Graphene Nanoplatelets Research Articles

The influence of GNP on the mechanical and thermomechanical properties of epoxy adhesive: Pearson correlation matrix and heatmap application in data interpretation

AbstractThis article explores the impact of Graphene Nanoplatelet (GNP) reinforcement on the mechanical and thermomechanical properties of epoxy adhesive. The impact of GNPs on the structural adhesive largely depends on factors like dispersion stability and GNP concentration. Given the complexity of these interactions, it is imperative to obtain indicators for the degree of each interaction. In this study, Pearson correlation matrix and heatmaps analysis were used to analyze the relationship between various variables and the strength of the connection. The addition of GNP at various concentrations to the epoxy adhesive led to a reduction in storage modulus, loss modulus, and glass transition temperature, attributed to the agglomeration of GNP. In bulk specimens, the incorporation of GNP, regardless of its content, has decreased tensile stress up to 70.7% while increasing its fracture elongation up to 396.3%. Within joining specimens with GNP, specimens with 1.5 wt% GNP content showed the highest cohesive fracture mode and largest shear strength. Pearson correlation matrix and heatmaps have demonstrated very good accuracy in reflecting the experimental data. They offer a comprehensive assessment of the relationship between various variables while indicating the degree of influence each variable has on the properties of the adhesive and joining specimens.Highlights GNP effects in adhesive can be accurately analyzed with Pearson correlation matrix & heatmaps. Connections strength for various variables can be shown by Pearson correlation matrix & heatmaps. Pearson correlation matrix & heatmaps assess variable relationships comprehensively.

Effect of water immersion on shear strength of epoxy adhesive filled with graphene nanoplatelets

Abstract Adhesive bonds are frequently used in industries such as aerospace, automotive, and civil engineering due to their ability to reduce damage to the adherend and their lightweight. However, their application is restricted by their inadequate durability and reliability in hostile environments. Graphene nanoplatelets (GNPs) are employed to enhance epoxy adhesives in this article. The thick adherend shear test is utilized to examine how the shear properties change with different water ageing times. Before exposure to water ageing conditions, GNP-reinforced adhesives exhibit a 3.51% increase compared with neat epoxy at a GNP content of 0.25 wt%. However, after 56 days of water ageing, the increase in shear strength is found to be 13.79%. This suggests that the well-dispersed GNP can reduce the degradation rate in shear properties by half, from 16.71 to 8.44%, at a GNP content of 0.25 wt%. Additionally, as water ageing time increases, the positive influence of GNP on shear properties becomes more evident. The addition of GNP delays the degradation of shear properties caused by water ageing conditions. The effect of GNP does not improve with higher GNP content. When the GNP contents increase to 1 wt%, the shear strength of the GNP-reinforced adhesive decreases compared to neat epoxy.

Effect of graphene addition on microstructure and wear behaviour of the A356-based composite fabricated by thixoforming process

Employing graphene as reinforcement in an aluminium matrix is a viable approach for developing composites with exceptional mechanical properties and wear resistance owing to its two-dimensional structure and high strengthening efficiency. This study aims to investigate the microstructure and wear behaviour of A356 aluminium matrix composites reinforced with different graphene nanoplatelets (GNPs) amounts (0.3, 0.5 and 1.0 wt%). The feedstock of composites underwent stir casting before being subjected to the thixoforming process. Field emission scanning electron microscopy (FESEM) and transmission electron microscopy micrographs (TEM) demonstrated the microstructure transformation of the composites after fabrication and the presence of carbon elements in the A356 matrix composite, respectively. TEM micrographs also displayed the existence of aluminium carbide (Al4C3) compound in the composites due to the reaction of aluminium matrix and graphene during fabrication. The hardness testing results revealed the hardness of the composite with 0.3 wt% GNPs is higher than that of A356 alloy by showing an improvement of 51.4% after the thixoforming process. The wear resistance of the composites was enhanced by decreasing the wear rate. In comparison with the as-cast and thixoformed A356 alloys, the thixoformed composite reinforced with 0.3 wt% GNPs exhibited the lowest wear rate, demonstrating a reduction of 18.7% and 11.5%, respectively. These findings demonstrated the significance of GNPs as an effective self-lubricating and favourable reinforcement for A356 aluminium matrix composite in the automotive industry.

