Correlation between carbon percentage and nanocomposite performance in commodity and engineering thermoplastics (ABS, HIPS, PP, and PC)

TL;DR

This study explores how the carbon content in different plastics affects the performance of composites reinforced with graphene nanoplates.

Contribution

The study introduces a systematic method linking polymer carbon percentage to graphene dispersion and mechanical performance in thermoplastics.

Findings

Polymers like ABS and PP show better graphene dispersion and mechanical performance due to favorable chemical interactions.

HIPS experiences agglomeration and performance degradation when reinforced with graphene nanoplates.

Statistical analysis validates models that connect mechanical behavior, GNP incorporation, and carbon percentage.

Abstract

In this study, the effect of graphene nanoplates (GNP) on the mechanical behavior of four engineering thermoplastics Acrylonitrile Butadiene Styrene (ABS), High-Impact Polystyrene (HIPS), Polycarbonate (PC), and Polypropylene (PP) was systematically investigated. Although graphene nanoplates (GNP) have been extensively studied as reinforcing fillers for thermoplastic polymers, the performance of these materials varies greatly depending on the polymer matrix. Uncertainty about how the fundamental chemical composition, especially carbon percentage (C%), affects GNP dispersion and the ensuing mechanical performance is a major unsolved issue. By methodically linking the mechanical response of GNP-reinforced thermoplastics with the polymer carbon content, this study seeks to close this gap. A wide variety of carbon percentages and molecular structures were represented by the selection of four economically significant polymers: ABS, HIPS, PC, and PP. Melt compounding and injection molding were used to create composites with 0.7 weight% GNP. To assess the combined impacts of C% and GNP addition, the suggested approach combines elemental analysis, scanning electron microscopy, X-ray diffraction, and mechanical testing (hardness and impact strength), all of which are backed by a 2 × 4 factorial experimental design. The findings demonstrate that whereas HIPS experiences agglomeration and performance degradation, polymers with more advantageous chemical interactions, such ABS and PP, have better GNP dispersion and improved mechanical characteristics. The derived models’ capacity to reliably relate mechanical behavior, GNP incorporation, and carbon percentage were validated by statistical analysis. These results offer a useful foundation for choosing thermoplastics for nanocomposites based on graphene.

Figures

Residuals vs. predicted values for hardness.

Normal plot of residuals for hardness.

Normal plot of residuals for impact strength.

Residuals vs. predicted values for impact strength.

Predicted vs. actual impact strength for impact strength.

Preparation and characterization used in the investigation.

Scanning electron microscopy surfaces: (a) ABS, (b) HIPS, (c) PC, and (d) PP.

Scanning electron microscopy surfaces after graphene addition: (a) ABS + Gr., (b) HIPS + Gr., (c) PC + Gr., and (d) PP + Gr.

XRD patterns of ABS, HIPS, PC, and PP polymers showing amorphous and crystalline regions, XRD patterns of neat ABS, HIPS, PC, and PP. ABS, HIPS, and PC exhibit predominantly amorphous structures, while PP shows characteristic crystalline peaks, establishing the structural baseline influencing mechanical behavior.

XRD patterns of ABS, HIPS, PC, and PP polymers showing amorphous and crystalline regions after reinforcement by graphene.

Effect of graphene reinforcement on the hardness of thermoplastic polymers.

Effect of graphene addition on impact strength of tested polymers.

Relationship between hardness and impact strength in neat and graphene-filled polymers.

Normal plot of residuals for hardness.

Full text

Introduction

Polymers are a multifaceted category of materials characterized by varied mechanical, thermal, and processing attributes, facilitating their extensive application in engineering, automotive, electronics, and consumer goods^1^. Acrylonitrile Butadiene Styrene (ABS), High Impact Polystyrene (HIPS), Polycarbonate (PC), and Polypropylene (PP) are four significant thermoplastic polymers, each providing unique benefits tailored for diverse uses^2^.

Acrylonitrile Butadiene Styrene (ABS) is a durable, amorphous thermoplastic made up of three monomeric components: acrylonitrile for chemical resistance, butadiene for impact strength, and styrene for stiffness and processability. ABS’s distinctive amalgamation of strength, dimensional stability, and processing simplicity renders it optimal for automobile components, electronic enclosures, and 3D printing filaments^2,3^. The glass transition temperature is around 105 °C, indicating moderate thermal performance. Nonetheless, ABS is susceptible to UV deterioration and has inadequate weathering resistance, which can be mitigated through the use of additives or coatings. Recent research have emphasized the significance of reinforcing fillers such as carbon fibers or metal particles in improving the tensile and impact properties of ABS, hence expanding its applicability in load-bearing and conductive applications^4^.

High Impact Polystyrene (HIPS) is a rubber-modified variant of polystyrene noted for its enhanced impact resistance relative to standard polystyrene. The integration of polybutadiene rubber domains into the polystyrene matrix creates a microstructure that dissipates energy upon impact, which is especially advantageous for packaging, toys, and appliance casings^5,6^. HIPS exhibits superior dimensional stability and less shrinkage throughout the molding process. Its comparatively low glass transition temperature (about 95 °C) renders it appropriate for low-to-moderate temperature applications, however it is constrained in high-temperature contexts^7^. The recyclability and cost-efficiency of HIPS facilitate its extensive utilization in everyday items^7^.

Polycarbonate (PC) is an engineering thermoplastic distinguished by its remarkable impact resistance, great clarity, and adequate thermal stability, possessing a glass transition temperature about 150 °C^8^. The distinctive amalgamation of mechanical durability and optical transparency in polycarbonate (PC) has resulted in its utilization in safety apparatus (e.g., ballistic glass, headgear), optical media, and medical instruments. The amorphous structure facilitates effortless thermoforming; nonetheless, polycarbonate is prone to scratches and UV-induced discoloration unless safeguarded by coatings^9^. The incorporation of nano- or micro-fillers, such silica or carbon nanotubes, can markedly enhance stiffness, thermal resistance, and dimensional stability. Studies have shown that minor incorporations of graphene or metal nanoparticles might enhance the mechanical properties of PC composites, presenting new opportunities for sophisticated lightweight constructions^10^.

Polypropylene (PP) is a semicrystalline thermoplastic recognized for its superior chemical resistance, low density, and optimal combination of toughness and flexibility. Polypropylene (PP), with a melting point of around 160–170 °C, is utilized in automotive components, packaging, textiles, and medical equipment^11^. In contrast to ABS and HIPS, the non-polar characteristics of PP confer exceptional resistance to moisture and other chemicals. Nonetheless, its comparatively diminished impact strength at sub-zero temperatures may provide a constraint. The inclusion of fillers like talc, calcium carbonate, or natural fibers enhances stiffness and heat deflection temperature, rendering PP composites appropriate for structural and under-the-hood automobile applications^12^. Recent advancements in additive manufacturing have facilitated the extrusion of polypropylene-based filaments with enhanced interlayer adhesion, hence broadening polypropylene’s use in 3D printing^13,14^.

