EP3790734A1 - Nanocomposites de poly(téréphtalate d'éthylène)-graphène à dispersion améliorée - Google Patents

Nanocomposites de poly(téréphtalate d'éthylène)-graphène à dispersion améliorée

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Publication number
EP3790734A1
EP3790734A1 EP19800351.9A EP19800351A EP3790734A1 EP 3790734 A1 EP3790734 A1 EP 3790734A1 EP 19800351 A EP19800351 A EP 19800351A EP 3790734 A1 EP3790734 A1 EP 3790734A1
Authority
EP
European Patent Office
Prior art keywords
pet
graphene
gnps
gnp
nanocomposites
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP19800351.9A
Other languages
German (de)
English (en)
Other versions
EP3790734A4 (fr
Inventor
Jay Clarke Hanan
Vahid SHABAFROOZ
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Niagara Bottling LLC
Original Assignee
Niagara Bottling LLC
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Publication date
Application filed by Niagara Bottling LLC filed Critical Niagara Bottling LLC
Priority claimed from PCT/US2019/031612 external-priority patent/WO2019217744A1/fr
Publication of EP3790734A1 publication Critical patent/EP3790734A1/fr
Publication of EP3790734A4 publication Critical patent/EP3790734A4/fr
Pending legal-status Critical Current

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Classifications

    • C—CHEMISTRY; METALLURGY
    • C08—ORGANIC MACROMOLECULAR COMPOUNDS; THEIR PREPARATION OR CHEMICAL WORKING-UP; COMPOSITIONS BASED THEREON
    • C08K—Use of inorganic or non-macromolecular organic substances as compounding ingredients
    • C08K3/00—Use of inorganic substances as compounding ingredients
    • C08K3/02—Elements
    • C08K3/04—Carbon
    • C08K3/042—Graphene or derivatives, e.g. graphene oxides
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B32—LAYERED PRODUCTS
    • B32B—LAYERED PRODUCTS, i.e. PRODUCTS BUILT-UP OF STRATA OF FLAT OR NON-FLAT, e.g. CELLULAR OR HONEYCOMB, FORM
    • B32B5/00—Layered products characterised by the non- homogeneity or physical structure, i.e. comprising a fibrous, filamentary, particulate or foam layer; Layered products characterised by having a layer differing constitutionally or physically in different parts
    • B32B5/22—Layered products characterised by the non- homogeneity or physical structure, i.e. comprising a fibrous, filamentary, particulate or foam layer; Layered products characterised by having a layer differing constitutionally or physically in different parts characterised by the presence of two or more layers which are next to each other and are fibrous, filamentary, formed of particles or foamed
    • B32B5/24—Layered products characterised by the non- homogeneity or physical structure, i.e. comprising a fibrous, filamentary, particulate or foam layer; Layered products characterised by having a layer differing constitutionally or physically in different parts characterised by the presence of two or more layers which are next to each other and are fibrous, filamentary, formed of particles or foamed one layer being a fibrous or filamentary layer
    • B32B5/26—Layered products characterised by the non- homogeneity or physical structure, i.e. comprising a fibrous, filamentary, particulate or foam layer; Layered products characterised by having a layer differing constitutionally or physically in different parts characterised by the presence of two or more layers which are next to each other and are fibrous, filamentary, formed of particles or foamed one layer being a fibrous or filamentary layer another layer next to it also being fibrous or filamentary
    • C—CHEMISTRY; METALLURGY
    • C08—ORGANIC MACROMOLECULAR COMPOUNDS; THEIR PREPARATION OR CHEMICAL WORKING-UP; COMPOSITIONS BASED THEREON
    • C08K—Use of inorganic or non-macromolecular organic substances as compounding ingredients
    • C08K2201/00—Specific properties of additives
    • C08K2201/002—Physical properties
    • C08K2201/006—Additives being defined by their surface area

Definitions

  • Embodiments of the present disclosure generally relate to the field of polymer composites. More specifically, embodiments of the disclosure relate to a graphene reinforced polyethylene terephthalate composition and methods for dispersing graphene nanoplatelets within polyethylene terephthalate.
  • Composites are multi-phase materials comprised of a matrix and a reinforcement material.
  • the matrix is a polymer and the reinforcement a nanofiller dispersed in the matrix.
  • Polymer composites take on characteristics dependent on their reinforcement, including changes in elastic modulus and tensile strength.
  • a broad range of inorganic and organic particles, such as minerals, glass, carbon black, and wood, have been used as fillers in the development of thermoplastic composites.
  • Recent research into nanomaterials has led to the development of nanoscale fillers that can be used to create nanocomposites with enhanced properties compared to conventional composites.
  • the logical progression is to develop polymer nanocomposites, which are defined as a multi-phase, polymer-based material, such as thermoplastics, thermosets, or elastomers, with a filler exhibiting at least one dimension below 100 nm.
  • polymer nanocomposites which are defined as a multi-phase, polymer-based material, such as thermoplastics, thermosets, or elastomers, with a filler exhibiting at least one dimension below 100 nm.
  • Nanofillers characteristically have a high surface-area-to-volume ratio.
  • the material properties of composites depend on the interaction between the matrix and the nanofiller. Nanocomposites often have more significant improvements in properties per volume fraction of filler than conventional composites. This is because of the higher surface-area-to-volume ratio of nanoscale materials, which allows for more interaction between the filler and the matrix per volume fraction. Due to the low fraction of filler, nanomaterials are typically much lighter than conventional composites. They are also more easily incorporated into existing polymer processing methods. This leads to materials that have many potential applications in a variety of industries, such as packaging materials, automotive, and aerospace applications. Over the past two decades, several different types of nanofillers, (e.g.
  • nanoparticles, clay, carbon nano fibers (CNFs), carbon nanotubes (CNTs), graphene, SiO?, Ti0 2 , etc.) have been utilized for the development of polymer nanocomposites. While improvements in various properties of polymer nanocomposites are dependent on the type of nanofiller used, the way they are integrated into the matrix also affects the performance and properties of the finished product. When producing nanocomposites, the most significant challenge is often obtaining a uniform distribution of the nanofiller in the matrix.
  • Several studies describe commonly used methods to fabricate nanocomposites such as solution blending, in-situ polymerization, and melt compounding.
  • Solution blending consists of the dissolution of the polymer in a suitable solvent followed by mixing with a dispersed suspension of nanofiller. While the production of nanocomposites through this approach is straightforward, one of the limitations is the selection of a suitable solvent. Due to the low solubility of some polymers in various solvents, blending often requires elevated temperatures which can make processing challenging. In addition, the solvent’s properties can affect the distribution of the nanofiller, having a negative impact on the properties of nanocomposites prepared by this technique.
  • In-situ polymerization is another approach for the development of nanocomposites.
  • This technique involves a chemical reaction resulting in the incorporation of a nanofiller within a polymer matrix.
  • the nanofiller is first dispersed in ethylene glycol (EG), a liquid, PET polymer precursor.
  • EG ethylene glycol
  • TP A terephthalic acid
  • the second step, polycondensation reaction is undertaken to continue the preparation of the polymer with intercalated nanofillers.
  • This technique can result in a more homogenous distribution of nanofiller in the matrix.
  • melt compounding consists of mixing the polymer and the nanofiller at high temperatures. In this process, the nanofiller is first compounded with the molten polymer to then fabricate nanocomposites using an injection molding process. Melt compounding utilizes shear forces to incorporate the nanofiller in the matrix. Of the three methods, melt compounding is the most industrially accessible, since it does not require solvents and can be used in existing large- scale processes.
  • PET Polyethylene terephthalate
  • thermal history rate of cooling
  • mechanical history stress history
  • Fig. 1 The molecular structure of PET consists of a phenyl ring and two ester groups and is illustrated in Fig. 1.
  • PET has desirable properties, (e.g. transparency, colorlessness, low density, high strength, and chemical resistance), and is a widely-used polymer in engineering applications including fiber production and filtration. Since its discovery in the 1940s, PET has been used mostly in the food and beverage packaging industry among other thermoplastics.
  • PET is semi-crystalline.
  • the degree of crystallinity in PET has a dominant influence on the mechanical and thermal properties, meaning that the physical properties of PET can be significantly improved by arrangment and degree of crystallization in the microstructure ⁇
  • the crystallization half-time (inverse of crystallization rate), t 1 ⁇ 2 , refers to the time at which the extend of crystallization is completed at 50%.
  • the crystallization half-time is often used to estimate the processing conditions of a new polymer by comparing the t 1 ⁇ 2 with those of known polymers.
  • PET has a slow crystallization rate.
  • PET crystallization rate with other polyesters including poly(butylene terephthalate) (PBT) and poly(trimethylene terephthalate) (PTT). They ranked the crystallization rate in the order of PBT > PTT > PET. Based on the results obtained in this research, it was found that the crystallization half-time (inverse of crystallization rate) was 0.95 ⁇ 0.15 min for pristine PET. Additionally, PET has limited barrier performance, which constrains the use of PET in some applications. However, research suggests that the addition of nanofillers increases the crystallinity of PET, which also contributes to enhancement in its mechanical and barrier properties.
  • PBT poly(butylene terephthalate)
  • PTT poly(trimethylene terephthalate)
  • Graphene is a relatively new nanofiller that has been used in the development of polymer nanocomposites.
  • Graphene-based nanocomposites consist of single-layer graphene sheets, few-layer graphene sheets, and multi-layer graphene sheets. Within the layers, covalent bonds are strong, whereas between the layers the weaker Van der Waals force dominates.
  • the elastic properties and breaking strength of graphene sheets have been measured and reported as 100 times greater than steel, with a Young’s modulus of 1.0 ⁇ 0.1 TPa and tensile strength of 130 GPa.
  • Table 1 summarizes the advantages and disadvantages of the techniques used to produce graphene.
  • Table 1 Advantages and disadvantages of currently used techniques to produce graphene.
  • % showed a thermo-oxidative degradation temperature 32 °C higher for 30% weight loss. Due to the differences in surface energies of PET and graphene, graphene tends to agglomerate, which negatively impacts the properties of the nanocomposite. To avoid the agglomeration of graphene sheets, functionalizing the graphene’s surface chemically helps to reduce the surface energy. However, the addition and removal of the functionalized group adds complexity to the development of nanocomposites.
  • FIG 2 illustrates the types of graphene incorporation into the matrix.
  • the polymer chains do not interact with the graphene sheets.
  • the bulk of the nanofiller phase, graphene will not be incorporated into the polymer matrix because of its phase separation and will therefore not be able to modify the properties of the whole composite as much as it could in the other cases because of its minimal incorporation with the matrix.
  • the graphene sheets In the second phase (b), intercalated, the graphene sheets have been exfoliated to few- to several-layer sheets that are much smaller than the first phase, but still not monolayer graphene.
  • FIG. 3 represents an illustration of a randomly- and aligned-orientated graphene-based nanocomposite both with an exfoliated structure.
  • graphene is commercially available, there is still limited information on the effectiveness of graphene-based nanocomposites. Further investigation is required to better understand the effects of the addition of graphene on the properties of the host polymer.
  • PET is one of the polymers that is preferred for food and beverage packaging. With graphene being an exceptional nanofiller, the creation of PET-graphene nanocomposites could be advantageous and open up several engineering applications.
  • a composition and a method are provided for graphene reinforced polyethylene terephthalate (PET).
  • PET polyethylene terephthalate
  • Graphene nanoplatelets comprising a suitable surface area are added to a dispersion medium for producing graphene reinforced PET.
  • the average surface area may range between substantially 15 m 2 /g and 750 m 2 /g.
  • the dispersion medium may be comprised of ethylene glycol.
  • the dispersion medium and graphene nanoplatelets are sonicated to disperse the nanoplatelets within the dispersion medium.
  • the dispersion medium and graphene nanoplatelets are centrifuged to remove larger nanoplatelets that are not suitably dispersed within the dispersion medium.
  • a supernatant solution of dispersed graphene nanoplatelets and dispersion medium is decanted and then used for polymerization of the graphene reinforced PET.
  • the resultant graphene reinforced PET is comprised of a continuous matrix of PET with a reinforcement material comprising dispersed phase graphene nanoplatelets.
  • Polymer nanocomposites are multi-phase materials comprised of a polymer matrix and a reinforcement nanofiller.
  • Graphene is one of the most promising nanofillers with a unique combination of properties. To achieve the maximum enhancement in the properties of nanocomposites, graphene must be well-incorporated within the polymer matrix.
  • PET polyethylene terephthalate
  • GNPs graphene nanoplatelets
  • GNPs may be dispersed in PET.
