Impact of graphene concentration on crystallinity,rheological,and mechanical characteristics of a polypropylene copolymer

Abstract

This study examines the impact of graphene nanoplatelets (GNP) on the properties of a CP442XP polypropylene (PP) copolymer. GNP was added in concentrations of 0.5%, 1%, and 2% by mass, alongside a 2% flake graphite blend. An objective of this work is to prepare the material using industrial equipment. Therefore, PP/GNP composite production involved twin-screw extrusion for mixing and injection molding to produce samples. Characterization as crystallinity by Differential Scanning Calorimetry (DSC), mechanical and thermal properties, morphology and rheological properties are investigated. Results indicate that 0.5% and 1% GNP enhance PP crystallinity, due to GNP particles acting as nucleation sites. However, 2% GNP reduced crystallinity, possibly due to poor dispersion. Besides that, the PP copolymer usually starts with a better impact strength, compared to a PP homopolymer. Mechanical analysis showed that 1% GNP in PP improves elasticity but reduces impact strength at higher concentrations, indicating a stiffer polymer matrix. Rheological analysis revealed that 1% GNP in PP lowers viscosity at shear rates of 10 to 100 1/s, suggesting less energy required for polymer processing. In summary, low GNP concentrations beneficially modify the mechanical properties and rheology of PP copolymers. Some properties are possible to achieve even using standard industrial equipment.

Keywords

Crystallinity graphene mechanical properties nanocomposites thermal properties

Introduction

Various fields have centered their research on graphene. The myriad potential applications of graphene, particularly within polymer matrix nanocomposites, underscore its versatility in various fields. In the realm of nanocomposites, properties like heat conduction, mechanical resistance, and molten-state fluidity can experience positive enhancements with graphene as a reinforcing element.^1–5 Graphene, characterized by an elastic modulus of approximately 1100 GPa, exhibits excellent mechanical, thermal, and electrical properties. In nanoplatelet form, graphene nanoplatelets (GNPs) constitute a multilayered graphite nano crystal held together by Van der Waals forces.² Despite possessing multiple layers, GNPs exhibit favorable properties at a comparatively lower manufacturing cost than single-layer graphene.¹

As a key thermoplastic, polypropylene (PP) finds extensive use in sectors such as automotive, piping, and packaging. Nevertheless, the inherent limitations in its thermal and mechanical properties restrict its application as an engineering material.^2,4 The introduction of a minor quantity of graphene particles into polymer matrices, such as PP, generally augments their thermal and mechanical characteristics.⁴

Variations in proportions and structural forms of graphene introduce discernible impacts on the thermal,^1–3,5 mechanical,^2–6 and rheological⁴ aspects of resultant nanocomposites. The rheological properties in particular, as well as crystallinity, influence processes such as component injection. However, most of the achievements in those properties are only possible using graphene modifications techniques or advanced dispersion methods. Those methods are generally not viable in the industry for its cost and/or complexity. Sutar et al.² suspended and agitated PP and GNP in ethyl alcohol and dried them in a vacuum oven before mixing it in a twin-screw extruder. Authors achieved an increase of more than 100% in tensile strength, from 16 MPa to 33 MPa, but elongation decreased. Abuoudah et al.³ compared two mixing methods of PP with thermally reduced graphene (TRG). One method was melt-mixing PP and TRG using a twin screw, the extruded material was chopped and then extruded again to ensure dispersion. The second method was by solution blending, dissolving PP in decahydronaphthalene, and then adding TRG already dispersed via sonication. Composite solution was then coagulated and then dried. The authors found that both composites had increased mechanical properties, with the mixed composite having increase in tensile strength and young modulus of 8% and 27%, respectively. Ezenkwa et al.⁵ used Brabender twin-screw extruder to mix various PP nanocomposites. The higher mechanical performing material pointed by the authors was a sample with 2% GNP with increase in tensile strength and modulus by 8% and 90%, respectively. Dong et al.⁷ used a sonication technique to coat PP pettels, and achieved slightly higher mechanical strength, higher impact, and yield strength in most samples. Liu and Yu,⁸ used a torque rheometer with 7 min of blending time and then produced a PP/GNP composite powder that went to injection molding. The authors found that while tensile strength increased only by 3%, impact and elongation increased by 30% and 308%, respectively. In another work using a torque rheometer, Liu and Liang⁶ found that 0.5% graphene in an iPP matrix led to tensile strength and flexural modulus increase of 4.8% and 42.5%, respectively. Dundar and Okan⁹ used a surface modification technique on the used GNP to compatibilize it with PP. Flexural strength and flexural modulus had an increase of 26% and 38%, respectively, on the PP/MAOO-g-GNP-0.1 sample.