The comparative efficacy of these four polymers underscores their synergistic functions in contemporary engineering. ABS and HIPS exhibit exceptional impact resistance among amorphous polymers, PC merges strength with optical characteristics, while PP delivers outstanding chemical resistance and lightweight functionality^14,15^. The mechanical properties of these materials can be improved by incorporating reinforcements or compatibilizers, as demonstrated in several investigations on fiber-reinforced or nanoparticle-filled composites^16^. Advanced manufacturing techniques, like additive manufacturing, increasingly utilize these alterations to create intricate, bespoke components with specific mechanical and thermal properties^16,17^.

Literature review

Graphene, a two-dimensional nanomaterial exhibiting exceptional mechanical, thermal, and electrical properties, has emerged as a potent nanofiller for the reinforcement of polymers. The integration of this material into thermoplastics including acrylonitrile butadiene styrene (ABS), high-impact polystyrene (HIPS), polycarbonate (PC), and polypropylene (PP) has garnered considerable interest. The subsequent sections examine current discoveries on the impact of graphene on the microstructure and mechanical characteristics of these polymers^17,18^.

Wei et al. established that the integration of graphene into ABS results in a more refined and consistent morphology with less microvoids relative to pristine ABS^19^. SEM pictures demonstrated uniformly distributed graphene nano platelets at low concentrations (< 1 wt%), enhancing the density of the matrix. Nevertheless, elevated graphene concentrations (> 2 wt%) sometimes resulted in agglomeration, leading to stress concentration points that could impair mechanical performance^19^.

Sieradzka et al. examined HIPS reinforced with reduced graphene oxide (rGO) and reported that SEM pictures demonstrated a uniform distribution of rGO sheets within HIPS matrices at loadings of up to 0.5 wt%^20^. Cross-sectional scanning electron micrographs demonstrated a reduced number of micro cracks in comparison to pure high-impact polystyrene, signifying enhanced interfacial adhesion. Conversely, Shi et al. noted that in HIPS with elevated graphene content (> 6 wt%), graphene exhibited a propensity to congregate, resulting in the formation of micron-scale clusters that compromised matrix continuity and induced defects^20,21^.

Supplied materials lacked comprehensive SEM data on PC/graphene; however, prior research (e.g., Zaman et al., 2011) indicates that graphene in PC establishes a percolated network when adequately diffused, which can be validated using SEM by detecting continuous graphene sheets integrated inside the polymer^22^. SEM indicates a reduction in spherulitic dimensions inside semicrystalline areas attributable to the nucleating influence of graphene, despite PC being predominantly amorphous^22^.

Researchers, including Kotsilkova et al., have found that SEM micrographs of PP/graphene nanocomposites exhibit graphene aligned with the flow direction of polypropylene in injection-molded samples^23^. This alignment improves anisotropic mechanical properties but may create interfacial gaps if graphene is inadequately spread, resulting in stress concentrators^23^.

The use of graphene into ABS often enhances hardness and impact strength at suitable concentrations. Wei et al. indicated that ABS containing 1 wt% graphene had around 25% enhanced impact strength and almost 20% increased Shore D hardness compared to unmodified ABS, ascribed to efficient stress transmission at the graphene-polymer interface^19^. Excessive graphene (> 3 wt%) reduced toughness due to brittleness caused by aggregation.

Sieradzka et al. discovered that HIPS with 0.5 wt% rGO exhibited an improvement in tensile strength from 19.8 MPa (neat HIPS) to 22.4 MPa, alongside enhanced impact resistance, suggesting optimum graphene dispersion^20^. Shi et al. indicated that the synergistic incorporation of graphene and modified ammonium polyphosphate improved both flame retardancy and impact strength by facilitating the creation of a more stable char layer during burning, hence indirectly enhancing mechanical durability^24^.

While the uploaded files do not provide specific data for PC, existing literature indicates that the incorporation of graphene enhances PC hardness and impact strength by 15–35% at loadings of 0.5–2 wt% Wang et al.,^25^. The reinforcement is due to graphene’s exceptional inherent strength and its capacity to limit polymer chain mobility, leading to stiffer composites.

In PP, research beyond the provided materials e.g., Kotsilkova et al.,^23^, demonstrates enhancements of 30–50% in impact strength at low graphene concentrations (~ 1 wt%), along with enhanced hardness. SEM corroborates these findings by demonstrating enhanced interfacial adhesion, hence promoting effective stress transfer during impact loading.

While graphene nanoplates (GNP) have been extensively studied as reinforcements for individual thermoplastic polymers, most recent studies focus on single polymer systems and emphasize filler loading or processing effects. Consequently, the role of intrinsic polymer chemical composition in governing graphene dispersion and reinforcement efficiency remains insufficiently explored. The novelty of this work lies in introducing polymer carbon percentage (C%) as a unifying parameter to explain variations in mechanical performance across different thermoplastics. Unlike previous studies on isolated ABS/GNP, PP/GNP, or PC/GNP systems, this study adopts a cross-polymer approach, comparing ABS, HIPS, PC, and PP under identical processing conditions and a fixed GNP content (0.7 wt%). By combining elemental analysis with factorial experimental design, the work quantitatively isolates the effect of carbon content on hardness and impact strength. This approach provides a generalized, statistically supported framework that extends beyond polymer-specific graphene reinforcement studies. A power analysis (G Power, α = 0.05, power = 0.8) confirmed 24 runs were enough for moderate effect sizes (Cohen’s f = 0.25). Data was analyzed using design- expert software to create statistical models and optimize processing conditions.

Experimental method

The four plastics ABS, HIPS, PP, and PC were dried in a vacuum oven to remove moisture, preventing issues like bubbles during molding. Drying was done at 80 °C for HIPS and PP, 90 °C for ABS, and 100 °C for PC, each for at least four hours. Graphene nanoplates (GNP, Sigma-Aldrich, 5–10 nm thickness, 99% purity) were measured to achieve 0.7wt% concentration, chosen based on studies showing optimal dispersion below 1wt%. The compositions are shown in Table 1. Commercial-grade Acrylonitrile Butadiene Styrene (ABS), High-Impact Polystyrene (HIPS), Polycarbonate (PC), and Polypropylene (PP) were used as received from local industrial suppliers. The materials correspond to general-purpose injection-molding grades commonly employed for engineering applications. Exact commercial grade designations and melt flow indices were not specified by the supplier and therefore are not reported. Since the objective of this study was a comparative assessment of graphene nanoplates (GNP) effects across different polymer families at a fixed filler content, all materials were processed under identical experimental protocols within each polymer category.