  • the first method involves melt compounding of a mixture of GNPs with PET pellets and powders. This method was investigated to evaluate the improvements in mechanical and thermal properties of PET. We hypothesize that dispersion of GNPs in a liquid medium, compatible with PET chemistry, can be used to achieve a more uniform distribution of GNPs in the PET matrix. We tested this in two methods: in-situ polymerization and dispersion dosing. In the in-situ polymerization method, GNPs were first dispersed and exfoliated in EG, and the dispersions were used for the development of the PET nanocomposites through in-situ polymerization.
  • the GNPs were dispersed in PEG, a dispersion medium with a higher viscosity than EG, and the dispersions were used for the development of the PET nanocomposites through PEG-GNP dispersion dosing via injection molding based on the following hypothesis: The higher viscosity of PEG leads to slower sedimentation of the dispersed GNPs, resulting in a higher concentration of dispersed GNPs in the medium.
  • GNPs were melt-compounded with both PET pellets and PET powders to create the nanocomposites.
  • the elastic modulus of PET powders and pellets improved by 182% and 101%, respectively and the tensile strength of PET powders and pellets improved by 35% and 14%, respectively.
  • Confocal microscopy showed that the GNPs inside the PET-GNP nanocomposites, prepared by PET pellets, agglomerated to a degree much greater than PET powders.
  • a polymer nanocomposite comprises: a matrix comprising polyethylene terephthalate; and a reinforcement material comprising dispersed phase graphene nanoplatelets.
  • the graphene nanoplatelets comprise a surface area of at least about 15 m 2 /g.
  • the graphene nanoplatelets comprise an average thickness ranging between about 10 nanometers (nm) and 20 nm.
  • the graphene nanoplatelets comprise a surface area ranging between about 120 m 2 /g and 150 m 2 /g.
  • the graphene nanoplatelets comprise an average thickness ranging between about 6 nm and 8 nm.
  • the graphene nanoplatelets comprise a surface area ranging between about 300 m 2 /g and 750 m 2 /g. In another exemplary embodiment, the graphene nanoplatelets comprise an average thickness ranging between about 2 nm and 3 nm.
  • a method for preparing graphene reinforced polyethylene terephthalate comprises: obtaining graphene nanoplatelets comprising a suitable surface area; adding the graphene nanoplatelets to a dispersion medium suitable for producing PET; sonicating the dispersion medium and graphene nanoplatelets so as to cause a homogeneous dispersion of the graphene nanoplatelets within the dispersion medium; centrifuging the dispersion medium and graphene nanoplatelets to remove a portion of larger graphene nanoplatelets that are not suitably dispersed within the dispersion medium; decanting a supernatant solution of graphene nanoplatelets dispersed in the dispersion medium; and using the supernatant solution for polymerization of the graphene reinforced PET.
  • the graphene nanoplatelets comprise a surface area of at least about 15 m 2 /g. In another exemplary embodiment, the graphene nanoplatelets comprise a surface area ranging between about 120 m 2 /g and 150 m 2 /g. In another exemplary embodiment, the graphene nanoplatelets comprise a surface area ranging between about 300 m 2 /g and 750 m 2 /g.
  • sonicating comprises immersing the solvent and graphene nanoplatelets in a bath sonicator for a period of time and operating the bath sonicator at a frequency suitable for dispersing the graphene nanoplatelets within the solvent.
  • sonicating comprises selecting the period of time so as desirably reduce an average length and width of the graphene nanoplatelets.
  • the frequency is a ultrasonic and the period of time ranges between at least 30 minutes and 180 minutes.
  • centrifuging comprises subjecting the solvent and graphene nanoplatelets to a rotational speed of centrifugation ranging between at least 1400 RPM and 7200 RPM.
  • adding further comprises selecting polyethylene glycol as the dispersion medium suitable for producing the graphene reinforced PET.
  • selecting polyethylene glycol comprises selecting any one of PEG-300, PEG-400, and PEG-600 as the dispersion medium.
  • adding further comprises selecting ethylene glycol as the dispersion medium suitable for producing the graphene reinforced PET.
  • using the supernatant solution for polymerization further comprises performing an esterification reaction to produce bis(2 -hydroxyl ethyl) terephthalate (BHET) with water as a by-product, followed by performing a polycondensation reaction so as to produce the graphene reinforced PET.
  • performing the polycondensation reaction further comprises including one or more catalysts comprising any one or more of Antimony (Sb), Cobalt (Co), and Phosphoric Acid.
  • Figure 1 is a chemical formula illustrating a molecular structure of polyethylene terephthalate in accordance with the present disclosure
  • Figure 2 illustrates a schematic representation of a) phase-separated, b) intercalated, and c) exfoliated, layered, structured filler in a polymer matrix with an amorphous structure;
  • Figure 3 illustrates a schematic representation of a) controlled alignment and b) random alignment in an exfoliated graphene-based nanocomposite;
  • Figure 4 illustrates a schematic representation of nanofillers’ aspect ratio with respect to their shapes;
  • Figure 5 illustrates an embodiment of graphene comprising a 2D mono-atomic thick carbon allotrope with a hexagonal structure
  • Figure 6 illustrates chemical bonds in carbon atoms wherein Bernal stacking is formed by putting a carbon atom of the second layer marked as b) on top of a carbon of the first layer, marked as a);
  • Figure 7 illustrates a schematic representation of achieving graphene dispersion in dispersion media
  • Figure 8 illustrates graphene aqueous dispersion a) surfactant molecules, b) stabilized graphene dispersion, and c) micelle formation in the dispersion;
  • Figure 9 comprises SEM micrographs of as-received GNPs powder showing a) N006 grade with 15 m 2 /g (GNP-15), b) M5 grade with 150 m 2 /g (GNP-150), and c) C grade with 750 m 2 /g surface areas (GNP-750);
  • Figure 10 illustrates filtration testing on GNP dispersions
  • Figure 11 illustrates an exemplary embodiment of a Renishaw RM 1000 system
  • Figure 12 illustrates an exemplary embodiment of a JEOL JEM-2100 system
  • Figure 13 illustrates a schematic representation of mixing of a) PET resin and b) GNPs
  • Figure 14 illustrates a solution evaporation approach, a) PET pellets and b) PET pellets coated with GNPs;
  • Figure 15 illustrates a schematic representation of micro-compounding and micro injection molding process showing a) screws, b) control panel to monitor the process parameters, c) micro injection molding unit, d) mold to create tensile bars, and e) PET and nanocomposite tensile bars prepared by melt compounding at 2 wt. % of GNP-15, GNP-150, and GNP-750;
  • Figure 16 illustrates a schematic representation of preparation of PET powders using a mill equipment;
  • Figure 17 illustrates exemplary photos showing dry mixed GNPs with PET pellets, a) and b), and a SEM micrograph collected from the PET pellets-GNP mixture, c), mixture of GNPs with PET powders, d) and e), and a SEM micrograph collected from the PET powders-GNP mixture, f);
  • Figure 18 illustrates a schematic representation an ES reactor
  • Figure 19 illustrates a formation of BHET during an ES reaction
  • Figure 20 illustrates a schematic representation a PC reactor
  • Figure 21 illustrates a formation of PET during a PC reaction
  • Figure 22 illustrates a multiplicity of PET-GNP nanocomposite tensile bars prepared by in-situ polymerized PET-GNP nanocomposite pellets
  • Figure 23 illustrates a schematic representation of an injection molding process to fabricate nanocomposites using PEG-GNP dispersion and masterbatch;
  • Figure 24 illustrates mechanical testing of preforms using a designed fixture
  • Figure 25 illustrates an injection molding machine and a location where PEG dispersions were dosed to mix with PET;
  • Figure 26 illustrates mechanical testing the PET nanocomposite tensile bars, a), and preforms using the tension grips, b);
  • Figure 27 illustrates a schematic of an exemplary SEM system
  • Figure 28 illustrates a schematic representation of XRD measurements showing a) a PET nanocomposite and b) sample geometry, amorphous and stretch sections, with respect to the instrument geometry;
  • Figure 29 illustrates a schematic representation of X-ray computed tomography illustrating the reconstruction process of radiographs into tomographs;
  • Figure 30 illustrates a CIEL*a*b* scale used for color measurements, a), and PET and PET nanocomposites prepared at varied concentrations, b);
  • Figure 31 illustrates measurements of elastic modulus and tensile strength of PET and nanocomposites prepared by melt compounding at 0.001 wt. %, and 2 wt. % concentrations of GNP-15, GNP-150, and GNP-750;
  • Figure 32 illustrates DSC behavior showing the first heating cycle collected from amorphous section of the PET and PET nanocomposites prepared by melt compounding at 0.001 wt. % and 2 wt. % concentrations of GNP-15, GNP-150, and GNP-750;
  • Figure 33 illustrates GNPs surface area vs. T g , T m , and T c collected from the amorphous section of the PET and PET nanocomposites prepared by melt compounding at 0.001 wt. %, and 2 wt. % concentrations of GNP-15, GNP-150, and GNP-750;
  • Figure 34 illustrates crystallinity measurements of the PET and PET nanocomposites prepared by melt compounding at 0.001 wt. %, and 2 wt. % concentrations of GNP-15, GNP-150, and GNP-750;
  • Figure 35 illustrates SEM micrographs collected from the stretch sections of PET and PET nanocomposites prepared by melt compounding at 0.001 wt. %, and 2 wt. % concentrations of GNP-15 and GNP-150;
  • Figure 36 illustrates confocal images collected from PET nanocomposites prepared by melt compounding at 0.001 wt. %, and 2 wt. % concentrations of GNP-15, GNP-150, and GNP- 750, wherein square areas correspond to agglomerated GNPs;
  • Figure 37 illustrates comparisons of XRD 1D patterns of PET and nanocomposites collected from the amorphous and the stretch sections;
  • Figure 38 illustrates 2D diffraction patterns for nanocomposite tensile bars, collected from an amorphous section
  • Figure 39 illustrates 2D diffraction patterns for nanocomposite tensile bars, collected from a stretch section
  • Figure 40 illustrates evaluations of crystallinity through XRD and DSC measurements collected from the amorphous section of the samples prepared by a) GNP-15 and b) GNP-150, wherein uncertainty on XRD area measurements was estimated at 5%;
  • Figure 41 illustrates evaluations of crystallinity through XRD and DSC measurements collected from the stretch section of the samples prepared by a) GNP-l 5 and b) GNP-l 50, wherein uncertainty for XRD area measurements estimated at 5%;
  • Figure 42 illustrates a 3D visualization of PET-GNP nanocomposites, a), identifying GNPs using ortho slices and colormap, b), and representation of the GNPs in a PET matrix, c);
  • Figure 43 illustrates measurements of elastic modulus of PET and PET nanocomposites prepared by melt compounding through powder and pellet mixing methods, wherein the horizontal axis represents nanocomposites at varied concentrations of GNPs compared with pristine PET;
  • Figure 44 illustrates measurements of toughness of a) PET and PET nanocomposites prepared at 2% and 5% concentrations of GNPs and b) nanocomposites prepared at 7.5%, 10%, 12.5%, 15%, and 20% concentrations of GNPs;
  • Figure 45 illustrates measurements of tensile strength of PET and PET nanocomposites prepared by melt compounding through powder and pellet mixing methods, wherein the horizontal axis represents nanocomposites at varied concentrations of GNPs compared with pristine PET;
  • Figure 46 illustrates DSC behavior showing the first heating cycle collected from the amorphous section of the PET and PET nanocomposites prepared by melt compounding through powder and pellet mixing methods
  • Figure 47 illustrates thermal behavior of PET nanocomposites versus concentration of GNPs compared with pristine PET prepared by melt compounding through a) powder and b) pellet mixing methods, wherein standard deviation (SD) of temperature measurements is 0.75 °C;
  • Figure 48 illustrates crystallinity measurements of the PET and PET nanocomposites from injection molding prepared by melt compounding through powder and pellet mixing methods, wherein the horizontal axis represents nanocomposites at varied concentrations of GNPs compared with pristine PET;
  • Figure 49 illustrates non-isothermal crystallinity measurements of the PET and PET nanocomposites prepared by melt compounding through powder and pellet mixing methods, wherein horizontal axis represents nanocomposites at varied concentrations of GNPs compared with pristine PET;
  • Figure 50 illustrates confocal images collected from microtome sections of PET nanocomposites prepared through powder mixing at a) 2 wt. %, b) 5 wt. %, c) 7.5 wt. %, and d) 10 wt. % and through pellet mixing at e) 2 wt. %, f) 5 wt. %, g) 7.5 wt. %, and h) 10 wt. % GNPs, wherein agglomerated GNPs are shown in highlighted regions;
  • Figure 51 illustrates comparisons of XRD 2D and ID patterns of PET and nanocomposites prepared through powder mixing, wherein an inset graph represents the broadened peak observed for graphene at 26.54°2$;
  • Figure 52 illustrates comparisons of XRD 2D and 1D patterns of PET and nanocomposites prepared through pellet mixing.