This study presents an examination of the mechanical, thermal, and rheological attributes of polypropylene (PP) and corresponding PP-based nanocomposites. The sample set encompasses pure PP copolymer, as well as PP composites featuring varying concentrations of graphene (0.5%, 1%, and 2%) and graphite flakes (2%). Key mechanical properties, including tensile strength, elongation, Young’s modulus, and impact resilience, were evaluated across all samples. Additionally, the tenacity modulus, synonymous with tensile toughness and indicative of the material’s ability to withstand deformation without breaking, was also measured. The thermal behavior of samples was characterized through the utilization of differential scanning calorimetry (DSC) to quantify the degree of crystallinity. Melt flow index and capillary rheology measurements were employed to assess the rheological properties of the materials. Finally, dynamic mechanical analysis (DMA) was applied to evaluate the viscoelastic behavior of the materials as a function of temperature. The results of this study provide valuable insights into the intricate structure-property relationships of PP-based materials. It underscores the potential benefits derived from the incorporation of graphene and graphite flakes as reinforcement fillers. Furthermore, results show the possibility to improve the mechanical and rheological properties of PP using only standard industrial equipment.

Materials and methods

Materials

The PP copolymer used in this investigation is CP442XP, produced by Braskem (São Paulo, Brazil). Since this copolymer has the presence of polyethylene in its structure chains, it was chosen to investigate how it would affect the final material. Nanopowder 0541 DX, consisting of graphene nanoplatelets with a thickness ranging from 6 to 8 nm and produced by SkySprings Nanomaterials (Houston, Texas, USA), was utilized as the graphene source. For comparative analysis, commercially available graphite flakes (CAS 7782-42-5, 332,461), with a molecular weight of 12.01 g/mol, were obtained from Sigma-Aldrich. The PP copolymer (PP) underwent processing with graphene loadings of 0.5% (PP-05NP), 1% (PP-1NP), and 2% (PP-2NP) by mass. To assess dispersion characteristics more effectively, a composite of PP with 2% graphite (PP-2GR) was also prepared. Table 1 shows samples investigated.

Table 1.

Samples formulations investigated.

Sample code	GNP weight (%)	Graphite weight (%)
PP	—	—
PP-05NP	0.5	—
PP-1NP	1	—
PP-2NP	2	—
PP-2GR	—	2

Methods

All materials where manually premixed in a recipient, then directly processed/mixed using a COR 20-32-LAB twin-screw industrial extruder. The extruder is constituted of screws featuring a 20 mm diameter and a Length/Diameter (L/D) ratio of 46. The temperature profile applied during the extrusion process consisted of the following set points: 100°C, 160°C, 170°C, 174°C, 180°C, 180°C, 185°C, and 190°C. The screw rotation speed was set to 200 rpm. The mixtures were then pelletized, in the form of pellets with a diameter of 3 mm and a length of 4 mm.

To produce ASTM test specimens intended for mechanical testing, the processed mixtures underwent injection molding using an LHS 150–80 injector. The injection process was made using a temperature profile of 170°C, 180°C, and 190°C at a pressure of 94 MPa.

Characterizations

The GNP underwent characterization through field emission gun scanning electron microscopy (FEG-SEM), Raman spectroscopy, and X-ray diffraction (XRD). Morphological analysis utilized the FEG-SEM technique, employing a Tescan Mira 3 microscope. This process necessitated the deposition of metallic gold ions onto the sample for a duration of 1 min at 15 kV.

Raman spectroscopy analysis utilized a Renishaw inVia Raman spectrometer with a 532 nm laser at 5% power, equipped with a 50× magnification lens. The X-ray diffraction (XRD) analysis was conducted on powdered GNP samples using a Shimadzu XRD-600 instrument. Parameters included CuKα = 0.1542 nm, 5° < 2θ < 40°, 0.05° step size, and 2 s⁻¹ scan rate. The number of layers in the GNP sample was estimated by applying the relation proposed by Pavoski et al.,¹⁰ dividing the crystal size (L) by the basal spacing (d), calculated through Bragg’s Law and Scherrer’s Law, respectively.