Improving the mechanical performance of concrete by graphene nanoplatelets (GNP) enrichment in the interfacial transition zone (ITZ)

The interfacial transition zone (ITZ) between the aggregates and cementitious paste is generally a weak spot in concrete. To address this deficiency, the graphene nanoplatelets (GNP) are adopted and a novel approach is proposed in this study. Initially, GNP with three different diameters of 2 μm, 4 μm and 7 μm are evaluated. The 2 μm GNP are selected for the best strength and microstructure improvement in cementitious composites. Subsequently, the concrete made of GNP-precoated aggregate is prepared. The SEM and EDS are used to evaluate the microstructure and elementary composition of its ITZ. This research demonstrates that GNP-precoated aggregate approach significantly improves the efficacy of GNP in concrete by enhancing the ITZ. GNP promote the formation of calcium silicate hydrate (C–S–H) while concurrently mitigating the production of calcium hydroxide (CH) in ITZ, leading to enhanced elemental distribution and compactness of ITZ, as well as a reduced ITZ thickness. The proposed method notably enhances the mechanical properties of concrete.

Evaluating the effect of unidirectional loading on the piezoresistive characteristics of carbon nanoparticles

The piezoresistive effect of materials can be adopted for a plethora of sensing applications, including force sensors, structural health monitoring, motion detection in fabrics and wearable, etc. Although metals are the most widely adopted material for sensors due to their reliability and affordability, they are significantly affected by temperature. This work examines the piezoresistive performance of carbon nanoparticle (CNP) bulk powders and discusses their potential applications based on strain-induced changes in their resistance and displacement. The experimental results are correlated with the characteristics of the nanoparticles, namely, dimensionality and structure. This report comprehensively characterizes the piezoresistive behavior of carbon black (CB), onion-like carbon (OLC), carbon nanohorns (CNH), carbon nanotubes (CNT), dispersed carbon nanotubes (CNT-D), graphite flakes (GF), and graphene nanoplatelets (GNP). The characterization includes assessment of the ohmic range, load-dependent electrical resistance and displacement tracking, a modified gauge factor for bulk powders, and morphological evaluation of the CNP. Two-dimensional nanostructures exhibit promising results for low loads due to their constant compression-to-displacement relationship. Additionally, GF could also be used for high load applications. OLC’s compression-to-displacement relationship fluctuates, however, for high load it tends to stabilize. CNH could be applicable for both low and high loading conditions since its compression-to-displacement relationship fluctuates in the mid-load range. CB and CNT show the most promising results, as demonstrated by their linear load-resistance curves (logarithmic scale) and constant compression-to-displacement relationship. The dispersion process for CNT is unnecessary, as smaller agglomerates cause fluctuations in their compression-to-displacement relationship with negligible influence on its electrical performance.

Utilizing optimal physics-informed neural networks for dynamical analysis of nanocomposite one-variable edge plates

This study presents an innovative Physics-Informed Neural Network (PINN) approach designed to predict the dynamic responses of the One-Variable Edge Plate (OVEP), a unique plate structure characterized by an edge defined by arbitrary mathematical functions. The OVEP is constructed from a nanocomposite material reinforced with graphene nanoplatelets. Utilizing an optimized PINN pipeline, this research successfully predicts the vibration characteristics of the OVEP, encompassing linear, nonlinear vibrations, and beating phenomena. The study also demonstrates that the optimal PINN outperforms conventional neural network in terms of stability, accuracy (achieving above 99% accuracy), and efficiency in predicting long-duration vibrations. Additionally, the computational time required for generating testing results is notably diminished compared to traditional partial differential equation (PDE) solvers (reduced by about 3 to 12 times). To demonstrate model robustness, synthetic noise is intentionally introduced into the training data. The results not only enhance our understanding of the complex dynamics of the OVEP but also highlight the effectiveness of the proposed PINN framework in capturing and forecasting the dynamic behaviors of advanced plate structures. This research presents a promising potential for addressing dynamic problems in the fields of aerospace, civil, and mechanical engineering.