  • Inset graph represents the broadened peak observed for graphene at 26.54°20;
  • Figure 53 illustrates a pole figure representation of a) geometry of the sample, indicating the area used for measurements in the injection flow direction, with respect to the instrument geometry, wherein data collected from b) pristine PET and c) PET nanocomposites prepared at 2 wt. % and 10 wt. % concentrations of GNPs through powder mixing and pellet mixing methods;
  • Figure 54 illustrates a pole figure representation of a) geometry of the sample, indicating the area used for measurements in the transverse direction, with respect to the instrument geometry, wherein data collected from b) pristine PET and c) PET nanocomposites prepared at 2 wt. % and 10 wt.
  • Figure 55 illustrates TEM micrographs of an as-received GNP-l 5 and GNP dispersions in EG, wherein samples were sonicated for 90 minutes and centrifuged at a) 260 RCF and b) 2350 RCF, and for 180 minutes centrifuged at c) 260 RCF and d) 2350 RCF, and wherein insets represent the binary filter to distinguish the edges of the monolayer graphene;
  • Figure 56 illustrates a) TEM micrograph collected from a grid coated with dispersed GNP-l 5 in EG after sonication of 30 minutes and centrifugation at 260 RCF, b), and c) highlighted regions show isolated few-layer graphene sheets;
  • Figure 57 illustrates a) Cryo-TEM micrograph collected from a grid coated with dispersed GNP- 15 in EG after sonication of 30 minutes and centrifugation at 260 RCF, showing the areas holding the frozen EG, b), and c) highlighted regions show isolated few-layer graphene sheets;
  • Figure 58 illustrates an average length and width measurement of GNPs in dispersions centrifuged at 260 RCF for a) GNP-15 and b) GNP-150, wherein error bars show SD;
  • Figure 59 illustrates an average length and width measurement of GNPs in dispersions centrifuged at 2350 RCF for a) GNP-l 5 and b) GNP-l 50, wherein error bars show SD;
  • Figure 60 illustrates Raman spectra for GNP-l 5 in the dispersion samples illustrating the D, G, and 2D bands shifts, wherein labels indicate:“sonication time” -“centrifugation speed”;
  • Figure 61 illustrates a peak analysis of 2D Raman bands, wherein averaged intensity collected from five different positions of the samples (R 2 ⁇ 0.98), and labels indicate:“sonication time” -“centrifugation speed”;
  • Figure 62 illustrates and evaluation of the stability of GNP dispersions in EG using filtration tests on dispersion samples prepared at a) 0.25 mg/mL and b) 5 mg/rni .;
  • Figure 63 illustrates measurements of the elastic modulus of the PET and PET nanocomposites prepared by melt compounding the in-situ polymerized pellets
  • Figure 64 illustrates measurements of the tensile strength of the PET and PET nanocomposites prepared by melt compounding the in-situ polymerized pellets;
  • Figure 65 illustrates measurements of the toughness of the PET and PET nanocomposites prepared by melt compounding the in-situ polymerized pellets;
  • Figure 66 illustrates crystallinity measurements of the PET and PET nanocomposites prepared by melt compounding the in-situ polymerized pellets, wherein percentile values are relative to PET;
  • Figure 67 illustrates thermal behavior of PET and PET nanocomposites prepared by melt compounding the in-situ polymerized pellets
  • Figure 68 illustrates SEM images collected from PET and PET nanocomposites prepared at varied concentrations of GNPs through melt compounding the in-situ polymerized pellets;
  • Figure 69 illustrates confocal images collected from the PET nanocomposites prepared at varied concentrations of GNPs through melt compounding the in-situ polymerized pellets;
  • Figure 70 illustrates comparisons of XRD 2D and 1D patterns of PET and nanocomposites prepared through melt compounding the in-situ polymerized pellets
  • Figure 71 illustrates a) and b) TEM micrograph of a grid coated with dispersed GNPs in PEG, and c) SAED is taken from the highlighted region;
  • Figure 72 is a graph illustrating volume-weighted particle size distributions of dispersed GNP-15 in PEG-300 dispersions #1, #2, and #3;
  • Figure 73 is a graph illustrating volume-weighted particle size distributions of dispersed GNP-15 in PEG-600 dispersions #4, #5, and #6;
  • Figure 74 illustrates an evaluation of the stability of the GNP dispersions in PEG-300 using filtration tests on dispersion samples prepared at a) 0.25 mg/mL and b) 5 mg/mL;
  • Figure 75 illustrates an evaluation of the stability of the GNP dispersions in PEG-600 using filtration tests on dispersion samples prepared at a) 0.25 mg/mL and b) 5 mg/mL;
  • Figure 76 illustrates measurements of elastic modulus of PET and PEG samples as well as PET nanocomposites prepared by PEG-GNP dispersions and masterbatch with respect to the concentration of the GNPs;
  • Figure 77 illustrates measurements of tensile strength of PET and PEG samples as well as PET nanocomposites prepared by PEG-GNP dispersions and masterbatch with respect to the concentration of the GNPs.
  • Figure 78 illustrates thermal behavior of PET nanocomposites prepared by a) PEG- GNP dispersions and b) masterbatch pellets, wherein an error of temperature measurements is 0.8 °C;
  • Figure 79 illustrates crystallinity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions and masterbatch pellets;
  • Figure 80 illustrates confocal images collected from the PET nanocomposites prepared using PEG-GNP dispersions at varied concentrations of GNPs
  • Figure 81 illustrates F1R-TEM micrographs collected from nanocomposites prepared by a) and b) PEG-GNP dispersion dosing, and c) and d) masterbatch methods at 0.02 wt. %;
  • Figure 82 illustrates luminosity data collected from the nanocomposites prepared by PEG-GNP dispersions and masterbatch pellets
  • Figure 83 illustrates measurements of the elastic modulus and tensile strength of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through centrifugation study;
  • Figure 84 illustrates crystallinity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through centrifugation study;
  • Figure 85 illustrates luminosity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through centrifugation study;
  • Figure 86 illustrates measurements of the elastic modulus and tensile strength of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through concentration study;
  • Figure 87 illustrates crystallinity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through concentration study;
  • Figure 88 illustrates luminosity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method through concentration study;
  • Figure 89 illustrates measurements of the elastic modulus and tensile strength of PEG and PET nanocomposites fabricated by dosing PEG-GNP dispersions that were prepared at 50% and 100% amplitudes;
  • Figure 90 illustrates crystallinity measurements of PEG and the PET nanocomposites prepared by PEG-GNP dispersions dosing through energy study
  • Figure 91 illustrates luminosity measurements of PET nanocomposites prepared by PEG-GNP dispersions dosing method through energy study
  • Figure 92 illustrates sketch of patterns obtained from PET nanocomposites with random orientation of GNPs, for face-on view and preferred orientation for edge-on view;
  • Figure 93 illustrates SEM micrographs collected from stretch sections of PET nanocomposites prepared at 2 wt. % and 5 wt. %, wherein arrows indicate a presence of micro voids at higher concentration of GNPs;
  • Figure 94 illustrates a) Mechanical testing of PET and PET nanocomposites, b) percent elongation of the PET nanocomposites, assuming that the elongation of the pristine PET is 100%, and c) measurements of toughness of PET and PET nanocomposites prepared through powder mixing method;
  • Figure 95 illustrates TEM micrographs collected from dispersions showing a) a grid coated by a sample from experiment 2, b) the binarized image of the sample, c) a grid coated by a sample from experiment 5, and d) the binarized image of the sample, wherein highlighted regions represent a monolayer graphene sheet;
  • Figure 96 illustrates comparisons of confocal images taken from a nanocomposite tensile bar prepared at 2.0% concentration of GNPs through a) melt compounding and b) in-situ polymerization;
  • Figure 97 illustrates comparisons of confocal images taken from a) a nanocomposite preform prepared at 0.006% concentration of GNPs and b) a nanocomposite tensile bar prepared at 2.0% concentration of GNPs through melt compounding;
  • Figure 98 illustrates an electronic structure of a) an insulator and b) graphene
  • Figure 199 illustrates a schematic representation of electron microscopy
  • Figure 100 illustrates a photograph of a typical electron diffraction pattern of a single crystal, wherein a transmitted spot at the center is much brighter than diffraction spots;
  • Figure 101 illustrates a schematic representation of laser diffraction with respect to particle size
  • Figure 102 illustrates a common approach to define distribution width
  • Figure 103 illustrates schematic examples of a) a stable and b) an unstable colloidal dispersion representing aggregation and sedimentation;
  • Figure 104 illustrates TEM micrographs showing agglomeration in GNP-750, wherein samples prepared using probe sonication for a) 30, b) 60, c) 90, d) 120, and e) 180 minutes and centrifuged at 260 RCF.
  • Nanofillers enhance the properties of the polymer matrix, owing to their high aspect ratio.
  • Nanofillers can be classified as either structural or functional. Lightweight materials with high elastic modulus and tensile strength are called structural nanofillers, while nanofillers with other properties such as electrical and thermal conductivity are called functional nanofillers.
  • Nanofillers used in the development of nanocomposites can also be classified into zero-dimensional (i.e . spherical particulates), one-dimensional (i.e. fibers, rods, and nanotubes), and two-dimensional (i.e. layered-platelet) structures.
  • Figure 4 represents typical nanofillers and geometries with their corresponding surface-area-to-volume ratios.
  • Nanoparticles are defined as particulate structures with a dimension in the range of 1 to 100 nm.
  • Metal Fe, Au, and Ag
  • metal oxide ZnO, CaC0 3 , and Ti0 2
  • Zhang et al. found that the tensile strength and elastic modulus of high-impact polystyrene (HIPS) can be increased significantly by the addition of Ti0 2 as low as 2%.
  • HIPS high-impact polystyrene
  • researchers reported a 50% increase in toughness by only adding 5% (vol. %) of Si0 2 in polymethylmethacrylate (PMMA) matrix.
  • Nanoparticles also have applications in biomedical engineering.
  • nanocomposites Various biodegradable polymers have been utilized in the formation of nanocomposites. While the major goals in designing nanoparticles are controlling the nanoparticles’ size and properties, they can be used as potential drug delivery devices, increasing the stability of the drugs. However, some nanoparticles are known to present a toxicity risk.
  • Carbon nanotubes are allotropes of carbon with exceptional properties that have already proven valuable for several applications in industries including electronics, optics, and nanotechnology engineering. CNTs possess a high thermal conductivity of 6000 W/(m.K). The superior mechanical properties of CNTs, Young’s modulus and tensile strength in the range of 0.2-0.9 TPa and 11-63 GPa, respectively, offer exciting opportunities for the development of nanocomposites.
  • Coleman et al investigated the addition of nanotubes in two different case studies. They reported an increase of 370% in elastic modulus, 430% in tensile strength, and 170% in toughness when added to polyvinyl alcohol (PVA) at less than 1 wt. %, and in polypropylene (PP), the addition of CNTs at equivalent loadings, resulted in an increase of 310%, 390%, and 440% in modulus, strength, and toughness, respectively.
  • PVA polyvinyl alcohol
  • PP polypropylene
  • Nanostructures such as nanoplatelets or layered materials can be classified as two- dimensional (2D) nanofillers. Improvement in mechanical properties of nanocomposites have been observed when a 2D nanofiller is incorporated in the polymer.
  • Clays are naturally found as platelets and are stacked layers ranging from few- to thousands of individual layers that possess Young’s modulus from 0.18 to 0.26 TPa.
  • One layer of clay has a thickness of 1 nm with platelet widths being in the range of 100 to 200 nm.
  • the majority of recent research has focused on nanocomposites based on layered materials such as silicate compounds and synthetic clay.
  • Toyota Central Research & Development Co. Inc. fabricated the first successful nanocomposites (Nylon 6/Clay) in 1994. According to Yu et al, clays can be used to enhance the mechanical and physical properties of polymers due to their high aspect ratio and large surface area-to- volume ratio.
  • clay is one of the most commonly used nanofillers for creating nanocomposites
  • manufacturing of polymer nanocomposites with efficient mechanical use of the clay is challenging.
  • Organic modification of the clay is generally needed to promote improved intercalation in the polymer matrix.
  • nanofillers like clay are often from natural sources such as montmorillonite, which contains ions or contaminants and influences the performance of the final product.
  • Garcia et al. showed that silicate composites possess weak electrical and thermal conductivity.
  • improving several properties simultaneously without negative impact on any key property, can be achieved when the dispersion and the interfacial interaction between the nanofiller and the matrix are controlled.