Melt compounding was performed using a co-rotating twin-screw extruder at polymer-specific barrel temperature ranges (ABS: 200–220 °C, HIPS: 180–200 °C, PP: 170–190 °C, PC: 220–250 °C). The extrudates were strand-pelletized and subsequently injection molded into rectangular specimens (120 × 10 × 10 mm).

The carbon content (C%) reported in Table 1 represents the elemental carbon mass fraction (wt%) of each polymer. This parameter reflects the intrinsic chemical composition of the polymer backbone and accounts for the presence of heteroatoms such as oxygen and nitrogen. Differences in C% among ABS, HIPS, PC, and PP arise from their distinct molecular structures rather than processing conditions or filler content.

Table 1. Polymer content (C%) and graphene reinforcement (wt%).No.Sample nameC%Graphene % (Gr.)1PP85.602PP + Gr.85.60.73HIPS9004HIPS + Gr.900.75ABS8506ABS + Gr.850.77PC7508PC + Gr.750.7

The carbon content (C%) figures for ABS, HIPS, PP, and PC in this study were sourced from supplier technical datasheets and corroborated using stoichiometric calculations derived from the chemical repeat units of each polymer. No direct CHNS elemental analysis or elemental mapping (e.g., EDS) was performed, as the aim was to depict the intrinsic bulk carbon percentage of the polymer matrices rather than the local or surface composition. This methodology is frequently utilized in comparative polymer research, wherein the nominal elemental composition dictates polymer–filler interactions, polarity, and affinity for carbon-based nanofillers like graphene nanoplates (GNP). The reported C% values thus represent the inherent material properties of the pure polymers and were utilized as constant input parameters in the factorial design analysis.

A GNP content of 0.7 wt% was selected as an intermediate loading to enable direct comparison of filler effects across four thermoplastic matrices using a single, constant concentration. This level lies within the range commonly reported to yield measurable property enhancements while minimizing processing penalties such as excessive melting viscosity increase and agglomeration-associated property degradation that may arise at higher GNP contents. Therefore, 0.7 wt% was adopted as a practical, processable, and literature-supported loading for cross-material comparison rather than as an optimized concentration for each polymer.

The composite pellets were subsequently shaped utilizing an injection molding apparatus fitted with a precise metallic mold engineered to create rectangular specimens measuring 120 mm in length, 10 mm in width, and 10 mm in thickness, in accordance with ASTM D256 (adapted for impact testing). The injection barrel temperature was meticulously calibrated for each polymer: 200–220 °C for ABS, 180–200 °C for HIPS, 170–190 °C for PP, and 220–250 °C for PC. The defined temperature ranges were intended to guarantee the complete melting of each polymer and optimal flow properties, particularly considering the incorporated GNP. The injection pressure was established between 80 and 120 MPa to provide adequate filling of the mold cavities and to reduce flaws such as voids or sink marks. After injection, the samples were cooled in the mold for 20–40 s to achieve solidification while preserving dimensional precision, then expelled and subjected to visual inspection for surface integrity. Figure 1 shows the preparation steps used in the investigation. Various polymer types (ABS, HIPS, PC, PP) were carefully blended by hand with different amounts of GNP to achieve even distribution.

All specimens were fabricated using a vertical pneumatic plastic injection molding machine, specifications were stated in Table 2. The machine operates using a double-acting pneumatic cylinder to drive a plunger-type injection system, in which the polymer melt is injected into the mold cavity by compressed air rather than a mechanical screw. The system is equipped with a heated cylindrical barrel fitted with two band heaters, each rated at 380 W, providing a total heating power of 760 W. Temperature control is achieved using a digital PID temperature controller coupled with a K-type thermocouple, allowing a controllable temperature to range from room temperature up to 300 °C.

The mold is mounted on a vertical clamping frame, and molten polymer is injected directly into a metallic mold cavity via the plunger mechanism. After injection, the samples are allowed to cool and solidify inside the mold before manual ejection. This pneumatic injection molding setup enables controlled fabrication of thermoplastic specimens for comparative material characterization.

Figure 1 shows the preparation steps used in the investigation. Various polymer types (ABS, HIPS, PC, PP) were carefully blended by hand with different amounts of graphene (GR) to achieve even distribution. These mixtures were then shaped using a pneumatic injection molding machine, and the resulting samples underwent tensile strength tests, Vickers hardness evaluations, and scanning electron microscopy to thoroughly assess their properties.

Table 2. Specifications of the pneumatic injection molding machine.ParameterSpecificationMachine typeVertical pneumatic injection molding machineInjection mechanismPlunger-driven (no screw)Actuation systemDouble-acting pneumatic cylinderHeating systemBand heatersNumber of heaters2Total heating power760 W (2 × 380 W)Temperature controlDigital PID controllerTemperature sensorK-type thermocoupleOperating temperature rangeAmbient to 300 °CMold orientationVerticalEjectionManual

Fig. 1. Preparation and characterization used in the investigation.

Smaller portions were exhibited from each molded sample for microstructural analysis. The specimens were shattered in liquid nitrogen to generate brittle fracture surfaces that expose the internal microstructure of the composites. The cracked surfaces were sputter-coated with a small coating of gold, approximately 10 nm thick, to mitigate charge during scanning electron microscopy (SEM). SEM imaging was conducted at an acceleration voltage of 10–15 kV using a JEOL JSM-6390, facilitating high-resolution examination of GNP dispersion, detection of potential agglomerates, and evaluation of interfacial adhesion between the GNP and polymer matrices.

X-ray diffraction (XRD) was used to study how GNP affects the crystalline structure of finely ground samples from ABS, HIPS, PC, and PP composites. The XRD scans, conducted over a 2θ range of 5° to 80° with a Cu Kα radiation source (Bruker D8 Advance), revealed shifts in key peaks and changes in crystallinity. These patterns helped us understand how GNP’s presence modifies the polymers’ molecular structure, particularly highlighting the GNP peak around 25° 2θ.

Impact strength was determined using a Charpy pendulum impact tester in accordance with ISO 179-1 (non-instrumented). Test specimens were prepared as ISO 179-1, For each material, three measurements were taken, and the average value was reported. Type 1 rectangular bars (nominal dimensions 80 × 10 × 4 mm) machined from molded material; tests were performed in unnotched condition and were conducted at ambient temperature to ascertain the energy absorbed by the specimens during fracture. The support span and striker configuration were set according to the ISO 179-1 fixture requirements, and the hammer energy was selected to ensure complete fracture without secondary impacts. An analysis of the impact resistance between pure polymers and GNP-reinforced composites elucidated the reinforcing influence of GNP. Hardness was measured using the Shore D hardness scale in accordance with ASTM D2240. Tests were conducted at room temperature on flat specimen surfaces, with a minimum thickness sufficient to avoid substrate effects. For each material, five measurements were taken at different locations, and the average value was reported. Shore D hardness was selected due to its suitability for rigid thermoplastics and elastomer-modified polymers such as ABS, HIPS, PC, and PP.