Transient bending analysis of the graphene nanoplatelets reinforced sandwich concrete building structure validated by machine learning algorithm

This paper demonstrates a thorough examination of the bending behavior of sandwich concrete building structures that are reinforced with graphene nanoplatelets (GPLs). The analysis is confirmed using a machine learning technique. Sandwich structures have notable benefits in terms of strength, longevity, and thermal insulation, making them well-suited for many building applications. Integrating GPLs into the concrete matrix improves the mechanical characteristics and performance of these structures, especially in terms of bending behavior. This study utilizes a machine learning technique to verify the characterization of the temporary bending behavior of a concrete building structure reinforced with graphene nanoplatelets. The approach utilizes a dataset consisting of simulated bending data to create a prediction model that can reliably estimate the temporary bending response of the reinforced structure under different loading situations. The machine learning algorithm’s effectiveness and dependability in optimizing the design and performance of graphene nanoplatelets reinforced sandwich concrete building structures are demonstrated through validation against simulated results. This provides engineers and designers with a powerful tool. This study enhances the comprehension and use of machine learning approaches in analyzing and designing sophisticated structural materials and systems.

Electrical and thermal properties of bio-inspired laminated Cu/Ti3SiC2/C composites reinforced by graphene nanoplatelets

Taking inspiration from the unique hierarchical structure of bio-materials like pearl oyster, this study employs bio-inspired composites technological route using flake powder metallurgy to prepare laminated Cu/Ti3SiC2/C composites. The prepared composites have clear laminated structure, uniform dispersion of reinforcing phase and clean interface. At a Cu-plated GNPs content of 0.5 wt%, the composites displayed tensile strength of 300.65 MPa, compressive strength of 575.32 MPa, electrical conductivity of 26.31 MS/m, and thermal conductivity of 285.87 W·m−1·K−1. The reinforcement of composites is caused by the load transfer effect of the laminated structure. During the loading process, the laminated structure creates multiple paths for deflecting cracks, which leads to the redistribution of the applied load. Moreover, the homogeneous distribution of GNPs throughout the laminated structure extends the mean free path of both free electrons and phonons within the material, consequently bolstering the electrical and thermal conductivity of the composites.

Fused Filament Fabrication of Polyethylene/Graphene Composites for In-Space Manufacturing.

Graphene-based composite materials are highly sought after for space applications due to their ability to encompass various properties, such as electrical conductivity, thermal resistance, and radiation shielding. This versatility allows for the creation of multifunctional components that can serve various purposes in space. Three-dimensional (3D) printing of composite materials in space offers a versatile and efficient means of manufacturing components, tools, and structures that are tailored to the unique challenges and requirements of space missions. In this work, we aim to develop 3D-printed composites made of medium-density polyethylene (MDPE) matrix and exfoliated graphene nanoplatelets (xGnP) as filler, using fused filament fabrication (FFF). Our research focuses on the challenges associated with the FFF process for fabricating MDPE/xGnP materials, particularly by optimizing filament extrusion and assessing the resulting material properties and space environmental compatibility. Firstly, we optimize the extrusion process, and use the MDPE/xGnP filaments to fabricate 3D-printed samples after defining the FFF parameters. We employ differential scanning calorimetry (DSC) to assess the melting properties and crystallization degree of the extruded filaments and 3D-printed samples, providing insights into the relationship between these properties and the characteristics of the initial powders. Electrical and tensile tests are carried out to evaluate the material properties after successfully mitigating challenges, such as warping and inadequate adhesion, to build plates during the printing process. Finally, we subject the 3D-printed composites to outgassing tests under exposure to the AM0 solar spectrum to evaluate their space environmental suitability. The results of this work demonstrate the capability of the FFF-based process to efficiently manufacture components made of MDPE/xGnP composites, providing optimized parameters for their potential in-space fabrication.