  • Gupta et al. reported on the challenges of clay -based nanocomposites. According to them, in many cases, the performance of the final product did not meet expectations regarding the improvement in useful properties. While it has been shown that the addition of clay could increase the stiffness of thermoplastics, for example, they found that the strength of the matrix would ultimately decrease.
  • graphite is a crystalline allotrope of carbon. Graphite is chemically similar to CNTs and structurally analogous to layered silicates. When exfoliated into an individual layer, the sp 2 bonded carbon layers are isolated and are referred to as a“graphene sheet”. Graphene is a planar, electrically conductive, elastic, crystalline allotrope of carbon that can be described as a one-atom-thick layer, arranged in a 2D, hexagonal pattern.
  • Graphene has a very high strength-to-weight ratio, with a bond length of the C-C bond 0.14 nm and a thickness of a single graphene sheet 0.34 nm.
  • Figure 5 illustrates a schematic of graphene’s hexagonal structure.
  • Carbon nanomaterials such as CNTs and graphene are advantageous over clay, due to their superior mechanical, thermal, and electrical properties. Recent research shows that graphene is even more advantageous and likely to be used as alternative nanofiller to CNTs in the production of polymer nanocomposites. As stated earlier, graphene offers enhanced mechanical properties over CNTs. This is due to the planar structure and the aspect ratio provided during the nanocomposite processing. The current research progress on graphene has helped finding potential applications for graphene-based nanocomposites. However, like the other nanofillers, the properties of graphene-polymer nanocomposites depend on the extend of distribution of graphene in the polymer matrix.
  • Figure 6 illustrates the crystal structure in graphene.
  • Each carbon atom of a graphene sheet uses three atomic orbitals (s, p x , and p y ) to form sp 2 bonded carbon atoms and makes a strong covalent bond with three neighboring carbon atoms, giving rise to a C-C-C bond with 120 °C angle, shown with the shaded region.
  • the final p z orbital is responsible for the p-bond that is oriented out of plane and is due to the overlap between p z orbitals.
  • Bernal stacking forms, when half of the atoms lie over the center of a hexagon in the lower graphene’s layer and half lie over an atom.
  • GNPs graphene nanoplatelets
  • Graphene can be produced in a form called graphene nanoplatelets (GNPs).
  • GNPs are nanoparticles in stacks of small graphene sheets between 5-50 layers thick.
  • GNPs with wide aspect ratio, represent a new class of graphene.
  • the platelet shape of GNPs results in a relatively higher number of carbon edges per unit volume, making them easier to chemically bond and change the fundamental properties of the polymer matrix.
  • they can create electrically and thermally conductive materials.
  • using GNPs can improve the electrical conductivity of thin film as high as 2,200 S/cm, significantly higher than that formed by other carbon-based materials, (i.e. CNTs).
  • GNPs are potential candidates to improving barrier properties, modulus, and surface toughness, after being incorporated into a polymer matrix. More recently, Dr. Bor Jang, from Wright State University, investigated developing GNPs suitable for applications such as conductive composites, heat radiation, conductive inks, and rubber. Table 2 summarizes the specifications of the investigated GNPs used in the current research.
  • Table 2 XG-Sciences and Angstron GNPs physical properties.
  • Sonicators either produce the ultrasonic waves from the outside of a container into a water bath, wherein samples are submerged (called bath sonicators) or can be propagated down a probe that is immersed directly into the sample (known as probe sonicators).
  • bath sonicators or can be propagated down a probe that is immersed directly into the sample (known as probe sonicators).
  • probe sonicators During sonication, the ultrasonic waves radiate through the medium with rapidly alternating low and high pressures resulting in cavitation. In the low-pressure stage, millions of micro-bubbles form and grow. The following high-pressure stage collapses the bubbles and releases a large amount of energy.
  • the power delivered to the convertor with the probe in air can be recorded. Without changing the amplitude, the probe should be immersed into the sample and the amount of delivered power can be again recorded.
  • the difference between power readings is divided by the area of the probe to calculate the power that is being delivered to the sample (power density) using the following equation: where P is the power density (Watts/cm2), P 2 is the power when probe is immersed (Watts), Pi is the power when probe is in air (Watts), and r is the radious of probe tip (cm).
  • P the power density
  • P 2 the power when probe is immersed
  • Pi the power when probe is in air
  • r is the radious of probe tip
  • E the energy density released to the sample during sonication (J/cm2)
  • P power density (Watts/cm2)
  • t time (s).
  • the generator transforms AC power to a 20 kHz signal that drives a converter.
  • the signal is converted to a mechanical vibration, which is then amplified and transmitted through the probe’s tip which is immersed in the sample.
  • the measurement of the tip’s excursion is referred to as amplitude and can be set manually during sonication.
  • Amplitude is an important parameter in probe sonication. Operation at low or high amplitude will deliver low and high intensity, respectively.
  • bath sonication provides a weak sonication, with approximately 25 Watts of output power
  • probe sonication provides a higher output, resulting in a uniform ultrasonic transmittance and cavitation. Due to the uniform cavitation in probe sonication, the effectiveness of the sonication process is much higher, offering a potential application in dispersing nanomaterials in liquids.
  • DH,hic enthalpy of mixing per unit volume (mJ/m3)
  • V m ix is the volume of mixture
  • Tfiake is the thickness of graphene flake
  • f is volume fraction of graphene
  • Exfoliation happens when the energetic penalty between the medium and graphene is minimized.
  • surface energy can be defined as the energy per unit area required to overcome the Van der Waals forces, when peeling two sheets apart.
  • Van der Waals forces between graphene sheets ⁇ 6l meV per C atom
  • a good exfoliation of graphene in a dispersion medium suggests the enthalpy of mixing to be close to zero. This suggests that liquid media with surface energies matching that of graphene would lead to more exfoliated dispersions than others.
  • surface tension has also been used to better understand the interaction between a solvent and graphene and the wettability of graphene from a thermodynamics viewpoint.
  • S w /g Yg — Yw — Ygw ⁇ 0 (5)
  • S w/g is the spreading coefficient (mN/m)
  • y g is the surface tension of graphene (mN/m)
  • y w is the surface tension of liquid water (mN/m)
  • y gw is the interfacial energy of the water/graphene interface (mN/m).
  • a negative spreading coefficient reflects the hydrophobicity of a material.
  • the surface tension of water at 25 °C is about 72.8 mN/m whereas the surface energy of graphene is estimated as 46.7 mN/m.
  • the interfacial energy has been estimated to be around 90.5 mN/m, suggesting the spreading coefficient to be negative and confirming the hydrophobicity of graphene.
  • the first group of dispersion media are those with high surface energy. For these, the surface energy is usually close to that of graphene, which helps disperse graphene without the use of any stabilizing agents.
  • Coleman et al. have published several studies on using sonication and centrifugation methods to disperse graphene in a wide range of dispersion media including non- polar solvents such as dimethylformamide (DMF), and n-methyl-2-pyrrolidone (NMP).
  • DMF dimethylformamide
  • NMP n-methyl-2-pyrrolidone
  • graphene is non-polar and it does interact well with non-polar solvents. Though non-polar solvents are more likely better media to achieve a graphene dispersion, many of them, (e.g. NMP), are expensive and highly toxic. Moreover, the final concentration may not be high enough for many industrial applications. In the studies by Hernandez et al, graphene was dispersed at a low concentration of 0.01 mg/mL.
  • the other group of dispersion media are those with low surface energy such as isopropyl alcohol (IP A) and water. Due to the hydrophobicity of graphene, these media are usually combined with stabilizing agents, (i.e. surfactants).
  • surfactants refer to a class of molecules that tend to adsorb onto a molecule to lower the surface tension between the molecule and the dispersion medium. To understand the effects of surfactants in graphene dispersions, we must consider the structure of these molecules.
  • a surfactant is comprised of two regions. The first region is known as the hydrophobic tail, whereas the latter one is known as the hydrophilic head.
  • Stabilizing the graphene dispersions with surfactants involves an interaction between the hydrophobic tails of surfactants with graphene, while the hydrophilic regions are attracted to water molecules. According to Green et al. , stabilizing graphene with surfactants can increase the degree of exfoliation in aqueous dispersions up to 60% while the concentration of graphene is estimated around 0.012 mg/mL.
  • Table 3 Potential solvents and surfactants to create graphene/graphene oxide dispersions.
  • Graphene dispersions in an appropriate medium can be incorporated into polymer matrices through in-situ polymerization. Depending on the chemical structure of the host polymer, different media can be selected to create a graphene dispersion.
  • Table 4 A list of research reported on in- situ polymerization for the development of nanocomposites using graphene-based materials with different polymer matrices is summarized in Table 4. In an ideal situation, graphene would be uniformly incorporated into the polymer matrix. However, depending on the polymer molecule’s chain structure, graphene may or may not affect the properties of the nanocomposite. For example, in the studies reported in polymerization of PMMA-based nanocomposites, while Jang et al.
  • One published method uses graphene dispersions prepared primarily using non-polar solvents.
  • the non-polar solvents typically have high boiling points, leading to difficulties in both removal of the solvent during composite preparation, and the formation of aggregations of graphene during solvent evaporation.
  • Functionalization can improve the dispersibility of graphene.
  • Functionalization can be divided into non-covalent (e.g . p-p interactions and surfactants) and covalent functionalization (e.g. graphene oxide (GO) and reduced graphene oxide (rGO).
  • surfactants is the most promising route to improve the dispersion of graphene in a polar solvent. However, surfactants can interfere with polymerization during the formation of polymer nanocomposites.
  • the interaction between the surfactant molecules and the polymer matrix depends on the molecular structure of both components.
  • the presence of the surfactant molecules in a polymeric matrix can detrimentally alter the properties of the polymer. Removing surfactant molecules before the incorporation into the polymer adds complexity to the process and increases the production cost of nanocomposites.
  • Table 4 Research on fabrication of nanocomposites through in-situ polymerization.
  • PET pellets (average pellet height and diameter of 3.10 mm and 2.10 mm, respectively) were ground into fine powders (average particle size of 0.8 ⁇ 0.1 mm).
  • GNPs from XG Sciences and Nano Graphene Platelets from Angstron Materials (see Table 2) were obtained. As shown in Figure 9, they are agglomerated particles in platelet shape, each consisting of several graphene layers stacked together. Masterbatch pellets were also utilized in this research. Using a twin- screw compounder, the GNP-15 were mixed with PET to achieve a masterbatch at final concentration of 1 wt. %. The masterbatch pellets were then diluted with PET for the preparation of the PET nanocomposites.
  • PEG and EG are polar compounds due to the presence of a hydroxide group in their molecular structures.
  • PEG possesses higher viscosity compared to EG.
  • Table 5 summarizes the properties of EG, PEG-300, PEG-400, and PEG-600.
  • GNP-15, GNP-150, and GNP-750 may be used to prepare GNP dispersions for various experimental studies.
  • Probe and bath sonication techniques were used in different studies to prepare the GNP dispersions. Water temperature increases during sonication over a prolonged period, causing considerable evaporation. This leads to a decreasing water level in the sonicator and an uneven distribution of energy to the samples.
  • a water pipe and pump were installed in the tank to circulate water between the bath and a chilled water source to keep the temperature under 40 °C.
  • the sample beaker was placed in a temperature-controlled water bath (maintained between 50 to 60 °C) for the duration of sonication. After sonication, the sample was divided into two portions to then transfer to two plastic centrifuge tubes. Each centrifuge tube was filled with 30mL of the sonicated dispersion pipetted from the middle of the beaker to avoid sediment. Then, centrifugation was performed at rotational speeds of 1500 and 4500 RPM (revolutions per minute) for 45 minutes. During the centrifugal acceleration, sedimentation of GNPs happens in response to the forces acting on them.
  • the force exerted on GNPs in the centrifuge is traditionally named“relative centrifugal force”, G-Force (RCF), and is a simple function of the rotational speed and can be calculated using the following equation:
  • G-F orce 1.12 xR x (RPM/ 1000) 2 (6) where R is the radius of rotational radius in centimeters (cm), and RPM is rotational speeds measured in revolutions per minute. After centrifugation, the top 10 mL of the six supernatants was carefully pipetted and transferred for further use.
  • Table 6 summarizes the GNP dispersions prepared by the probe and bath sonication techniques for various purposes.
  • Table 7 summarizes the technical and experimental applications of the dispersions used in current research.
  • Table 7 Applications of GNP dispersions in EG, PEG-300, PEG-400, and PEG-600.
  • A aCL (7)
  • A absorbance of liquid
  • a absorption coefficient mL/(mg.m)
  • L cell path length (m)
  • C concentration of material (mg/mL).
  • the BL law can be used to measure the concentration of exfoliated graphene dispersed in solvents examined with spectrophotometry analysis.