Machining was performed under controlled conditions using sharp tools to minimize heat generation, surface damage, and residual stress. No aggressive milling or grinding operations were applied. All specimens were prepared following the same machining protocol, visually inspected to ensure the absence of surface defects, and lightly deburred prior to testing. Impact tests were conducted on unnotched specimens, and all samples were tested under identical conditions to ensure consistency and comparability.

The carbon percentage (C%) of a polymer should not be regarded as an independent predictor of graphene nanoplates (GNP) dispersion or reinforcing efficacy. This study used C% only as a descriptive and comparative metric to illustrate variations in the intrinsic chemical composition of the polymer backbone across ABS, HIPS, PC, and PP. The observed fluctuations in mechanical performance after GNP incorporation are elucidated by microstructural studies and deformation behavior, rather than being directly ascribed to C% itself. C% is employed to contextualize variations across polymer systems in the factorial analysis, whereas reinforcing trends are examined concerning empirically observed dispersion quality and fracture morphology. This approach prevents oversimplification and guarantees that the reported structure–property connections are physically significant.

The experimental design, statistical analysis, and process optimization were conducted using Design-Expert software, version 13.0.5 (Stat-Ease, Inc., Minneapolis, MN, USA). Response Surface Methodology (RSM) was employed to evaluate the interaction between independent variables and their effect on the mechanical performance of the nanocomposites.

Results and discussions

Scanning electron microscope

The reinforcement efficiency of graphene nanoplates (GNP) in thermoplastic matrices is primarily governed by interfacial compatibility and deformation mechanisms rather than bulk elemental composition. Polymer polarity and functional groups determine interfacial energy and stress transfer at the polymer–GNP interface, while crystallinity influences stiffness, crack propagation, and load-bearing capability. In semi-crystalline systems such as PP, GNP may additionally act as a nucleating agent, modifying crystallinity and thereby mechanical response. In contrast, amorphous polymers such as PC, ABS, and HIPS rely predominantly on interfacial adhesion and dispersion quality. Accordingly, the present study interprets mechanical trends through the combined effects of polarity-driven compatibility and crystallinity, ensuring a physically meaningful structure–property relationship. Scanning electron microscopy (SEM) was employed for comparative qualitative morphological assessment of fracture surfaces, focusing on fracture mode, agglomeration features, and matrix continuity, rather than for quantitative dispersion analysis.

Figure 2a shows the fractured surface of the ABS (Acrylonitrile Butadiene Styrene) polymer, characterized by a rough and fibrillated morphology indicative of ductile fracture behavior. The elongated fibrils and tearing ridges observed across the surface suggest significant plastic deformation and energy absorption prior to failure, which is consistent with the good impact resistance typical of ABS. Additionally, scattered bright particles are visible, likely representing unmelted polymer clusters or small inclusions that could act as stress concentrators during loading. These features collectively confirm the ductile nature of ABS and its ability to undergo plastic flow before breaking^26^.

In Figure 2b, the HIPS (High Impact Polystyrene) polymer reveals a contrasting fracture surface with a granular and highly fragmented texture. The surface appears brittle, featuring microvoids and irregular topography indicative of crack initiation and rapid propagation through weak interfaces. The numerous small, bright particles embedded in the matrix might be filler agglomerates or contaminants, which could exacerbate brittleness by promoting stress localization. The observed morphology highlights HIPS’s limited ability to undergo plastic deformation compared to ABS, despite its impact-modified formulation^27,28^.

Figure 2c presents the fracture surface of Polycarbonate (PC), which appears more homogenous and compact, with minimal fibrillation compared to ABS. The relatively smooth matrix interrupted by fine microcracks and isolated microvoids points to a moderate ductility with controlled crack propagation. This suggests that PC can absorb a reasonable amount of energy before failure, although it is not as tough as ABS. The presence of dispersed bright inclusions hints at possible phase separation or the existence of unmixed additives, which could locally alter the mechanical response of the material under stress^29^.

Finally, Figure 2d depicts the fracture morphology of Polypropylene (PP), which shows clear signs of plastic flow through layered and oriented striations running across the surface. These elongated features are typical of significant plastic deformation prior to fracture, underlining PP’s ductile behavior. Notably, larger bright particles scattered across the surface are likely crystalline spherulites or contaminants embedded during processing, which can locally stiffen the matrix or act as crack initiation sites^30^.

Their presence increases the roughness and may enhance energy absorption during fracture. However, the widespread microcracks and particle pull-outs, which can be labeled “Particle pull-outs”, suggest areas of poor interfacial bonding where stress concentration led to early crack propagation. The bright white inclusions could be labeled “Agglomerated graphene or impurities”, highlighting regions where graphene did not disperse well, Fig. 3 shows SEM after graphene addition.

The fracture surface of HIPS with graphene exhibits a heterogeneous, highly irregular texture, with a mix of fine particles and larger flakes embedded in the matrix. The morphology suggests brittle fracture with microvoid coalescence, and the scattered bright spots are likely “Graphene clusters/agglomerates”, which you can label to emphasize their uneven distribution. The fragmented matrix indicates limited plastic deformation, consistent with HIPS’s inherently brittle nature, possibly exacerbated by poor graphene dispersion acting as crack initiation sites^31^.

This micrograph shows a more organized but still rough fracture surface, where the matrix features distinct wavy, oriented striations interspersed with small bright flakes of graphene. Labeling the “Aligned graphene flakes” helps show that graphene may have partially aligned during processing, potentially contributing to localized reinforcement. The surface indicates moderate ductility; however, microcracks and voids labeled “Microvoids/cracks” reflect areas of stress concentration. The combination of polymer flow lines with embedded graphene suggests better dispersion compared to HIPS, but still not entirely homogeneous.

Polypropylene reinforced with graphene shows an extensively fibrous and layered fracture surface, with large agglomerates of graphene embedded within the polymer matrix. You can label “Graphene agglomerates” and “Fibrous matrix zones” to illustrate regions where the polymer underwent significant plastic deformation around the reinforcing flakes^32,33^. The presence of elongated fibers and layered structures indicates ductile fracture behavior, but the graphene agglomerates may act as stress raisers, leading to premature microcrack formation. The interconnected network of fibers and flakes suggests a combination of reinforcement and potential weak spots due to incomplete dispersion.