Tensile, flexural, and impact specimens were also produced. Tensile and flexural tests were conducted on an EMIC DL 2000 universal testing machine with a 200 kgf load cell and a maximum speed of 500 mm/min, following ASTM D638 and D790 standards, respectively. Izod impact tests with a notch were performed according to ASTM D256 using a CEAST 9050 equipment.

DSC was employed to assess crystallization variations. The Shimadzu DSC 60 apparatus was used with nitrogen at a flow rate of 50 mL/min and a heating rate of 10°C/min. The temperature range analyzed was 23°C to 250°C. Crystallinity was calculated using equation (1), where Xc is the percentage of the crystalline phase, ΔH is the enthalpy of the event, and ΔHo is the maximum enthalpy in a fully crystalline PP phase. The value of mpp corresponds to the mass ratio of PP to the total mass. The value of ΔHo used was 209 J/g.³

X_{c} (%) = \frac{∆ H}{{∆ H}_{o} . m p p} . 100

(1)

To determine the tenacity modulus of each sample, the area under the stress vs deformation curve was calculated using output data from the tensile testing machine. This method provides quantification of the material’s ability to withstand deformation and absorb energy before failure.

The Melt Flow Index (MFI) test was performed in accordance with ASTM D1238 standards. The test was carried out using a melt flow indexer at a temperature of 230°C and a load of 2.16 kg for a duration of 10 min.

Viscosity at various shear rates was measured through capillary rheology using a Ceast SR 20 equipment with a 20/1 mm capillary tube at a temperature of 190°C. Shear rates of 10, 30, 50, and 100 s⁻¹ were employed. The sample was loaded into the capillary and measurements were taken after the flow stabilized. The shear rate was then increased incrementally, and the viscosity was recorded.

DMA analysis was carried in the Q 800 from TA instruments, using dual cantilever bending mode. Specimen dimensions were 60 mm × 12 mm × 3.5 mm. The experiment was conducted at a frequency of 1 Hz under nitrogen atmosphere, with temperatures ranging from −40°C to 120°C at a heating rate of 5°C/min.

Results and discussion

Graphene nanoplatelets characterization

Figure 1 displays the FEG-SEM micrographs illustrating the morphology of the graphite (a) and GNP (b) samples utilized in this study. The commercial graphite sample (Figure 1(a)) is composed of micrometric particles, comprising several layers. In contrast, the GNP sample (Figure 1(b)) showcases small, dispersed, and exfoliated particles typical of graphene nanoplatelets, as well as the expansion of the lattice plane. Closer inspection reveals translucent and nearly transparent particles, indicative of few-layer graphene. These observations align with findings from other researchers.^11,12

Figure 2 presents the results of Raman spectroscopy (a) and X-ray diffraction (b). In Figure 2(a), the graphene nanoplatelet samples (GNP) exhibit the G band at approximately 1582 cm⁻¹, which corresponds to the in-plane vibration of sp² carbon atoms.¹³ Additionally, the 2D band at 2721 cm⁻¹, predictive of the number of graphene layers,¹⁴ is discernible. The D band, recognized as the disorder band and indicating the presence of defects or distortions in carbon rings, is evident between 1270 and 1450 cm⁻¹.^14,15 A representative Raman spectrum of graphite is included for comparison, showcasing the G and 2D bands with significantly higher intensity in comparison to the GNP sample.

The I_D/I_G ratio is a significant parameter in gauging the degree of disorder within the crystalline structure of a sample. It is established that the inverse proportionality between the intensity of peak D and peak G is indicative of the average distance between defects. In other words, a higher ratio implies a smaller distance between defects, signifying a greater presence of graphene polycrystals (or a higher concentration of defects in the form of a greater number of grain boundaries). For the examined GNP sample, the computed I_D/I_G ratio was 0.98. This result, coupled with the low intensity of the D band in the GNP sample, implies the absence of functional groups on the surface or minimal defects within the hexagonal lattice of carbon atoms.¹⁴

According to Nguyen et al.,¹⁶ the I_2D/I_G ratio is crucial in discerning the number of graphene layers in the analyzed sample. A ratio of 3 designates single-layer graphene, a ratio between 2 and 1 indicates bilayer graphene, and a value less than 1 signifies multilayer graphene. The GNP sample used in this study exhibited an I_2D/I_G ratio of 0.89, indicating the presence of multilayered graphene nanoplatelets. Clarifying this further, Malard et al.¹⁷ expound in their study that estimating the number of graphene layers can be achieved through the shape of the peak referring to the 2D band. However, this approach is applicable only for graphenes with up to 4 layers; beyond that, estimating the number of layers based on this observation becomes impractical.