  • the concentration of material remaining after centrifuge can be evaluated by measuring the optical absorbance and can be correlated to the concentration of graphene after centrifuge (CG) using BL once the absorption coefficient is known. While the concentration of graphene depends on several factors including flake size and thickness, it is important to emphasize that BL law is only valid for dispersions with a relatively low concentration.
  • the concentration of actual dispersed GNPs in each sample was calculated. Measured concentrations were correlated with the ratio of the absorbance values per path length (A/L) of the corresponding sample using the BL law, to then calculate the absorption coefficient.
  • Raman spectroscopy was carried out for five different locations on each sample at room temperature (see Fig. 11).
  • a 20x objective lens with a working distance of 12 mm and a 50% density filter were used for measurements.
  • lasers with different excitation wavelengths can be used to generate Raman scattering.
  • the Raman signal is normally proportional to the amount of radiated laser’s power. The higher the power, the stronger the signal.
  • high power lasers can modify the structural or chemical properties of materials due to heat generation. To avoid this, the laser power was kept at 1 mW using 20% of the laser power.
  • Sample preparation was done by pipetting a small quantity of the dispersion samples to glass slides, which were then heated to 200 °C for 30 minutes to dry them out.
  • the PEG dispersions were evaluated for GNP size distribution using laser diffraction.
  • the samples for size measurements were divided into two sets based on the viscosity of the dispersion media.
  • the as-received GNP powders were used as a reference for measurements.
  • the Hydro MV and Aero S accessories were used to analyze the wet dispersions and the GNPs powder, respectively.
  • For wet analysis a few drops of dispersion were added to the Hydro MV tank until a sizable obscuration was obtained.
  • a high disperser pressure, 4 bar, was used to complete the dry analysis.
  • a general refractive index of 1.58/1 was used for the analyses.
  • the dispersion samples were prepared using the GNP- 15 and PEG-300 and PEG-600, at a concentration of 5 mg/mL. Table 8 summarizes the samples with the process parameters used for testing.
  • the particle size distribution was calculated based on the Mie theory of light scattering. Based on this theory, three percentile values, which include D X 10, D x 50, and D x 90, are selected to define the volume-weighted distribution of the population.
  • Table 8 Dispersed GNP- 15 samples evaluated for particle size measurements through laser diffraction.
  • Table 9 Summarizes the nanocomposites fabricated through injection molding.
  • nanocomposite samples were prepared and were divided into two different groups depending upon the approach that had been selected to mix the GNPs with PET resin.
  • a double cavity mold with a dogbone shape was used to make the tensile bars based on the ASTM D 638 standard, type I specification.
  • nanocomposite tensile bars were fabricated. Nanocomposite tensile bars prepared at 2 wt. % are shown in Fig. 15.
  • FIG. 16 represents mixing methods of GNPs with PET pellets (Figs. l7a-c) and powders (Figs. l7d-f). To study the effects of powder mixing, the GNP-l 5 were taken and mixed with both PET powders and pellets at varied concentrations, summarized in Table 10.
  • Table 10 Summarizes the PET-GNP nanocomposites fabricated through melt compounding of the materials.
  • PET polymerization was attempted using a melt-polymerization unit, available at the polymer institute at the University of Toledo, equipped with an esterification (ES) reactor and a polycondensation (PC) reactor, each with a 3L capacity.
  • ES esterification
  • PC polycondensation
  • the GNP-15 were selected to prepare the dispersions in EG. Bath sonication was utilized for 60 minutes to disperse the GNPs in EG immediately before it was introduced into the reactor. The amount of graphene needed to prepare the dispersions was calculated based on the desired graphene weight fraction in the theoretical yield of PET during the PC reaction, -1.384 kg, and it was dispersed in 0.672 kg of EG for each batch. With the EG/TPA molar ratio being set at 1.5, the dispersions were added to 1.2 kg of TPA to start with the ES reaction.
  • Figure 18 illustrates the components involved in the ES reactor.
  • the reactor was pressurized with N 2 to minimize the 0 2 inside the reactor and a high pressure (2.8 kgf/cm 2 ) was used to facilitate the dissolution of TPA in EG. 295 m ⁇ of tetramethylammonium hydroxide (TMAH) was added to the mixture to act as diethylene glycol suppressor. Concentration of TMA1T was set to be 40 ppm in the final PET product.
  • An anchor-type stirrer was utilized for the reaction. The stirrer’s rotational speed was set at 50 RPM and then was increased to 100 RPM during the reaction. During the reaction, the set-point and actual temperatures of the reactor, temperatures of the reflux column, pressure inside the reactor, and the stirrer’s rotational speed were monitored and recorded.
  • the reactor temperature was set at 100 °C. Once the ES reactor’s temperature reached the set-point, it was raised in steps of 5 °C until it reached 240 °C. This was repeated throughout the reaction, and the change in the temperature was monitored every 15 minutes.
  • the bottom portion of the reflux column stays hotter than the top portion of the column. Due to the temperature gradient inside the reflux column, EG vapor condenses as it reaches the top portion of the column and comes back to the reaction chamber.
  • the esterification reaction takes place at a high temperature between 220 to 240 °C which produced bis(2 -hydroxyl ethyl) terephthalate (BHET) with water as a by-product.
  • BHET bis(2 -hydroxyl ethyl) terephthalate
  • the solutions were prepared in such a way that the final concentrations of antimony and cobalt, in the final PET product, were set to 260 ppm and 120 ppm, respectively.
  • the solutions were then added to the mixture along with 50 m ⁇ phosphoric acid.
  • the PC reactor while pressurized, was used at 285 °C for 40 minutes to mix the blend using a helical-type stirrer.
  • a high vacuum ⁇ 4 Torr
  • the excess EG and the EG formed during the PC reaction were collected in a vessel. Dry ice was used to keep the liquid solidified to prevent flowing back into the vacuum.
  • the intrinsic viscosity (I.V.) was monitored and recorded. The reaction was considered finished after achieving a desired I.V. (> 0.60 dL/g) of the polymer melt.
  • the polymer strands were collected from the bottom of the PC reactor on a winder, fast-cooled in an ice/water bath, and air-dried overnight to reduce the residue of water. Strands were copped for pelletizing. Pellets were vacuum-dried overnight at 120 °C.
  • the schematic shown in Fig. 21 summarizes the synthesis of PET through the PC reaction.
  • I .V. is a measure of the polymer's molecular weight, and is correlated with the polymer’s other properties (e.g. the melting point, crystallinity, and the tensile strength). Polymers with higher I.V. often exhibit greater tensile strength compared to those with lower I.V. As mentioned in the previous section, during the PC reaction the I.V. was monitored. With an objective of improving the I.V. of the polymer obtained after polymerization, solid state polymerization (SSP) was carried out. SSP was done at 220 °C to remove volatiles (e.g. air and water) from the polymer.
  • SSP solid state polymerization
  • An inert gas (N 2 ) is purged to remove the by-products of the reactions (e.g. ethylene glycol and acetaldehyde). These by-products diffuse to the surface of the polymer and are carried away by the inert gas flow or vacuum.
  • the polymer chain lengths are increased, and as a result, the I.V. of the polymer improves.
  • SSP can be carried out from 2 to 8 hours (the higher the initial I.V., the shorter the SSP and vice versa).
  • melt viscosities were measured.
  • PET nanocomposite pellets were prepared by adding GNP dispersions at varied concentrations, summarized in Table 11 , and processed using bath sonication for 60 minutes immediately before addition to the reactor. Additionally, a GNP dispersion, processed for 90 minutes and centrifuged at 260 RCF, was prepared using probe sonication, in 12 small batches (due to equipment size and volume constraints) approximately one week before use at a different facility. The small batches were mixed into one container before shipment to the facility with the polymerization reactors. There, the dispersion was bath sonicated for 10 minutes to re-disperse the GNPs immediately before introduction to the reactor. Table 1 1 summarizes the dispersion samples prepared for the polymerization experiments.
  • Table 11 Summarizes the performed polymerization reactions to fabricate the PET-GNP nanocomposite pellets.
  • the PET-GNP nanocomposite tensile bars were fabricated by melt compounding the PET-GNP nanocomposite pellets.
  • Figure 22 represents the PET-GNP nanocomposites prepared by experiments 1 to 6. The PET-GNP nanocomposites were examined for their I.V. The data collected from the samples before SSP, after SSP, and after melt compounding are presented in Table 12.
  • Table 12 Summarizes the intrinsic viscosity measured for PET and PET nanocomposites.
  • PET and PET nanocomposite were fabricated using the PEG-GNP dispersions and masterbatch pellets to further understand and evaluate the effects of sonication on the properties of the final product.
  • GNP-15 were first dispersed in PEG-600 through probe sonication.
  • the GNP dispersions were added to PET melt using dosing equipment as the screw barrel is filled with new polymer. Desired dosing rates were employed for the dosing process to achieve known concentrations of GNPs in the PET nanocomposites. The details including the concentration of the dispersions, dosing rates, and the concentrations of the nanocomposites are summarized in Table 13.
  • Table 13 Process parameters involved to fabricate PET nanocomposites.
  • Table 14 Process parameters involved to fabricate PET nanocomposites.
  • Figure 23 illustrates the manufacturing process of the PET nanocomposites.
  • the PET nanocomposites shown in Fig. 24, were prepared based on an experimental method performed by Bandla el al.
  • the preforms produced through injection molding have a tubular shape, making them difficult to mount on standard Instron grips.
  • the tubular-shaped preforms were tensile-tested according to the ASTM D 638 standard.
  • a custom-made fixture (Fig. 24) was designed for mechanical testing of nanocomposite tensile preforms.
  • the 90-ton injection molding machine shown in Fig. 25 is located at Niagara Bottling LLC’s research facility in Ontario CA, is equipped with a screw of 38 mm diameter. Four preforms, each 9.4 grams, were produced through each injection shot.
  • PEG-400 was used as control samples.
  • X-Ray diffraction a non-destructive analytical technique, is commonly used to evaluate the atomic structure of crystalline materials.
  • GNPs exhibit“Graphene-2H” reflections corresponding to the (002) plane (26.54 °2Q for Cu a X-rays).
  • the triclinic crystal structure of PET can be observed with four principle reflections from the (010), (110), (100), and ( ⁇ 05) planes (17.5°, 22.5°, 25.6°, and 42.6 °2Q for CuXa X-rays).
  • XRD analysis can also be informative to understand the effects of GNPs’ content on the crystallinity of the nanocomposites.
  • the general area diffraction detection system was used to investigate the crystallographic textures of the nanocomposite samples prepared by a dry mix of the GNPs with PET powders and pellets at 2 wt. % and 10 wt. %.
  • the 2D diffraction patterns were integrated along 2Q for every 1 ° in c direction.
  • the data are plotted as pole figures and presented plane for both the PET and PET nanocomposites in terms of contours of intensity of reflections from the (002) plane.
  • X-Ray computed tomography is a non-destructive technique that offers 3D imaging of materials. It involves computed X-ray measurements to produce cross- sectional (tomographic) images of specific areas of a scanned sample. The X-rays can be transmitted through the specimen and can be correlated with the specimens’ properties using the following equation:
  • I I 0q ⁇ mhiRC (8)
  • I the transmitted X-ray intensity
  • I 0 the initial X-ray intensity
  • p m mass attenuation coefficient
  • p density
  • x the material thickness.
  • MCT was performed.
  • MCT was carried out on the PET nanocomposite sample prepared by mixing PET pellets with GNP-15 at a concentration of 2%.
  • a bulk section of the sample (200 pm x 200 pm x 1000 pm) from the outer surface of the amorphous section of the sample was scanned on Zeiss Xradia 410 X-ray computed tomography system at 0.97 pm/pixel resolution. Radiographs were collected and the reconstructed tomographs were visualized using a 3D visualization software.
  • DSC Differential scanning calorimetry
  • melting temperature (T m ) and glass transition temperature (71.) were determined from the second heating cycle.
  • the crystallization temperature (T c ) was taken from the first cooling cycle.
  • the heat of fusion and the heat of cold-crystallization were collected from the first heating cycle to determine the crystallinity of the samples.
  • the crystallinity of the samples was evaluated using the following equation: _ [ AHf-AHc
  • AH f is the heat of fusion (J/g)
  • AH Cc is the heat of cold- crystallization (J/g)
  • AH ° c is the heat of fusion for 100% crystalline polymer, 140.1 (J/g) for PET.
  • FIG. 30 represents the measurement scale as well as the samples used in this research.
  • L * refers to luminosity and measures lightness of the samples, ranging from 100, for white, to 0, for black.
  • a * measures redness when positive, gray when zero, and greenness when negative.
  • the b * measures yellowness when positive, gray when zero, and blueness when negative.
  • luminosity of PET and PET nanocomposites were evaluated using a VIS-IR spectrophotometer in transmission mode.