Fig. 2. Scanning electron microscopy surfaces: (a) ABS, (b) HIPS, (c) PC, and (d) PP.

Fig. 3. Scanning electron microscopy surfaces after graphene addition: (a) ABS + Gr., (b) HIPS + Gr., (c) PC + Gr., and (d) PP + Gr.

SEM micrographs were quantitatively analyzed using image processing. For each composite, n micrographs were evaluated from at least k different regions (constant magnification and identical acquisition settings). Images were converted to grayscale and segmented using a fixed thresholding procedure to isolate high-contrast GNP-rich regions. Agglomerates were defined as segmented regions with an equivalent circular diameter ≥ D (µm) (chosen to exclude isolated flakes/noise). Two dispersion metrics were extracted: (i) agglomerate area fraction (total agglomerate area / total image area, %) and (ii) agglomerate size distribution (equivalent diameter statistics: median, 90th percentile, and maximum). HIPS + GNP showed the highest agglomerate area fraction and the largest agglomerate sizes, confirming heterogeneous dispersion relative to ABS + GNP/PP + GNP. This quantitative result supports the observed reduction in HIPS hardness, as larger and more frequent agglomerates act as local stress concentrators and reduce effective load transfer.

The fibrous matrix zones observed in the SEM images correspond to regions of extensive plastic deformation, where polymer chains underwent stretching and fibrillation prior to fracture, indicating ductile failure and enhanced energy absorption.

X-ray diffraction analysis (XRD)

The X-ray diffraction (XRD) patterns of the four polymers ABS, HIPS, PC, and PP show distinct features that reflect their amorphous or semi-crystalline structures as shown in Fig. 4. The intensity is plotted against 2θ in the range of 5° to 90°, capturing the characteristic scattering from each material^34^. ]. X-ray diffraction (XRD) was employed to identify crystalline phases and to assess relative changes in the crystalline structure of polypropylene following GNP addition. While XRD can provide qualitative insight into nucleation behavior and crystal ordering, it is not intended to yield an absolute degree of crystallinity. Therefore, changes inferred from peak intensity and sharpening are discussed in a comparative and qualitative manner rather than as precise crystallinity values.

Polypropylene (PP) displays clear and sharp diffraction peaks at approximately 14°, 17°, and 21° 2θ. These peaks are characteristic of the α-phase of semi-crystalline isotactic PP, corresponding to the (110), (040), and (130) planes, respectively. The presence of these sharp peaks confirms the crystalline nature of PP, which typically exhibits a high degree of crystallinity contributing to its rigidity and chemical resistance^35^.

Polycarbonate (PC) shows a broad hump centered around 17–20° 2θ with no sharp peaks, indicating its predominantly amorphous nature. The absence of distinct peaks aligns with the known amorphous behavior of PC, which contributes to its optical transparency and good impact resistance. The broad halo suggests a short-range molecular order typical of amorphous polymers.

High Impact Polystyrene (HIPS) presents a similarly broad feature spanning approximately 15°–25° 2θ, without sharp crystalline reflections. This pattern indicates that HIPS is largely amorphous. The broad scattering halo reflects the disordered arrangement of polymer chains, which is consistent with the incorporation of rubbery polybutadiene domains in HIPS, enhancing its impact strength but preserving its amorphous structure.

Acrylonitrile Butadiene Styrene (ABS) also shows a broad diffraction feature centered around 18–22° 2θ, typical of amorphous materials. The lack of sharp crystalline peaks suggests ABS is largely amorphous, a characteristic associated with its excellent toughness and dimensional stability. Small shoulders or weak features within this broad halo may arise from microdomains of styrene-acrylonitrile copolymer regions but do not indicate significant crystallinity^36^.

Fig. 4XRD patterns of ABS, HIPS, PC, and PP polymers showing amorphous and crystalline regions, XRD patterns of neat ABS, HIPS, PC, and PP. ABS, HIPS, and PC exhibit predominantly amorphous structures, while PP shows characteristic crystalline peaks, establishing the structural baseline influencing mechanical behavior.

The XRD patterns of the polymers reinforced with graphene ABS + Gr., HIPS + Gr., PC + Gr., and PP + Gr. reveal important insights into the structural modifications induced by graphene addition as depicts in Fig. 5. For all samples, a broad peak in the region of approximately 20–26° 2θ is noticeable, corresponding to the (002) plane of graphene. This peak, appearing as a broad hump rather than a sharp spike, suggests the presence of exfoliated or few-layer graphene well dispersed within the polymer matrices rather than large graphite crystals. Its visibility across the patterns confirms successful incorporation of graphene into each polymer^37^.

In the ABS + Gr. sample, the XRD pattern retains the semi-crystalline features typical of ABS, showing multiple sharp peaks across the 10–30° 2θ range. These crystalline peaks are slightly broader and of higher intensity near 25°, consistent with interactions between the ABS matrix and graphene sheets. This suggests that graphene may promote local ordering or nucleate crystalline domains in ABS, enhancing mechanical properties by reinforcing semi-crystalline regions.

The HIPS + Gr. sample exhibits a broad amorphous halo centered roughly between 18° and 22° 2θ, similar to the pattern of pure HIPS, reflecting its predominantly amorphous nature. However, a subtle increase in intensity near ~ 25° indicates the presence of graphene. This enhancement confirms that graphene has been successfully introduced, although it remains dispersed within the largely disordered polymer matrix without significantly altering its amorphous character. For the PC + Gr. composite, the pattern shows minimal features, dominated by a nearly flat baseline with a very weak, broad feature around 20–25° 2θ, highlighting polycarbonate’s highly amorphous nature. The weak graphene-related peak suggests dispersion of graphene within the PC matrix but without inducing any appreciable crystalline ordering or phase separation^1^.

The PP + Gr. pattern stands out, showing distinct crystalline peaks at approximately 14°, 17°, 21°, and 25° 2θ, which are characteristic of the α-phase of isotactic polypropylene. The sharper and slightly intensified peaks compared to pure PP suggest that graphene acts as a nucleating agent, enhancing crystalline and possibly improving mechanical properties through increased order and better load transfer in the composite.

Fig. 5XRD patterns of ABS, HIPS, PC, and PP polymers showing amorphous and crystalline regions after reinforcement by graphene.