During X-ray diffraction (XRD) analyses, the graphite sample revealed a pronounced and well-defined diffraction peak at 2θ = 26.5°, corresponding to the (002) plane of the graphitic domains (Figure 2(b)). A similar diffraction peak, albeit with lower intensity, was observed in the GNP sample.^18,19 Through calculations, the estimated number of graphene layers in the GNP sample was approximated to be around 35, corroborating the findings derived from Raman spectroscopy.

Mechanical properties

The mechanical properties obtained from the tests are summarized in Table 2. The incorporation of graphene did induce changes in tensile strength, possibly attributed to suboptimal adhesion to the matrix.^3,5,20–22 It is important to highlight that the reinforcement mechanism in nanocomposites is facilitated through polymer bridging, where nanoparticles restrict the movement of amorphous polymer chains. In the absence of interaction between particles and the deformation of polymer chains, there would be no observable effects on the mechanical properties.²³

Table 2.

Mechanical properties of the tested blends.

Sample	Tensile strength (MPa)	Elongation (%)	Young’s modulus (MPa)	Impact strength (kJ/m²)
PP	20.75 ± 0.16	197.7 ± 99.1	503.47 ± 11.97	56.68 ± 2.54
PP-05NP	19.74 ± 0.41	301.2 ± 56.2	509.98 ± 11.83	48.72 ± 3.49
PP-1NP	20.03 ± 0.59	299.9 ± 106.6	535.96 ± 17.12	41.72 ± 2.71
PP-2NP	20.53 ± 0.95	331.6 ± 174.8	513.47 ± 10.83	20.57 ± 2.24
PP-2GR	20.79 ± 0.44	100.5 ± 43.3	532.42 ± 13.69	43.80 ± 4.74

Conversely, elongation increases considerably compared to PP (197.7%), reaching values within the range of 300%. This suggests that graphene exerts a lubricating effect when well-dispersed in the polymer matrix⁵ possibly allied with a favorable interaction of GNPs with the PP matrix.⁸ In contrast, the graphite-modified PP (PP-2GR) exhibited reduced elongation (100.5%) compared to unmodified PP. Graphite is an agglomerate of nanoplatelets, which hampers its efficient dispersion in the polymer matrix, consequently diminishing the plasticizing effect.

Furthermore, Figure 3 shows the statistical significance among samples after applying Tukey’s test to the mechanical properties results in the form of a heat map. Significance is set at 0.05 and is highlighted in gray when observed. The statistical analysis reveals that the PP-05NP sample exhibited a significantly lower tensile strength compared to pure PP. If the primary objective of the material were tensile strength, all the samples demonstrated either equal or inferior performance compared to pure PP. A parallel analysis of Young’s modulus results indicates a significant increase in the PP-1NP sample compared to pure PP.

While there were variations in the mean values of the elongation parameter, no significant differences were observed in the graphene samples compared to pure PP, with notable distinctions occurring only when compared with the PP-2GR sample. The addition of graphite appeared to decrease elongation. Impact strength exhibited a significant decrease with the increase of graphene mass percentages in the sample. In contrast, the incorporation of graphite (PP-2GR) yielded impact results similar to the PP-1NP sample.

The introduction of graphene and graphite nanoplatelets yielded a marginal increase in the tensile elastic modulus of the composites, indicative of increase in rigidity.² The reduction in energy absorbed during impact can be attributed to restricted particle mobility and low adhesion between the matrix and the nanoparticles load.⁵ Since the PP copolymer already has a higher tier of impact strength, the presence of particles could act as rigid walls, decreasing energy dispersion within the structure, therefore decreasing impact strength.

Although tensile strength exhibited minimal variation, other properties were analyzed to fully characterize the behavior of the materials. The tenacity modulus, also known as tensile toughness, is a key property of polymeric materials. It describes the amount of energy required to fracture a sample.²⁰ In this study, the tensile toughness of polypropylene (PP) composites with varying graphene loadings was evaluated. To visually represent tensile toughness, the median stress–strain curve of each sample is plotted in Figure 4. Results show an increase in tensile toughness with an increase in graphene loading. Conversely, the incorporation of graphite diminished the material’s capacity to sustain deformation.