  • the nanocomposite tensile bars were produced to evaluate the effects of the surface area of the GNPs and the effects of the mixing method of PET with GNPs on the properties of the final product.
  • Figure 33 presents the thermal behavior of the samples with respect to the surface area of the GNPs at concentrations of 0.001 wt. % and 2 wt. %. While increasing the concentration of the GNPs did not significantly affect the Tm, the glass transition of the PET nanocomposites prepared by GNP- 150 at both concentrations showed a decreasing trend. The crystallization temperature increased with increase in the surface area of the GNPs (Fig. 33). A comparison of the percent crystallinity of the tensile bars prepared by the GNPs with varied surface areas is shown in Fig. 34.
  • PET-GNP nanocomposites prepared through pellet mixing at 2 wt. % was analyzed by X-ray CT to characterize the level of distribution of GNPs.
  • Figure 42b shows a cross-section. Microvoids were observed at a cross-section of the sample, indicating poor processing of melt- compounded GNPs with PET during injection molding (see Fig. 42). It is unclear if this is related to the process parameters or the concentration of GNPs. Therefore, further research is required to study the effect of the concentration of GNPs in PET on the formation of microvoids. This can be done using MCT analysis.
  • the GNP- 15 In the study of the effect of surface area of GNPs on the properties of PET, the GNP- 15 exhibited a higher mechanical gain compared to other grades.
  • GNP-15 To further study the effect of GNP-15 on nanocomposite properties, they were added to PET pellets and powders at different concentrations, as explained in section 3.4.1.
  • the elastic modulus of PET nanocomposites prepared through powder mixing shows an increasing trend and can yield a maximum of 182%, at 20 wt. % concentration of GNPs, which is 38% higher than those prepared through pellet mixing.
  • PET nanocomposites prepared through powder mixing significantly increased in tensile strength over PET. PET and PET nanocomposites were also examined for toughness. Measurements are shown in Fig. 44. As seen, the toughness consistently decreases as the concentration of GNPs increases.
  • Figure 47 presents the glass transition temperature (T g ), melting temperature ( T m ), and crystallization temperature (T c ) for the samples prepared through powder and pellet mixing methods with respect to GNP weight fractions. While increasing the concentration of the GNPs in powder mixing did not significantly affect the T g , the glass transition of the PET nanocomposites prepared through a dry mix of GNPs with PET pellets showed a decreased trend at 7.5 wt. % and 10 wt. %. The crystallization temperature, however, increased to higher values by increasing the GNPs concentration. The percent crystallinity of the nanocomposite tensile bars presented in Fig. 48 showed an increasing trend with respect to GNP concentration.
  • FIG. 50 represents the internal structures of the nanocomposites prepared at increasing concentrations of the GNPs (e.g. 2 wt. %, 5 wt. %, 7.5 wt. %, and 10 wt. %) through powder and pellet mixing methods, respectively.
  • concentrations of the GNPs e.g. 2 wt. %, 5 wt. %, 7.5 wt. %, and 10 wt. %
  • the distribution of GNPs inside the PET-GNP nanocomposites consisted of agglomerated GNPs; however, the samples that were prepared by a mixture PET pellets with GNPs at 7.5% and 10% concentrations did so to a greater degree.
  • the size of the agglomerates was in the range of 50 to 60 pm (see Fig. 50g and Fig. 50h). Based on the data collected from confocal microscopy, it was found that mixing GNPs with PET powders lead to a more uniform distribution of GNPs in the matrix compared to the mixture with PET pellets. The higher improvements in the elastic modulus of the samples confirm this observation as well.
  • Diffraction patterns were collected from PET and PET nanocomposite tensile bars.
  • Figures 51 and 52 represent the 2D and 1D diffraction patterns collected from the samples prepared through powder and pellet mixing methods, respectively. While the PET spectrum represents an amorphous structure, the peak broadening observed for the graphene peak at 26.54 °2Q is indicative of the presence of platelets. The intensity of the peak increased with increasing concentration of GNPs. As seen, the nanocomposite tensile bars exhibit a broad hump around 19 °2Q.
  • pole figures for the (002) diffraction plane representing the presence of graphene
  • Figures 53 and 54 show the pole figures for PET-GNP nanocomposites, prepared at increasing concentrations and mixing methods, on the injection flow direction (face on view) and the transverse direction (edge on view), respectively.
  • the graphene peak in the pole figures can be used to measure the orientation of the GNPs in the PET matrix. From the pole figures, it was observed that increasing the concentration of GNPs, from 2 wt. % to 10 wt. % as well as the mixing methods have similar impact on orientation of the GNPs.
  • the GNPs exhibited a random orientation distribution in the face on view direction, along the axial direction of the tensile bar, and a preferred orientation in the edge on view direction, along the thickness of the tensile bar.
  • EG one of the raw materials in polymerizing PET, was selected as the dispersion medium.
  • the following sections summarize the preliminary results obtained by characterizing the GNP dispersions in EG.
  • Monolayer graphene can be identified from the bright field TEM micrographs because of their well-defined edges. Multi-layer graphene, however, can be identified from the larger objects, contiguous clumps extended over several grid openings, regularly observed in the original pre-sonication samples.
  • TEM micrographs of the as-received GNP- 15 and the dispersion samples sonicated for 90 and 180 minutes and centrifuged at 260 and 2350 RCF were taken and analyzed using binary filters.
  • Figure 55 represents the analysis of TEM micrographs taken using GNP-15 and the dispersion samples prepared by the same GNPs. The analysis with binary filters indicates the presence of monolayer graphene from edges, as marked with red arrows, in the dispersion samples (see Fig. 55). As seen, an isolated monolayer graphene was observed in all the dispersion samples.
  • Figure 56 shows micrographs of TEM grid of GNP-15 prepared using the samples that were sonicated for 30 minutes and centrifuged at 260 RCF. During the analysis of the TEM micrographs in previous work, binary filters were applied to help distinguish few-layer GNPs. Here, as shown in Fig. 56a, the isolated platelets consist of few layers. [00219] To limit the effects of potential heat trauma from sample preparation for traditional TEM, we investigated the same type of samples from the previous section using Cryo-TEM. Figure 57 represents the micrograph. As shown, few-layer graphene sheets, with a similar geometry to those observed in Fig. 56 were captured. A minimal surface contamination (i.e. moisture from the air) was observed during imaging, which could be attributed to blotting during sample preparation.
  • a minimal surface contamination i.e. moisture from the air
  • FIG. 58 and 59 show the size distribution of GNP-15 and GNP-150.
  • Statistical analysis of TEM micrographs shows that by increasing the sonication time from 30 to 90 minutes, the average length of the GNPs for samples centrifuged at 260 RCF decreases from 1.5 to 1.2 pm, whereas the average width decreases from 0.9 to 0.8 pm, resulting in 20% and 11% decrease, respectively.
  • the average length and width of the platelets remained almost same at 0.9 and 0.6 pm, respectively. Additional data related to the degree of exfoliation can be generated by calculating the area of the GNPs.
  • Sonication time is negatively correlated with platelet size: the longer the sonication time, the smaller the size and area of the GNPs after sonication.
  • Table 18 summarizes the GNPs average areas. The values significantly dropped at the 180-minute sonication time point.
  • Table 19 Sample preparation for filtration testing using EG as the dispersion medium.
  • Table 21 The concentration of GNPs in EG dispersions as a function of sonication times and centrifugal forces. Sonication was performed using a probe sonicator in 30-min increments between 30 to 180 minutes.
  • Table 22 The concentration of GNP dispersions in EG as a function of sonication times and centrifugal forces. Sonication was performed using a bath sonicator in 24-hour increments between 24 to 120 hours, shown in minutes.
  • Figure 60 represents the evolution of the D, G, and 2D Raman bands of sonicated dispersion samples after centrifugation.
  • the dispersion samples that were sonicated for shorter times, (e.g. 30 and 60 minutes), and centrifuged could not be used for measurements by Raman spectroscopy. It appears that after heat treatment and drying on the glass slide, there were not sufficient GNPs on the glass slide to obtain Raman spectra due to the low concentration of the GNPs in the dispersion samples.
  • Raman spectra from the aforementioned samples were collected, and analyzed for the shift in 2D band of the spectra. Band shift was determined by integrating the Gaussian peaks in the spectra.
  • Figure 61 illustrates the peak analysis of the averaged 2D band of the Raman spectra collected from the GNP dispersions in EG.
  • the shape of the 2D bands from the Raman spectra of dispersion samples are almost identical, but significantly different from the spectra collected from the as-received GNPs.
  • PET nanocomposites were also examined for their toughness. As shown in Fig. 65, the PET nanocomposites prepared at concentrations greater than 0.1 wt. %, seems to show a more stabilized behavior in the toughness compared to those prepared at lower concentrations.
  • Figure 66 represents the crystallinity measurements of PET and PET nanocomposites. As shown, the percent crystallinity of the samples, shown on the graph, seem to increase at concentration of GNPs greater than 0.1 wt. %. Thermal properties of the samples are illustrated in Fig. 67. While the T g does not show a significant change, the T m and T c exhibit increasing trend for samples that were prepared at concentrations greater than 0.1 wt. %.
  • PET nanocomposites prepared at 0.004 wt. %, 0.1 wt. %, 0.5 wt. %, 1 wt. %, and 2 wt. %, were examined by SEM to analyze their microstructure after mechanical testing.
  • Figure 68 represents the SEM images collected from the PET-GNP nanocomposites’ fracture surfaces. The fracture analysis of the samples prepared at 0.5 wt. %, 1 wt. %, and 2 wt. % concentrations of GNPs exhibited polymer chain entanglements, which was different from the behavior observed for the samples prepared at 0.004 wt. % and 0.1 wt. %.
  • FIG. 69 represents the internal structures of the nanocomposites prepared at 0.004 wt. %, 0.1 wt. %, 0.5 wt. %, 1 wt. %, and 2 wt. % concentrations of GNPs. While the GNPs in the 0.004 wt. % sample were not captured during the imaing, the unexfoliated GNPs increased with an increase in the concentration of GNPs.
  • FIG 71 shows micrographs of a TEM grid coated with PEG-600 dispersion that was sonicated for 180 minutes and centrifuged at 260 RCF.
  • the dispersed GNPs in PEG are comprised of short stacks of multi-layer graphene sheets.
  • the presence of multi-layer graphene sheets is confirmed by the SAED, shown in Fig. 71c.
  • the geometry of the platelets seem to be significantly different than those dispersed in EG.
  • the data here suggest that the higher viscosity of the dispersion medium can impact the exfoliation of the dispersed GNPs: the higher the viscosity of the dispersion medium, the higher the fraction of the fractured GNPs, which leads to a higher number of agglomerated GNPs.
  • Table 24 Sample preparation for filtration testing using PEG-300 as the dispersion medium.
  • Table 26 Comparison of GNP dispersions in EG and PEG-300 prepared at 0.25 mg/mL.
  • Table 27 Effects of initial concentration of GNPs on the concentration of PEG-300 dispersions, calculated from absorbance.
  • Table 28 Comparison of GNP dispersions in PEG-300 and PEG-600 prepared at 0.25 mg/mL, calculated from absorbance, using the absorbance coefficient found for PEG-300 for all calculations.
  • the PEG-600 dispersion medium results in higher values of the dispersed GNPs.
  • Table 29 Effects of initia concentration of GNPs on the concentration of PEG-600 dispersions.
  • Table 30 summarizes the size distribution including the values for D x l0, D x 50, D x 90, and the mean value.
  • Table 30 Particle size measurements for as-received GNPs and PEG-300 dispersions 1, 2, and 3.
  • Figure 73 and Table 31 represent the particle size measurements for the sample set II. A similar decreasing trend for the mean size of the as-received GNPs was observed for the dispersions-4, 5, and 6 with respect to sonication and centrifugation.
  • GNP dispersion in PEG-300 and PEG-600 were prepared and examined for stability. While the GNP dispersions in PEG-300, prepared at initial concentration of 5 mg/mL, did not change the stability of the dispersions, those prepared at initial concentration of 0.25 mg/mL showed a lower sedimentation rate compared to the dispersions in EG (Fig. 74). As shown in Table 32, the percent decrease in the concentration is smaller than EG dispersions, indicating a relatively better stability of the dispersion. Similar to the PEG-300 dispersions, GNP dispersion in PEG-600 were prepared and examined for stability.
  • the GNP dispersions in PEG-600 showed a significantly lower sedimentation rate compared to the dispersions in EG and PEG-300 (Fig. 75). As shown in Table 33, the percent decrease in the concentration is significantly smaller than EG and PEG-300 dispersions, indicating a better stability of the dispersion.