The microstructural features observed through SEM and XRD analyses elucidate the mechanical responses measured in the composites studied. SEM images of ABS and PP demonstrate a relatively uniform dispersion of GNP, alongside ductile fracture characteristics including fibrillation, layered deformation, and crack deflection. The mechanisms facilitate efficient stress transfer from the polymer matrix to the rigid GNP sheets, resulting in increased hardness and moderate enhancements in impact strength. The XRD patterns of PP with GNP show noticeable changes in peak intensity and sharpness, suggesting a relative enhancement in crystalline ordering due to the nucleating effect of GNP, which correlates with the measured increase in stiffness and hardness. HIPS demonstrates significant GNP agglomeration and a brittle fracture morphology, characterized by microvoids and crack initiation at filler clusters. These features function as stress concentrators instead of reinforcements, which explains the decrease in both hardness and impact resistance. The largely amorphous structure in PC is maintained following GNP addition, as verified by XRD, while SEM indicates limited yet sufficient dispersion. This elucidates the marginal alteration in mechanical properties, wherein the inherently high toughness of polycarbonate predominates and constrains additional reinforcement. The combined SEM and XRD observations indicate that mechanical performance is influenced not solely by the presence of GNP, but rather by factors such as dispersion quality, interfacial compatibility, and the associated deformation and fracture mechanisms.

A definitive mechanistic correlation exists among polymer carbon content, graphene nanoplate (GNP) dispersion, and the resultant mechanical performance. Despite all examined polymers being carbon-based, variations in carbon content are inherently associated with differences in polymer chain chemistry, polarity, and the capacity for interfacial interactions with graphene. Polymers with lower carbon content and higher polarity, such as polycarbonate (PC) and acrylonitrile–butadiene–styrene (ABS), enhance interfacial interactions with GNP via π–π stacking and polar–polar interactions. This improved affinity promotes a more uniform GNP distribution, as evidenced by SEM analysis, and allows for effective stress transfer at the polymer–filler interface, resulting in significant enhancements in hardness and consistent or improved impact resistance. Conversely, polymers characterized by elevated carbon content and low polarity, such as high-impact polystyrene (HIPS) and polypropylene (PP), primarily depend on weak van der Waals forces for interaction with graphene. These diminished interactions facilitate GNP agglomeration, as demonstrated by clustered morphologies in SEM micrographs, which serve as stress concentrators and hinder the efficacy of load transfer. As a result, these systems demonstrate minimal or even adverse alterations in mechanical performance following the incorporation of GNP. In semi-crystalline polypropylene, graphene nanoplatelets function as a heterogeneous nucleating agent, enhancing crystallinity as evidenced by X-ray diffraction, which results in a moderate improvement in hardness and impact strength, despite restricted interfacial compatibility. The results indicate that carbon concentration alone does not determine nanocomposite performance; instead, the mechanical response of GNP-reinforced thermoplastics is influenced by the interplay of carbon percentage, polymer polarity, and the quality of graphene dispersion.

The development of unique fracture zones evident in the SEM micrographs is determined by the inherent molecular architecture of each polymer, the dispersion state of graphene nanoplates (GNP), and the characteristics of polymer–filler interfacial interactions. In amorphous polymers like ABS, HIPS, and PC, fracture behavior is primarily governed by localized shear yielding, microvoid creation, and crack propagation through disordered polymer chains. ABS displays coarse, fibrillated fracture surfaces attributable to its multiphase structure, wherein springy butadiene domains facilitate energy dissipation and impede crack propagation. Conversely, HIPS exhibits granular and brittle fracture regions, resulting from inadequate interfacial bonding and GNP aggregation, which serve as stress concentrators and promote fast crack initiation. Polycarbonate has remarkably smooth and uniform fracture surfaces, indicating regulated crack propagation and its intrinsic high toughness. In semi-crystalline polypropylene (PP), fracture zones arise from the presence of crystalline lamellae and amorphous tie chains, with cracks preferentially advancing at crystal–amorphous interfaces, resulting in layered and oriented fracture characteristics. The addition of graphene alters these mechanisms in a manner dependent on the polymer. The uniform distribution of GNP in ABS and PC facilitates crack deflection, crack pinning, and stress redistribution, resulting in more convoluted fracture courses and improved fracture resistance. Conversely, in HIPS and partially in PP, GNP agglomerates exacerbate local stress concentrations, leading to brittle fracture zones and premature failure. Moreover, graphene affects the crystalline-amorphous equilibrium variably among polymers.

XRD study indicates that in amorphous matrices (ABS, HIPS, PC), GNP does not facilitate bulk crystallization but may encourage localized chain ordering on the filler surface, hence enhancing stiffness without modifying the overall amorphous nature. In polypropylene, GNP serves as an efficient heterogeneous nucleating agent, augmenting crystallinity by roughly 15–20%, hence improving hardness and stiffness, while it may restrict ductility in cases of non-uniform dispersion. The observed fracture morphologies and mechanical responses result from the interrelated impacts of polymer morphology, graphene dispersion quality, and graphene-induced alterations to the crystalline–amorphous structure.

Hardness measurements

Figure 6 presents the shore hardness D values for various polymer samples, both in their original form and after reinforcement with graphene nanoplates (GNP, denoted as + GNP). The results reveal distinct differences in how hardness varies across these polymer types. It should be emphasized that the bulk carbon percentage (C%) of a polymer does not directly govern graphene nanoplates (GNP) dispersion or mechanical reinforcement. Rather, dispersion quality and load transfer are controlled by polymer polarity, the presence of functional groups, interfacial energy, melt viscosity during processing, and crystalline structure, as well as the use of compatibilizers or surface-modified fillers. In this work, C% is therefore used only as a descriptive parameter reflecting differences in polymer backbone chemistry, while the observed mechanical trends are interpreted in terms of interfacial compatibility, dispersion morphology, and deformation mechanisms^38,39^.

For ABS (Acrylonitrile Butadiene Styrene), adding GNP significantly improved hardness. Unmodified ABS had a baseline hardness of about 8 ± 0.5 Shore D, which jumped to roughly 11 ± 0.6 Shore D after GNP reinforcement a 37.5% increase. This boost suggests that GNP particles strengthened the ABS structure, likely due to strong interactions (pi-pi stacking between GNP and styrene groups) and effective stress transfer within the material.

High Impact Polystyrene (HIPS), however, showed a different response. The baseline HIPS sample had the lowest hardness among the tested polymers, at around 4.7 ± 0.3 Shore D. Surprisingly, incorporating GNP slightly reduced this to about 4.3 ± 0.4 Shore D, an 8.5% decrease. This decline indicates that GNP may not enhance HIPS’s mechanical properties and could even weaken its structure. Possible causes include uneven GNP distribution or weak bonding between GNP and HIPS (due to fewer polar sites), which might create stress points or small voids during processing.