Tensile toughness was calculated using the area under the deformation curve for all tested samples and is illustrated in Figure 5. Given its consideration of the area, this metric can provide a more accurate estimate of deformation behavior compared to the unidimensional property of elongation.

The observed results spanned from 32 N*mm*mm⁻² for pure PP to 53.1 N*mm*mm⁻² for PP-2NP, denoting a substantial 66% increase relative to pure PP. Similarly, the tensile toughness of PP-05NP and PP-1NP registered values of 45.6 and 46.3 N*mm*mm⁻², respectively. Notably, there is considerable variation within the results. The nanocomposite composed of PP and 2% graphite flakes (PP-2GR) exhibited the lowest tensile toughness at 17.5 N*mm*mm⁻². This may be attributed to the comparatively lower mechanical properties of graphite in contrast to graphene. Another reason could be that graphite particles are acting as stress concentrators.

The substantial increase in tenacity modulus, coupled with the elongation data, signifies that the addition of graphene may augment the capacity of the copolymer to absorb energy during deformation. This observed behavior deviates from findings reported in prior studies.^3,5,24,25 Notably, Liu and Liang⁶ reported similar behavior when employing a three-layer graphene in conjunction with isotactic polypropylene. The authors posited that graphene nanosheets could function as stress transfer and reinforcement agents when the composites are subjected to external forces. Liu and Yu⁸ had similar results in elongation on another work. The remarkable elongation at break observed in the PP/graphene composites suggests effective stress transfer at the interfaces, attributed to the two-dimensional structure and favorable dispersibility of graphene in PP in their work. As external forces act on the composite, the macromolecular chains of the matrix and graphene nanosheets align along the force direction. With crack propagation direction, roughly perpendicular to this alignment, graphene nanosheets can effectively bridge crack ends, inhibiting their propagation.⁶

Thermal properties

The thermal behavior of the samples, as depicted in Figure 6, was assessed through differential scanning calorimetry (DSC). Results indicated that the melting temperature of all samples was comparable. During the first heating of the DSC analysis, the peak temperatures for PP-2GR, PP-2NP, PP-1NP, PP-05NP, and pure PP were 167°C, 165.8°C, 167.7°C, 167.5°C, and 167.1°C, respectively.

The consistent melting temperatures across all samples suggest that the addition of graphene at the studied concentrations exerts minimal influence on the thermal behavior of the PP matrix. However, the slight deviation in peak temperature observed for PP-2NP compared to pure PP could be attributed to the presence of graphene, albeit to a relatively minor extent. Possible agglomeration of graphene particles within the PP matrix may contribute to this observed deviation.^3,5

The crystallinity, determined from the enthalpy values obtained through DSC, is presented in Table 3 alongside enthalpy data. The enthalpy values from the first heating melting process are included, representing the state of the polymer after the injection process. These results are associated with the mechanical properties scrutinized in this study. The presence of graphene and graphite contributes to increased crystallinity as these particles act as nucleation sites for crystallization.³ For graphene concentrations of 0.5% and 1.0%, there was a discernible rise in crystallinity values. Conversely, graphene and graphite at concentrations of 2.0% led to a decrease in crystallization values.

Table 3.

Values of crystallinity obtained from the first heating and their enthalpy.

	Sample	PP	PP-05NP	PP-1NP	PP-2NP	PP-2GR
1st heat	ΔHf (J/g)	63.69	72.26	72.88	69.23	67.95
1st heat	Xc%	30.47	34.75	35.22	33.80	33.18

Rheological properties were assessed through melt flow index (MFI) and capillary rheology, with the behavior of each mixture illustrated in Figure 7. A slightly elevated melt flow index was observed for PP modified with 0.5% graphene compared to unmodified PP. The incorporation of 2% graphene and 2% graphite resulted in a reduction in the melt flow index. However, the Tukey HSD heat map indicates that only the decrease in PP-2NP is statistically significant.