  • Table 32 Calculation of the percent decrease in the concentration of the PEG-300 dispersions.
  • Table 33 Calculation of the percent decrease in the concentration of the PEG-600 dispersions.
  • Fig. 76 The measurements of Elastic modulus and the tensile strength of PET and PET nanocomposites are shown in Fig. 76.
  • PET and PEG-dosed PET (labeled as PEG) were used as baselines to evaluate the effects of addition of GNP dispersions to PET.
  • the modulus of the nanocomposites increased with increase in the GNPs concentration.
  • a maximum of 10% increase in the modulus of PET and 5% increase in the tensile strength of PET were achieved by an addition of PEG-GNP dispersions at 0.13 wt. %.
  • PET and the PET nanocomposites were evaluated for their crystallinity and thermal properties with respect to the GNPs concentration.
  • Figure 78 represents the thermal behavior of the nanocomposites prepared by PEG-GNP dispersion and masterbatch approaches. While the nanocomposites using masterbatch pellets didn’t show a significant trend in the thermal properties, an increasing trend in the T c was observed for nanocomposites prepared by PEG-GNP dispersions. This indicates the presence of more crystals in the matrix due to early nucleation. The glass transition temperature, however, decreased by increasing the GNPs concentration, suggesting the presence of agglomerated GNPs inside the PET matrix.
  • Figure 79 represents the percent crystallinity of the PET, PEG, and PET nanocomposite samples. As shown, a similar increasing trend was observed for both types of nanocomposites. However, the PEG-GNP dispersions increased the crystallinity of PET to a much greater degree.
  • confocal microscopy images were collected from the nanocomposite samples with 1 pm thickness.
  • Figure 80 represents the images taken from the internal structure of the nanocomposites prepared by PEG- GNP dispersions at 0.001 wt. %, 0.01 wt. %, and 0.1 wt. % concentrations of GNPs.
  • the confocal images were binarized using binary filters to observe the GNP distribution. Not represented on this figure are the confocal images from the samples that were prepared by masterbatch pellets, as they were determined to be too soft to section at room temperature. Further investigation is required to section the samples in cryogenic conditions (cryoultramicrotomy).
  • the PET nanocomposites were analyzed for their color using the CIHLW scale color analysis method, shown in Fig. 30a. As can be seen, the nanocomposites prepared by the PEG- GNP dispersions showed values of luminosity higher than those prepared by masterbatch pellets. This indicates that the samples are lighter in color even with higher concentration of GNPs.
  • the PET-GNP nanocomposites fabricated through PEG-GNP dispersion dosing, outperform those that were prepared using masterbatch.
  • the nanocomposite tensile preforms were produced by dosing GNP dispersions, prepared by varied process parameters. Individual studies were conducted on effects of centrifugation, concentration of dispersions, and different sonication times and amplitudes, employed during the dispersion preparation, on the final properties of PET-GNP nanocomposites.
  • Figure 84 represents crystallinity measurements of the PET, PEG, and PET nanocomposites prepared in centrifugation study (Table 15). As shown, the addition of PEG-400 dispersions lead to a higher improvement in crystallinity of PET matrix compared to PEG-600 dispersions. It was found that the addition of PEG-400 and PEG-600 improved the crystallinity of the PET matrix by 72% and 32%, respectively. A maximum of 22% improvement in crystallinity was observed for the sample prepared through the addition of GNP dispersions in PEG-600 at 2350 RCF.
  • Figure 85 represents the luminosity measurements of PET, PEG, and PET nanocomposites prepared by PEG-GNP dispersions dosing method. While the addition of PEG did not affect the luminosity of PET samples, increasing the centrifugation speed of the PEG-GNP dispersions increased the luminosity, making them lighter in color. Based on the previous sections, it was found that increasing the centrifugation force from 260 RCF to 2350 RCF had a positive impact on mechanical and thermal properties of the PEG samples. Although the dispersions contained a significantly low concentration of GNPs, the data showed improvements in the tensile strength (Fig. 83) and crystallinity (Fig. 84) of the PEG samples.
  • Figure 88 represents luminosity measurements of PEG and the nanocomposites prepared by PEG-GNP dispersions dosing. As shown, increasing the GNP concentration to 0.02 wt. %, affects the luminosity of the samples, making them much darker compared to the control sample.
  • Table 34 Calculation of energy density for PEG dispersions prepared at 50% and 100% amplitudes.
  • Figure 89 represents the measurements of elastic modulus and tensile strength of samples prepared by pristine PEG (with zero sonication time) and PET nanocomposites prepared in sonication energy study (Table 17). The results shown in Fig. 89, reflect an inconclusive effect of sonication energy on the elastic modulus of samples. However, we see a 5% increase in the tensile strength of PET nanocomposites when the GNP dispersion, prepared at 180 minutes and 50% amplitude, was used. The energy densities of these data points are summarized in Table 34.
  • Figure 90 summarizes the crystallinity measurements of PEG and the PET nanocomposites prepared by PEG-GNP dispersions dosing. With an exception of 30 minutes sonication time, it was found that the crystallinity of the nanocomposites are lower than that of PEG samples.
  • Ultrasonic exfoliation is an effective method to exfoliate GNPs and to create few- to monolayer graphene in a dispersion medium. This conclusion is supported in two ways. First, it was observed, from TEM, that increasing the sonication time further exfoliates the as-received GNP and separates them from each other. This is reasonably attributed to exfoliation of the GNPs due to the released energy during sonication, and is independent of centrifugation. As shown in Fig. 55, TEM analysis confirmed the presence of large graphene sheets for the as-received GNPs and monolayer graphene after sonication for 90 and 180 minutes sonication and centrifugation at 260 and 2350 RCF.
  • the confidence is not high enough to draw a clear conclusion about the optimal time required to exfoliate the GNPs without fracturing them at 50% amplitude.
  • the data from Raman spectroscopy indicates that the number of GNP layers is decreasing with the sonication and centrifugation process parameters used to produce the dispersion samples.
  • the 2D bands presented herein are very similar to the spectra published by Ferrari et al. and Yoon et al. for graphene with 5 to 10 layers (Fig. 61). To rule out confounds from the regular TEM sample preparation process, Cryo-TEM was performed on a frozen dispersion to look at individual GNPs.
  • a dispersion of GNPs with a relatively higher concentration can be achieved at higher sonication times beyond 30 minutes at both 260 and 2350 RCF (Table 19 and Table 20). Even though the concentration of the dispersed GNPs significantly drops from 260 to 2350 RCF, increasing the G-Force better separates the thicker GNPs from thinner ones. The apparent plateau in concentration after 30 minutes of sonication may reflect a saturation level of GNPs in EG. It is important to note how other measurements indicate that an increase in sonication time decreases the average platelet size, indicating that longer-sonicated samples likely have a higher number of platelets per unit volume than the shorter-sonicated samples.
  • exfoliation energy values were then compared to 8x 10 11 eV/cm 2 , the energy with which graphene sheets are bound, and the difference was reported as excess energy.
  • Table 35 summarizes the comparison between the energy density, exfoliation energy, and the excess energy during sonication. As seen, this energy at each process condition is higher than what it is required to break a bilayer graphene sheet, supporting that exfoliation of GNPs occurred during the sonication process.
  • Table 35 Energy density, exfoliation density, and excess energy during sonication process.
  • Nawani el al. determined the orientation of a nanofiller in polymer nanocomposite films using an X-ray scattering method. According to them, for a system with some orientation the distribution of the nanofiller can be identified by a radial and an angular component, similar to what we have observed for the edge on view direction.
  • Figure 92 summarizes the orientations of the GNPs dispersed in PET in two directions. The GNPs exhibited preferred orientation in the edge on view direction, along the thickness of the tensile bar, and a random orientation distribution in the face on view direction, along the axial direction of the tensile bar.
  • the PET-GNP nanocomposites at 0.0015 wt. % concentration of GNPs increased the elastic modulus and the tensile strength of PET by 9% and 11%, respectively. More significant improvements were observed at 2 wt. % concentration of GNPs (experiment 8 in Table 11); the elastic modulus and the tensile strength improved by 22% and 10%, respectively.
  • experiments 3, 4, and 5, sonication for 60 minutes helped exfoliate a fraction of the GNPs. This led to a significant fraction of unexfoliated GNPs in the dispersions.
  • the resulting concentration of the exfoliated GNPs is a function of the starting concentration of unexfoliated GNPs. While the samples below 0.5 wt. % (experiments 3, 4, and 5) did not show a significant improvement in mechanical properties, at 0.5 wt. % (experiment 6) improvements in PET mechanical properties are apparent. As shown in Fig. 68, the nanocomposites from experiments 3 and 5 exhibit a fracture surface different from those prepared by experiments 6, 7, and 8 (> 0.5 wt. %). Based on the XRD analysis, shown in Fig. 70, the strongest graphene peak was observed at 0.5 wt. % concentration of GNPs and is expected to increase with weight fraction.
  • Figure 95 represents the TEM micrographs and binarized images collected from the precursors used for those experiment. While the precursor used for experiment 2 was mostly comprised of few- to monolayer graphene sheets (Figs. 95a-b), the one used for experiment 5, however, was comprised of a large fraction of unexfoliated multi-layer graphene sheets (Figs. 95c- d). Although the concentration of the GNPs in the sample prepared by the precursor from experiment 2 is the lowest amongst other samples, the data showed significant improvements in mechanical and thermal properties.
  • the glass transition temperature decreased with increasing GNP concentration. This could be due to agglomeration of GNPs inside the PET matrix. Agglomerated GNPs can act as plasticizer by getting in between the polymer chains, and spacing them out from each other. This causes the polymer chains to slide past each other more easily at lower temperature, T g , than they would without the plasticizer.
  • the glass transition temperature of a semi-crystalline polymer is considered to be higher and broader than that of the amorphous polymer.
  • the glass transition temperature of a polymer is influenced by its molecular weight (chain length). According to Flory et al.
  • the glass transition temperature can be related to the molecular weight using the Flory-Fox equation: where T g is the glass transition temperature, T g ⁇ is the maximum glass transition temperature that can be achieved at a theoretical infinite molecular weight, K is an empirical parameter that is related to the free volume present in the polymer sample, and M n is the molecular weight of polymer
  • Free volume refers to polymer chain’s ability to move and achieve different physical conformations, and it depends on the number of polymer chain ends.
  • a polymer with long chain lengths (high molecular weights) will have fewer chain ends and less free volume than a polymer with short chain lengths (low molecular weight). Fewer chain ends or free volume results in a higher T g.
  • the agglomerated GNPs can increase the free volume, therefore decrease the T g.
  • the T m shifted to higher values, suggesting the presence of crystalline zones in PET.
  • increasing GNP concentration increased percent crystallinity in the nanocomposites. Additional crystallinity also tends to improve mechanical properties. Further investigation is needed to understand the nucleation mechanism and properly attribute the effects of graphene and crystallinity on mechanical enhancement.
  • E m modulus of matrix
  • A/is aspect ratio of the filler (L/t length/thickness)
  • f volume fraction of the filler
  • E r is the ratio of the filler’s modulus to matrix’s modulus.
  • the Hui-Shia model is another micromechanical model that has been widely used to predict the modulus of the composites including unidirectional aligned disk-like platelets.
  • all moduli depend on a geometrical parameter, g, which depends on the inverse aspect ratio.
  • the longitudinal and transverse modulus of the composite materials can be estimated using the following equations: where Eu is longitudinal modulus of the composite, E22 is transverse modulus of the composite, E m is modulus of matrix, E j is the filler’s modulus, f is volume fraction of the filler, and a is the inverse aspect ratio (t/L).
  • the aspect ratio (L/t) of the GNPs is one of the important input parameters that should be used to evaluate the micromechanical models.
  • the polymer was brittle for sectioning.
  • the larger granules appeared resistant to sectioning and tended to fragment when striking the knife edge, resulting in shredded thin sections on a glass knife. Therefore, the thin sections were not successfully produced for TEM testing.
  • the PEG-dosed PET preform was used as baseline to isolate the effects of GNP dispersion on the properties of the nanocomposite from that of PEG alone.
  • the GNPs similarly improved the modulus of the nanocomposites by 3% (SD 0.1 ) even though the concentration of the incorporated GNPs in the tensile preform is significantly lower than the tensile bar.
  • the effectiveness of GNPs for tensile preforms was found to be 1000 ⁇ 600. This indicates that dispersion dosing leads to a better distribution of GNPs in the PET matrix.
  • Table 36 Summarizes the effectiveness of GNPs in PET nanocomposites prepared by different methods.
  • the main objective of this research was to achieve a uniform distribution of GNPs in PET nanocomposites via dispersion preparation followed by injection molding.