Polycarbonate (PC) started with the highest hardness among the unmodified polymers, at approximately 14.5 ± 0.7 Shore D. Adding GNP slightly increased this to about 15 ± 0.8 Shore D, a 3.4% improvement. The larger error bars suggest some inconsistency, possibly from uneven GNP dispersion, but the overall trend supports GNP’s ability to enhance hardness. This is likely due to PC’s polar nature (carbonyl groups), which allows better bonding with nanofillers.

Polypropylene (PP) had a moderate initial hardness of around 6 ± 0.4 Shore D. With GNP, this increased slightly to about 6.5 ± 0.5 Shore D, an 8.3% gain. The modest improvement reflects PP’s non-polar nature, which limits its compatibility with GNP (relying on weaker van der Waals forces). Without compatibilizers or surface treatments, reinforcing PP with nanofillers remains challenging.

Fig. 6. Effect of graphene reinforcement on the hardness of thermoplastic polymers.

Impact test measurements

Figure 7 illustrates the impact strength measurements (in joules, J) for various polymer samples, comparing both neat polymers and their graphene-reinforced composites. The chart provides a clear representation of how graphene addition influences the impact resistance of each polymer type^39^.

Starting with ABS (Acrylonitrile Butadiene Styrene), the neat sample demonstrates moderate impact resistance, around 2.5 J. When graphene is added (ABS + Gr.), the impact strength increases slightly to about 3 J. This indicates a minor enhancement, likely due to improved stress distribution and crack deflection mechanisms introduced by the presence of graphene. However, the increase is modest, suggesting limited interfacial bonding or a low graphene loading that does not significantly alter the material’s energy absorption capacity^40,41^.

In the case of HIPS (High Impact Polystyrene), the base polymer already shows a low impact strength, approximately 2 J, and upon the addition of graphene (HIPS + Gr.), the value drops slightly, settling below 2 J. This decrease could indicate poor compatibility or agglomeration of graphene within the HIPS matrix, potentially introducing weak zones that act as stress concentrators during impact, thereby reducing toughness^27^.

The most striking observation is with Polycarbonate (PC), which exhibits the highest impact strength by far, reaching nearly 30 J. This is consistent with the well-known toughness of PC, which is widely used in applications requiring high impact resistance. When reinforced with graphene (PC + Gr.), the impact strength remains at the same high level, with only a negligible change. This suggests that graphene neither improves nor diminishes the inherent toughness of PC, possibly due to a ceiling effect where the polymer’s energy absorption capacity is already maximized^42^.

For Polypropylene (PP), the neat sample has a very low impact strength (around 1.5 J), reflecting its brittle nature under certain conditions. The addition of graphene (PP + Gr.) shows a slight improvement, bringing the value closer to 2 J. This modest enhancement could be attributed to limited dispersion or poor adhesion between the graphene and the non-polar PP matrix. While the improvement is minimal, it still points to potential for performance gains with further optimization, such as the use of compatibilizers or surface-treated fillers.

The absorbed energies reported here are geometry- and configuration-dependent and therefore are not intended for direct comparison with catalog values or ISO 179-1 impact strengths, particularly for impact-modified grades such as HIPS. Accordingly, the discussion focuses on within-study comparisons under identical processing and testing conditions, and on microstructural features (dispersion/agglomeration and fracture morphology) that explain relative changes with GNP addition.

Fig. 7. Effect of graphene addition on impact strength of tested polymers.

Correlation matrix of mechanical properties

Figure 8 demonstrates the correlation matrix between the mechanical properties of thermoplastic polymers, namely hardness and impact strength prior to and subsequent to the incorporation of graphene. A robust positive association exists between neat hardness and impact strength, indicating that polymers with greater initial hardness typically have enhanced impact resistance. This trend persists upon reinforcement, evidenced by the strong correlation between neat and graphene-reinforced values for both characteristics. The alterations in hardness and impact strength (ΔHardness and ΔImpact) resulting from graphene incorporation exhibit a relatively significant positive association, suggesting that enhancements in hardness frequently coincide with advancements in impact resistance. The matrix indicates a negative correlation between initial impact strength and subsequent improvement after reinforcement, suggesting that polymers with high toughness, like polycarbonate (PC), achieve negligible enhancements from graphene addition probably due to a saturation or ceiling effect. Conversely, materials such as ABS and PP, which initially possess moderate mechanical characteristics, exhibit more significant enhancements. The statistics also underscore the instance of HIPS, which exhibited negative or weak correlations, consistent with its recorded performance decline attributed to inadequate graphene dispersion.

Fig. 8. Relationship between hardness and impact strength in neat and graphene-filled polymers.

Statistical analysis of carbon–graphene effects on mechanical properties

The statistical review conducted using Design-Expert affirmed that the factorial models developed for hardness and impact strength effectively mirrored the experimental findings^43^. For hardness, the analysis of variance (ANOVA) revealed a non-significant lack of fit (p = 0.5859), suggesting the model fit the observed data well. While the factor effects didn’t prove statistically significant across the tested ranges, the lack of fit absence indicates the chosen model structure was a good match. Likewise, for impact strength, the ANOVA yielded a model p-value above 0.05, yet it still offered a reliable basis for exploring response trends. Collectively, these outcomes validate the models’ statistical integrity and their ability to reflect the link between carbon percentage, graphene inclusion, and the mechanical properties studied, despite the absence of notable factor effects within the examined ranges.

The relative influence of the examined components was quantified by assessing effect contributions through analysis of variance (ANOVA) results. Contribution percentages were derived from the ratio of each factor’s sum of squares to the total sum of squares for both hardness and impact strength responses. The research indicates that polymer carbon content (C%) is the principal factor, contributing the most to the total variance in mechanical properties, so suggesting that intrinsic polymer chemistry is the key determinant of nanocomposite performance. The loading of graphene nanoplates (GNP%) accounts for a minor yet statistically significant portion of the variance, affirming its reinforcing function when effective dispersion and interfacial adhesion are attained. The interaction term (C% × GNP%) significantly contributes, indicating that the influence of graphene is heavily reliant on the polymer matrix rather than functioning independently. The results quantitatively substantiate the suggested process, wherein polymer carbon content and matrix chemistry govern graphene dispersion and load transfer efficiency, therefore determining the observed mechanical response.

Figure 9 presents a normal probability plot for the externally studentized residuals from the polymer hardness model, where points are shaded according to hardness levels from 4.26 to 14.4. The points follow a mostly straight line, pointing to a reasonable assumption of normality in the residuals and lending credence to the overall reliability of our regression approach. In Fig. 10, we see the externally studentized residuals plotted against the model’s predicted hardness values, again with coloring based on observed hardness (ranging 4.26–14.4). There’s no obvious trend or funneling around the zero line, which reassures us that the predictions aren’t systematically off and that homoscedasticity is satisfied in this analysis. Figure 11 compares the model’s predicted hardness scores to the actual measurements, using color coding for hardness values between 4.26 and 14.4. The data points hug the 45-degree line pretty closely, highlighting how well the model captures the real-world polymer properties without much deviation^43^.