A capillary rheology test, simulating conditions closer to an industrial injection process, revealed the viscosity of unmodified PP and PP modified with either graphene or graphite at different shear rates (Figure 8). In the shear rate range of 10 to 50 s⁻¹, a decrease in viscosity was observed for the 0.5% and 1% graphene concentrations. These rheological results suggest that small amounts of graphene either contribute to a better flow of the material in the molten state, or tend to not increase viscosity. Consequently, processes like injection may require less energy to move the material and fill mold cavities. The lubricating effect provided by graphene particles in the mixture is evident. In capillary rheology, particles tend to align in the direction of flow, facilitating the flow of molten mass. This is prominent in mixtures with lower load percentages, where particles are more dispersed, generating a lubricating effect for graphene nanoplatelet particles.⁴ Conversely, an increase in graphene nanoplatelets concentration (2%) resulted in behavior akin to that of graphite, likely forming agglomerates of graphene nanoplatelets. At higher shear rates, all samples behave the same.

Dynamic mechanical properties

Assessing the influence of graphene nanoplatelets in a polymer matrix can be achieved through DMA analysis. This data allows the correlation of mechanical response with nanofiller dispersion. At a specific filler loading, particle size, and surface area, good filler dispersion within the matrix is related to a higher amount of mobile chain segments and vice versa. This increased mobility of chain segments can elevate internal friction, consequently increasing the loss modulus and providing a higher peak value of tan δ at the glass transition temperature (T_g). Generally, if the interfacial interactions between the matrix and filler particles are strong enough, the peak value of tan δ is reduced and the Tg shifts toward higher temperatures.²⁶ With an increasing concentration of micro- or nanoparticles in a filled polymer, the tan δ peak value typically decreases due to heightened interfacial interactions.^27–30 Therefore, DMA results, either alone or in conjunction with other analytical techniques, can provide important information about the degree of filler dispersion (filler–filler and filler–polymer interactions) and the extent of interfacial interactions in the interphase region.

In the current study, a copolymer of polypropylene (PP) serverd as the matrix material for incorporating graphene nanoplatelets (GNPs) at different concentrations (0.5%, 1%, and 2%) and graphite flakes (2%). Storage modulus presented in Figure 9 shows very similar behavior between samples. Most notable differences are noticeable in the region of glassy state. In this region, samples with 1% and 2% GNP were able to make the polymer stiffer, due to increased adhesion between PP and nanofiller.³¹

The loss modulus presented in Figure 10 curve was chosen to better evaluate the mechanical properties of polymer composites containing nanoparticles in this case. This curve provides information on energy dissipation, identifies relaxation peaks, and is useful in assessing the level of nanoparticle dispersion within the polymer matrix, highlighting changes in mechanical behavior attributed to their presence.

Table 4 provides additional information into the loss modulus curves analyzed within this study. The table presents the peak values for each sample, allowing for a more detailed comparison across the different composites. This information complements the analysis derived from the DMA graph, providing a more comprehensive grasp of the mechanical properties of the nanoparticle-laden composites. By comparing the values of distinct peaks for each sample, it is possible to discern the effect of nanoparticles on the mechanical behavior of the composites and gauge the level of dispersion achieved for each nanoparticle concentration.

Table 4.

Transition peaks in the loss modulus analysis.

Sample	Peak temperature (°C)			Loss modulus E″ (MPa)
Sample	γ	β	α	γ	β	α
PP	−49.2	14.3	67.7	496.1	440.0	240.7
PP-05NP	−49.9	14.3	58.6	451.9	409.5	229.2
PP-1NP	−49.8	15.1	58.1	474.9	460.8	245.9
PP-2NP	−50.1	13.1	61.2	527.8	506.9	264.1
PP-2GF	−49.9	13.6	61.9	518.9	491.9	249.8

The loss modulus peaks obtained from dynamic mechanical analysis (DMA) indicates that the inclusion of GNPs led to a reduction in the peak intensity of the loss modulus, concomitant with a decrease in the alpha peak temperature across all samples. Conversely, the beta and gamma peaks exhibited minor variation in temperature. Notably, the PP composite with 0.5% GNPs displays a diminished intensity of the loss modulus peak, whereas samples with higher GNPs concentrations (1% and 2%) exhibited elevated loss modulus peaks. These results might be correlated with enhanced dispersion in the lower concentration sample (PP-05NP).^27–30 Furthermore, the loss modulus peaks of the PP-2NP sample surpass those of the PP-2GF sample. These findings suggest that the integration of GNPs into the PP matrix modulates the viscoelastic behavior of the material, with the copolymer structure exerting a noteworthy influence on the DMA peaks.