  • the following results were derived through the applications of melt compounding, in-situ polymerization, and injection molding over the course of this research:
  • the low surface area GNPs appears to provide a larger interface with more efficient interaction with the polymer matrix. This is because the GNP-15 contain larger graphene sheets per gram compared to GNP-150 and GNP-750, resulting in more free carbon edges and graphene surface area available to interact with PET chains.
  • Ultrasonic exfoliation is effective in dispersing GNPs in EG. Either probe or bath sonication methods are effective.
  • Probe sonication is more effective, likely due to the higher localized energy during cavitation, but it adds much more heat to the system compared to bath sonication. Overheating can severely damage the sonicator system and negatively impact the cavitation effectiveness during sample processing.
  • unexfoliated GNPs can be removed with centrifugation. If not, they do not negatively impact the nanocomposite, as measured by the tensile strength and elastic modulus, while visually decreasing the luminosity.
  • the PET-GNP nanocomposites fabricated through PEG-GNP dispersion dosing, outperform those that were prepared using masterbatch, exhibiting greater improvements in tensile strength of the PET. This is most likely due to exfoliation happening during the sonication that was used in preparation of dispersions. Exfoliation results in a higher fraction of few- to monolayer graphene sheets.
  • PEG shows promise to be used as dispersion medium for GNPs in creation of PET- GNP nanocomposites through the dispersion dosing approach due to its high viscosity and compatibility with PET chemistry. Improvements in crystallinity, modulus, and strength of PET observed in samples prepared by dosing PEG-400 dispersions.
  • Viscosity of the dispersion medium affects the stability and the achievable concentration of the dispersion, by reducing the sedimentation rate of dispersed GNPs.
  • GNP dispersions in PEG-400 at 0.006 wt. % improved the elastic modulus and tensile strength of PEG-dosed PET preforms by 8% and 4%, respectively.
  • a decreasing trend in the elastic modulus and tensile strength of PEG-dosed PET preforms was observed by an increase in concentration of GNPs. This is due to the agglomeration of the dispersed GNPs, caused by the higher viscosity of PEG relative to EG.
  • the luminosity of nanocomposites was a function of the concentration of GNPs, specifically the number of platelets per unit volume.
  • Centrifugation employed during dispersion processing, has positive impact on luminosity of PET nanocomposites. Centrifugation separates out the unexfoliated GNPs from exfoliated ones. Increasing the centrifugation speed leads to a lower fraction of more light- absorbing unexfoliated GNPs, resulting in an increased luminosity of PET nanocomposites.
  • PET-GNP nanocomposites prepared through in-situ polymerization were characterized by superior mechanical properties compared to those prepared through melt compounding.
  • bath sonication was utilized to prepare the GNP dispersions for the fabrication of nanocomposites. Effects of probe sonication on the quality of the dispersions and subsequent properties in the PET nanocomposites are still unknown. Therefore, future investigation is required to build upon and to optimize the existing results obtained through this method for commercial application.
  • centrifugation had a positive effect on the mechanical properties of the nanocomposites prepared through in-situ polymerization. As shown in this research, the yield of the exfoliated GNPs after centrifugation is very low.
  • the nanocomposite tensile preforms were characterized to by superior mechanical and thermal properties compared to pristine PET.
  • the PEG dispersions must be stable to be uses for the industrial scale production of PET bottles during injection molding and blow molding process. Therefore, further investigation is required to fabricate and investigate the PET bottles using the PEG dispersions.
  • TEM testing was successfully performed on the GNP dispersions to evaluate the size and thickness of the GNPs dispersed in EG.
  • TEM testing of the PET-GNP nanocomposites was not successful due to the challenges associated with sample preparation.
  • the data disclosed herein suggests that the PET-GNP nanocomposites, fabricated through PEG-GNP dispersion dosing, outperform those that were prepared using masterbatch, exhibiting greater improvements in stiffness and tensile strength of the PET.
  • the HR-TEM micrographs indicated a more uniform distribution of GNPs in PET for these nanocomposites, however, more statistical data is needed to further support this claim. Therefore, information related to the size and thickness of the exfoliated GNPs dispersed in PET remains unknown.
  • Raman spectroscopy is by far the most straightforward method to study the level of defects and identify the number of layers in graphene materials.
  • a typical Raman spectrum of graphene consists of three major bands including D band, G band, and 2D band near 1355 cm , 1570 cm 4 , and 2700 cm 4 , respectively.
  • the D band is a weak feature of the Raman spectrum. It is due to a one-phonon scattering from defects. It is either absent or extremely weak in a spectrum for monolayer graphene, but it becomes distinguishable when there is a significant amount of defects.
  • the G band is due to the degeneration of the optical phonon mode in graphene.
  • the intensity (I) of the G band is sensitive and increases with the number of layers up to 7 layers.
  • the shape of this band does not vary much.
  • Childres et al showed that the ratio of the intensity of the D band to the G band, ID/I G in Raman spectra, can be used to characterize the level of defects in graphene related materials. According to Khan et al.
  • the ID/I G of the as-received powder and the samples after the sonication and centrifugation could be approximately related to the lateral size of graphene by: where ID/IG is the ratio of the intensity of the Raman D and G bands, and k is estimated to be 0.17.
  • ID/IG is the ratio of the intensity of the Raman D and G bands
  • k is estimated to be 0.17.
  • the 2D band is a strong band that is due to a two-phonon scattering. This band is also referred to as G' .
  • the line shape of the 2D band reflects the electronic band structure and the number of layers of graphene.
  • Raman spectroscopy is a widely used characterization technique in the structural and electronic studies of graphene. To better understand the electronic structure of graphene, it is helpful to review the bond structure in graphene. As discussed earlier, three of the four atoms’ electrons are involved in sp 2 bonding, and they contribute very little to graphene’s electronic structure. The remaining atom in a state so-called p state plays an important role in the electronic structure of graphene. Band theory has been successfully used to explain physical properties of materials like electrical conductivity and optical absorption. According to solid-state physics, there will be an energy level in a solid where no electron can exist. This is called a band gap. In general, an electronic band structure of an insulator solid, shown in Fig. 98a, describes different levels of energies that an electron may have.
  • the energy bands are either full or empty.
  • the bands will look like parabolas (Fig. 98a).
  • graphene presents an uncommon behavior.
  • the cones will become circular, and the momentum will be connected through their extremities, showing a zero-gap structure.
  • the valence and conduction bands meet at Dirac point (Fig. 98b).
  • a total of six Dirac points, labeled as K, are divided into two non-equivalent sets.
  • the electronic behavior of graphene when electrons involved in the hexagon propagate through the lattice, they possess the same velocity as if they have no mass.
  • the electrons produce an energy that can be found using a conventional model and can be calculated using the below equation: where g is the nearest-neighbor hopping energy ⁇ 2.8 eV, a is the lattice constant ⁇ 2.46 A, and
  • E + and E represent the two energy bands for valence and conduction bands.
  • ionizing radiation When interacting with the specimen, electrons act as ionizing radiation.
  • ionizing radiation is capable of removing tightly-bounded inner-shell electrons by transferring energy to the atoms in the specimen.
  • the wavelength of an electron beam is significantly shorter than that of visible light, allowing visualization of the internal structure of a specimen. According to De Broglie’s law, the wavelength (l) of an electron beam is inversely proportional to the energy of the electrons (E) and can be calculated using the equation below:
  • SAED is an experimental technique used in TEM analysis.
  • a diffraction pattern is formed when an electron beam passes through a crystalline specimen in a TEM. It is one of the available crystallographic techniques to study the crystal structure of graphene. SAED not only can be used to identify crystal structures, but also to examine crystal defects. With the intention of distinguishing a monolayer with a multi-layer graphene, SAED were employed during the TEM testing in this study.
  • the diffraction pattern represents a reciprocal lattice plane, which contains the diffraction response of lattice planes belonging to one crystal zone, and reciprocal lattice points, which are shown as diffraction spots.
  • Figure 100 represents a diffraction pattern collected from a single crystal.
  • a laser beam passes through a dispersed particle in the sample and the angular variation in intensity of the scattered light is measured. While large particles scatter light at small angles, small particles scatter light at large angles. This is illustrated in Fig. 101. The angular scattering intensity is then analyzed to calculate the size of the particles using the Mie theory of light scattering.
  • One common approach to understand the particle size measurements is to report a distribution along with one or more values to describe the width of the size distribution. For the Mastersizer 3000, three different values on the x-axis are generally selected to define the volume- weighted distribution of the population. These values include D x l 0, D x 50, and D x 90 and are shown in Fig. 102. This means that 10 percent of the population lies below the D x l0 and 90 percent lies below the D x 90, while the D x 50 is the median, meaning that half of the population lies below this value.
  • the stability of the GNP dispersions is an important factor that can affect the usability of the dispersions in the development of nanocomposites.
  • the dispersed phase may agglomerate, leading to precipitation of the dispersion.
  • the dispersed-phase platelets stick to each other and form irregular clusters called aggregations. Once aggregation takes place, the aggregates will grow in size, and as a result, they settle out, which is referred to as sedimentation. Aggregation of the particles can be avoided when the repulsion forces between the particles dominate, leading to a stability of the dispersion.
  • Colloids are two-phase systems consisting of a dispersed phase, also called a discontinuous phase, and a dispersion medium, also called a continuous phase.
  • a system in which the dispersed phase is of the same size are called monodisperse system. If a range of sizes are present, the system is then called polydisperse.
  • colloid systems include mixtures in which the dispersed phase is insoluble, with random movement or Brownian motion, and is suspended in the dispersion medium.
  • a colloidal dispersion represents a state of higher free energy. Colloidal dispersions have a tendency to reduce their free energy by reducing the surface energy, altering the stability of the dispersion.
  • the intermolecular forces between two molecules can be found using the Lennard-Jones potential from the below equation: where V is the Lennard-Jones potential (J), e is a measure of how strongly two molecules attract each other (J), s is a constant parameter, a distance at which the intermolecular potential between two molecules is zero (nm), and r is the intermolecular distance between the two molecules (nm).
  • the Lennard-Jones potential describes the potential energy when two non-bonding molecules interact with each other based on their intermolecular distance.
  • the Lennard-Jones potential is comprised of two terms: a repulsive force, ( -J , and an attractive force, ( -) , and it provides a useful overview of the total intermolecular interactions.
  • a repulsive force ( -J )
  • an attractive force ( -)
  • Figure 104 shows the first case study in this work. Micrographs of TEM grid indicating the GNP-750, prepared by drop casting a few droplets of the samples that were sonicated from 30 to 120 minutes and centrifuged at 260 RCF.
  • GNPs typically consist of aggregates of sub-micron platelets with a diameter less than two microns, which are smaller than GNP- 15 and GNP-150. Due to the high amount of released acoustic energy during sonication, graphene sheets tend to be broken up, resulting in a decrease in the initial size of materials. As shown in Fig. 104, the platelets appear agglomerated, causing difficulties for sample processing. Therefore, further investigation on this grade of GNPs was discontinued.

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Abstract

La présente invention concerne une composition et un procédé pour la production de polyéthylène téréphtalate (PET) renforcé par du graphène. Des nanoplaquettes de graphène constituant une surface appropriée sont ajoutées à un milieu de dispersion pour produire du PET renforcé par du graphène. La surface moyenne peut varier entre sensiblement 15 m2/g et 750 m2/g. Selon certains modes de réalisation, le milieu de dispersion peut être constitué d'éthylène glycol. Le milieu de dispersion et les nanoplaquettes de graphène sont soumis à des ultrasons pour disperser les nanoplaquettes dans le milieu de dispersion. Le milieu de dispersion et les nanoplaquettes de graphène sont centrifugés pour éliminer des nanoplaquettes plus grosses qui ne sont pas dispersées de manière appropriée dans le milieu de dispersion. Une solution de surnageant de nanoplaquettes de graphène dispersées et de milieu de dispersion est décantée puis utilisée pour la polymérisation du PET renforcé par du graphène. Le PET renforcé par du graphène ainsi obtenu est constitué d'une matrice continue de PET avec un matériau de renforcement constitué de nanoplaquettes de graphène en phase dispersée.
EP19800351.9A 2018-05-09 2019-05-09 Nanocomposites de poly(téréphtalate d'éthylène)-graphène à dispersion améliorée Pending EP3790734A4 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113583401A (zh) * 2021-08-30 2021-11-02 宁波杰立化妆品包装用品有限公司 一种透明pet复合材料的制备方法

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KR20180040579A (ko) * 2015-07-08 2018-04-20 나이아가라 바틀링, 엘엘씨 그래핀 보강된 폴리에틸렌 테레프탈레이트

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113583401A (zh) * 2021-08-30 2021-11-02 宁波杰立化妆品包装用品有限公司 一种透明pet复合材料的制备方法

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