Fig. 9. Normal plot of residuals for hardness.

Fig. 10. Residuals vs. predicted values for hardness.

Fig. 11. Normal plot of residuals for hardness.

Figure 12 shows a normal probability plot for the externally studentized residuals tied to impact strength, with colors reflecting values from 0.883333 up to 26.83. The points track nicely along the straight line, hinting that the residuals likely follow a normal pattern, which bolsters confidence in the statistical model we’ve used for this analysis. In Fig. 13, we find the externally studentized residuals plotted alongside the predicted impact strength figures, colored according to impact strength ranging from 0.883333 to 26.83. The residuals hover around zero with no clear drift, suggesting the predictions hold steady and the data’s variance stays consistent throughout. Figure 14 lays out a comparison between the predicted and actual impact strength values, with coloring based on impact strength spanning 0.883333 to 26.83. The points sit close to the diagonal, showing a good fit between what was predicted and what was measured, which speaks to the model’s reliability in capturing impact strength accurately^44^.

Fig. 12. Normal plot of residuals for impact strength.

Fig. 13. Residuals vs. predicted values for impact strength.

Analysis of variance (ANOVA) for the factorial model assessing impact strength is presented in Table 3. The results indicate that the overall model is highly significant (F = 27384.2, p < 0.001), confirming that the selected factors adequately explain the observed variability in impact strength. Carbon content (C%) exhibits a statistically significant effect (p < 0.001), as does graphene nanoplates content (GNP%) (p < 0.001). In addition, the interaction term (C% × GNP%) is also statistically significant (p < 0.001), indicating that the effect of GNP addition on impact strength depends on the polymer carbon composition.

Fig. 14. Predicted vs. actual impact strength for impact strength.

The lack-of-fit test yields a p-value of 0.0714, which is higher than the conventional significance level (α = 0.05), indicating that the lack of fit is not statistically significant relative to the pure experimental error. This confirms that the proposed factorial model provides an adequate representation of the experimental data within the investigated design space^44^.

Table 3ANOVA factorial model for impact strength.SourceSum of squaresdfF-valuep-valueModel3503.67727384.2< 0.001C%3503.033191,573< 0.001GNP%0.30149.2< 0.001C% × GNP%0.37320.2< 0.001Residual0.1016Lack of Fit0.08122.670.0714

Analysis of variance (ANOVA) results for the factorial model evaluating hardness are summarized in Table 4. The overall model is statistically significant (F = 824.1, p < 0.001), indicating that the selected factors adequately explain the variation in hardness. Carbon content (C%) shows a highly significant effect (p < 0.001), while graphene nanoplates content (GNP%) and the interaction term (C% × GNP%) are also statistically significant (p < 0.001), confirming their influence on hardness behavior.

The lack-of-fit test yields a p-value of 0.5859, which is substantially higher than the significance level of 0.05, indicating that the lack of fit is not statistically significant relative to the pure experimental error. This confirms that the proposed factorial model provides an adequate and reliable representation of the experimental hardness data within the investigated design space^45^.

Table 4ANOVA factorial model for hardness.SourceSum of squaresdfF-valuep-valueModel381.677824.1< 0.001C%367.032645.2< 0.001GNP%4.3194.0< 0.001C% × GNP%10.4375.3< 0.001Residual0.7416Lack of Fit0.50121.330.5859

The level of agreement between empirically measured and model-predicted values was quantitatively assessed utilizing various goodness-of-fit criteria. The analysis of variance (ANOVA) validated the statistical significance of the established factorial models for both hardness and impact strength, with p-values under 0.001 for the primary effects of carbon content (C%), graphene nanoplates (GNP) loading, and their interaction. The hardness model had a high coefficient of determination (R² = 0.92), and the impact strength model revealed comparable predictive efficacy (R² = 0.90), signifying that the models account for the bulk of the observed variability in the experimental data. Furthermore, the lack-of-fit tests yielded non-significant results (p = 0.5859 for hardness and p = 0.0714 for impact strength), indicating that the residual variation is predominantly attributable to random experimental error rather than deficiencies in the model. Diagnostic plots, such as normal probability plots of residuals and predicted-versus-actual comparisons, exhibited no systematic deviations, hence reinforcing the resilience and dependability of the proposed statistical models.

Conclusions

• This investigation explored how incorporating small amounts of GNP (0.7 wt%) into four thermoplastics ABS, HIPS, PC, and PP affects their mechanical and structural characteristics. A 2 × 4 factorial design was employed to evaluate the combined effects of carbon content (C%) and GNP addition (GR%) on hardness and impact strength, testing four C% levels (76, 85, 86, 92) and two GR% levels (0, 0.7) across eight combinations, each replicated three times. The results highlight that GNP’s impact depends heavily on the polymer type, driven by variations in elemental composition (PC 30 ± 1.5 J) with a slight increase of slight hardness (14.5 ± 0.7 to 15 ± 0.8 shore hardness D), reflecting good compatibility with GNP due to polar interactions.
• Statistical analysis using Design-Expert software validated the factorial models. For hardness, ANOVA showed a non-significant lack of fit (p = 0.5859, F = 1.33), indicating a robust model fit, with significant effects (p < 0.001, R² = 0.92). homoscedasticity by diagnostic plots: Fig. 9’s normal probability plot showed residuals aligning closely with a straight line, supporting normality; Fig. 10’s residual versus predicted plot displayed no systematic trends, confirming homoscedasticity; and Fig. 11’s predicted versus actual plot showed tight clustering along the 45-degree line for hardness values (4.26–15), affirming predictive accuracy. For impact strength, ANOVA indicated significant effects (p < 0.001, R² = 0.90), but a borderline lack of fit (p = 0.0714, F = 2.67) suggests potential model limitations. Polymers with higher carbon content, like HIPS (92%), showed poorer GNP dispersion due to weaker pi-pi interactions, while lower carbon content, like PC (76%), exhibited better compatibility, likely due to stronger polar interactions with GNP’s carbon structure.
• In summary, the study demonstrates that GNP can significantly enhance thermoplastic properties, particularly for ABS and PP, where better dispersion drives mechanical improvements. However, HIPS’s poor performance underscores the importance of polymer–filler compatibility. Future work should explore GNP functionalization (e.g., amine or silane groups) or compatibilizers (e.g., maleic anhydride-grafted polymers) to improve dispersion and bonding in HIPS and PP and investigate thermal/electrical properties to fully harness GNP’s potential across diverse polymers.