ultrasound treated nanocomposites showed similar
behavior as
observed in ultrasound treated PET, illustrated in Figs. 53 and 54. The
decrease in the shear
modulus at high frequency is due to the damage of the polymer chains
(molecular weight) and the
increase in the shear modulus at lower frequency could be from an increase in
entanglement from
ultrasound treatment as well the presence of dispersed graphene. Higher
ultrasound amplitudes
show lower shear modulus; this indicates that there is better dispersion at
higher amplitudes, which
is also evident from mechanical properties. However, for the 7.5 um ultrasound
amplitude, the
drop in molecular weight is higher compared to other amplitudes. Ultrasound-
assisted dispersion
of graphene has shown a difference in the thermal properties of the
nanocomposites compared to
regular twin-screw injection (for the same graphene weight fraction).
Evaluating the glass
transition temperature, crystallization half-time, and percent crystallinity,
shown in Figs. 47 and
49, point to better graphene dispersion at 7.5 um ultrasound amplitude over
other amplitudes. The
crystallization half-time of PET decreases with a decrease in the molecular
weight; however
dispersed graphene could be the reason for the increase in half-time at 7.5 um
amplitude. These
observations along with the melt rheology data, shown in Figs. 53 and 54,
suggest that an
ultrasound amplitude of 7.5 um is likely to have improved the dispersion of
GNPs. However, this
improvement in dispersion observed from thermal analysis did not reflect in
the mechanical data.
[00267] While preparing the tensile bars of ultrasound treated nanocomposites
on the micro
injection molding system, the effect of mixing time on the mechanical
properties was investigated.
Nanocomposite samples were injection molded for each of the following process
times: 1 min, 2
min and 3 min. Modulus data, shown in Fig. 72, indicate that longer mixing
times resulted in a
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decrease in the nanocomposite modulus. This could be due to the damage of
polymer with longer
residence times.
Effect of Graphene Surface Area on PET Nanocomposite Properties.
[00268] In-situ polymerized PET nanocomposites suggest that the surface area
of the graphene
nanoplatelets can be a basis for the difference in the crystallization
behavior of PET. Coming to
the mechanical properties of the nanocomposites, their difference is not
significant enough to make
a conclusion. Nanoplatelets dispersed through sonication will contain
platelets of different
dimensions, giving rise to a broad distribution of nanoplatelet aspect ratios,
changing the average
surface area available. The application of a size selective approach, through
centrifugation can
help in understanding the effect of the nanoplatelet surface area.
[00269] As mentioned herein, one drawback for in-situ polymerization is
achieving similar
molecular weight polymer between different batches. This indicates that
polymerization process
is not alone sufficient for the producing nanocomposites; application of
secondary techniques such
as solid state polymerization can help in addressing the disparity in
molecular weights.
Effectiveness of Graphene as Reinforcement
[00270] The mechanical behavior of PET is dependent on the type of
crystallinity: spherulitic
and stretch crystallization. The modulus of a PET crystal was calculated to be
146 GPa, based on
the deformation of the covalent bonds. One approach in improving the
properties of PET is to
increase its crystallinity from processing methods. PET film samples obtained
through biaxial
stretching show 5.4 GPa at 45% crystallinity. Comparing that with the
nanocomposites, the
modulus for only 10% GNP weight fraction was 5.3 GPa. With a reinforcement
that is 5.5 times
stiffer than a PET crystal, the improvement with GNP addition is comparable to
that of self-
reinforced (stretch crystalized) PET. For the same biaxial stretched sample,
when tested along the
maximum molecular orientation the direction showed about a 9.1 GPa modulus.
This indicates
that inducing orientation to graphene nanoplatelets during the processing of
nanocomposites could
improve the properties further.
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CONCLUSIONS
[00271] Poly(ethylene terephthalate) ¨ graphene nanoplatelet (PET-GNP)
nanocomposites
have been demonstrated by way of injection molding. As described herein, the
PET-GNP
nanocomposites were evaluated for dispersion, mechanical, and theinial
properties. Accordingly,
the PET-GNP nanocomposites show an exponential improvement in Young's modulus,
ranging
between 8% for 0.5% GNP weight fraction and 224% for 15% GNP weight fraction,
without
affecting the strength of the PET. An addition of graphene nanoplatelets above
2% weight fraction
was found to affect the failure strain of PET. Further, the particular molding
system utilized plays
a significant role in influencing the final properties of the nanocomposite.
In particular,
nanocomposites made by way of high speed injection molding yield a relatively
improved
modulus.
[00272] As described herein, the master-batch method effectively disperses the
nanoplatelets
within the PET, with a lower GNP content yielding better dispersion than
higher GNP content
master-batches. Ultrasound treatment of PET generally increases its toughness,
while providing a
minimal effect on molecular weight and no effect on Young's modulus. Twin-
screw compounding
and ultrasound-assisted twin-screw compounding lead to similar improvements in
Young's
modulus. Moreover, PET-GNP nanocomposites obtained by way of twin-screw
compounding
exhibit a GNP interparticle distance which decreases with increasing
concentration. In particular,
a 15% nanocomposite exhibits an average GNP interparticle distance of
substantially 520 nm.
[00273] PET-GNP nanocomposites prepared by way of injection molding exhibit a
preferential
orientation of the GNPs in a flow direction to a depth of substantially 200
?Am below the mold
surface. The depth of the preferential orientation is dependent on a cooling
rate of the PET-GNP
nanocomposite. Further, a presence of GNPs affects crystallization behavior of
PET, wherein
crystallization temperature increases with additional nucleation from
graphene, and crystallization
half-time (t1/2) increases with increasing GNP content. The crystallinity of
PET generally is
influenced by the rate of cooling, as well as an amount of stretching. Strain-
induced crystallization
is effective in improving mechanical properties of PET as compared to
theimally-induced
crystallization. It will be appreciated, therefore, that graphene
reinforcement may be optimized by
increasing the nanoplatelet effective surface area and increasing the
orientation of nanoplatelets
along the flow direction.
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[00274] While the invention has been described in terms of particular
variations and illustrative
figures, those of ordinary skill in the art will recognize that the invention
is not limited to the
variations or figures described. In addition, where methods and steps
described above indicate
certain events occurring in certain order, those of ordinary skill in the art
will recognize that the
ordering of certain steps may be modified and that such modifications are in
accordance with the
variations of the invention. Additionally, certain of the steps may be
performed concurrently in a
parallel process when possible, as well as performed sequentially as described
above. To the extent
there are variations of the invention, which are within the spirit of the
disclosure or equivalent to
the inventions found in the claims, it is the intent that this patent will
cover those variations as
well. Therefore, the present disclosure is to be understood as not limited by
the specific
embodiments described herein, but only by scope of the appended claims.
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