The loss modulus data presented in the table highlights distinctive characteristics between the PP-2GF and PP-2NP samples. Specifically, the PP-2GF sample exhibits a higher peak in the γ-region, indicating a higher level of stiffness or resistance to deformation. Additionally, the PP-2GF sample has a higher peak in the β-region, indicative of enhanced energy dissipation or damping capacity. On the other hand, the PP-2NP sample showcases a higher peak in the α-region, suggesting a higher level of molecular mobility or increased flexibility. This could be attributed to the larger surface area of the graphene nanoplatelets, which facilitates stronger interactions with the polymer matrix and consequently induce a more pronounced disruption of polymer chain mobility.

Overall, the comparison between the PP-2GF and PP-2NP samples suggests that the type of nanoparticle used as a reinforcement in the polymer matrix can have a significant impact on the mechanical and viscoelastic properties of the resulting composite material.

The peaks observed on DMA analysis of a polymer composite is related to the mechanical properties and the degree of filler dispersion.

Parameswaranpillai et al.³² investigated the influence of carbon nanofibers (CNF) on an ethylene propylene diene copolymer and loss modulus data showed increase with the CNF content. Authors attributed this behavior on increased friction on samples with higher filler content. Storage modulus was stable between samples. A study involving the incorporation of nanometer-sized zinc oxide (nano ZnO) into natural rubber,³³ where the highest E′ modulus in the rubbery region was observed for the sample containing 2 phr nano ZnO, indicating the homogeneous dispersion of nanoparticles in the matrix and strong interfacial interactions between them. However, at higher levels of nano ZnO phr, these effects diminished, suggesting poor dispersion of nanofiller particles in the composite. Another study showed DMA results indicating an increase in the Tg of a nanocomposite up to 0.09% addition of IL-modified graphene oxide (GO), followed by a decrease at 0.12%. This shift in Tg was attributed to improved interfacial interactions (when it increased) and to poor dispersion of the nanosheets in the composite (when it decreased).³⁴

Conclusions

In this study, the effects of graphene nanoplatelets (GNPs) and graphite flakes on the mechanical, thermal, and rheological properties of polypropylene (PP) composites were investigated. Initial characterization showed characteristics of the particles used. On the results, findings reveal some increase enhancement in elongation, tensile modulus, and tensile toughness upon the incorporation of GNPs, without compromising tensile strength. The improvement in mechanical properties can partially be attributed by the change in morphology, as well as GNPs and the PP matrix interactions. Enhanced plastic deformation and energy dissipation during deformation are attributed to GNPs capability to be stress transfers within the material. In contrast, the addition of graphite flakes resulted in reduced elongation while maintaining comparable tensile strength and modulus values. Furthermore, all nanocomposites had less impact strength compared to pure PP copolymer that has already a higher tier of impact energy absorption.

Thermal analysis via DSC showed that the melting temperatures of the composites closely resembled that of pure PP, indicating minimal impact on the thermal behavior of the PP matrix at the studied concentrations of graphene. The crystallinity of the composites increased with the presence of both graphene and graphite, suggesting the particles served as nucleation sites for crystallization. Rheological analysis revealed that low concentrations of GNPs improved flow behavior in the molten state, providing a lubricating effect.

In dynamic mechanical analysis (DMA), loss modulus peaks revealed that the incorporation of GNPs influenced the material’s viscoelasticity, with the copolymer structure exerting a significant influence on DMA peaks. The choice of nanoparticle reinforcement in the polymer matrix was found to significantly impact the mechanical and viscoelastic properties of the resultant composite material.

In conclusion, the incorporation of GNPs into a PP matrix emerges as a promising strategy for enhancing the mechanical, thermal, and rheological properties of the resulting composites. These insights can be useful for the development of advanced polymeric materials tailored for diverse applications in industries such as automotive, aerospace, and electronics. Results show that GNPs enhancements are achievable using regular industrial equipment for mixing and processing materials and parts. Further research endeavors may focus on optimizing the dispersion of GNPs within the matrix using industrial equipment.

Footnotes

Acknowledgments

The authors thank the CNPq (National Council for Scientific and Technological Development).

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Conselho Nacional de Desenvolvimento Científico e Tecnológico.

ORCID iDs

Charles Ost

Lídia K Lazzari

Data availability statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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