Fatigue response of multiscale extrusion-based additively manufactured acrylonitrile butadiene styrene-graphene nanoplatelets composites

This study investigates the effect of varying concentrations of graphene nanoplatelets (GNPs) on the mechanical and fatigue characteristics of acrylonitrile butadiene styrene (ABS)/GNPs nanocomposites, both in filament form and as 3D-printed parts with different raster orientations. Quasi-static and cyclic loading tests were performed on specimens containing 0.1 wt%, 0.5 wt%, 1.0 wt%, and 2.0 wt% GNPs. The results indicated that the addition of 0.1 wt% GNPs to the ABS polymer matrix increased the ultimate tensile strength (UTS) of the filament by 18 %. Addition of 1.0 wt% and 2.0 wt% GNPs to the matrix improved the Young's modulus of the filament by up to about 35 % but did not enhance the UTS. The filament containing 0.5 wt% GNPs demonstrated the highest fatigue life, even higher than that of the standard samples fabricated through injection molding technique. This was due to its high static strength, Young's modulus, and ductility. However, when the ABS/GNPs nanocomposites were 3D-printed, the addition of GNPs had no major impact on their fatigue life, especially in the higher load levels. Inadequate adhesion and reduced interlayer bonding strength resulted in a detrimental impact on fatigue life of 3D-printed objects. The extrudate-swell phenomenon seems to significantly affect this reduction in fatigue life. To address this, larger nozzle diameter (0.6 mm) was used in fabricating 3D-printed samples. Results indicated that samples with less distortion and smaller extrudate-swell had higher fatigue life. It highlights the importance of considering GNP concentration and printing parameters for optimal fatigue properties in ABS/GNPs composites.

Improved photoelectrochemical performance of tungsten-catalyzed graphene nanoplatelet electrodes prepared by hot-wire chemical vapor deposition at low substrate temperatures

The current increase in demand for graphene in various energy applications such as electrode materials for supercapacitors, batteries, thermoelectric, and hydrogen production via water-splitting, the production of high-quality graphene, considering its fascinating physical and electrical properties, high-yield, and large-area has becoming more challenging at the research and development level. Therefore, in this work, graphene nanoplatelets (GNPs) were directly grown on tungsten nanoparticle (W NP)-coated p-type crystalline silicon and quartz substrates using hot-wire chemical vapor deposition at low substrate temperatures (<500 °C). Prior to the GNP deposition, a plasma process was employed to induce the formation of W NPs, which act as a metal catalyst for facilitating the growth of large-area and multi-layer GNPs. The W NPs were formed at substrate temperatures ranging from 250 to 550 °C, with the largest graphene sheet was grown at 450 °C. Higher substrate temperatures promote the growth of high-quality graphene layers with high intensities of G (IG) and 2D bands (I2D), and high I2D/IG ratio values. The GNP photoelectrode prepared at 450 °C demonstrated better photoelectrochemical responses with the highest photocurrent density of 1.65 mA/cm2 at 1.5 VAg/AgCl, the lowest charge transfer resistance (14.0 kΩ), and the highest donor density (2.57 × 10 28 cm−3) compared to the tungsten carbide thin film and W NP electrodes prepared at the same temperature. The effects of substrate temperature on the optical, structural, and photoelectrochemical properties of the as-grown GNPs are discussed.

Designed and tailor-made double hydrophilic block copolymer-graphene nanoplatelet hybrids for reinforcing epoxy thermosets

Because of their propensity to build micellar nanostructures, amphiphilic block copolymers (ABCs) are an appropriate and unique toughening agent for epoxy systems individually on their own and in grafted form. The presence of epoxiphilic and phobic ends in ABCs is responsible for the self-assembly and the micellar structure. Nanofiller-grafted ABCs can effectively enhance the toughness of epoxy via the synergistic interaction of nanofillers and the ABCs. Even though there is sound literature supporting the effect of ABCs in epoxy, the action of double hydrophilic block copolymers (DHBC) in the epoxy matrix is less handled. Hence, the grafting of nanofillers in DHBCs and their subsequent role in tuning the properties of epoxy is a new concept. Hence this paper tries to bridge the gap via studying the effect of grafted fillers based on DHBCs in epoxy matrix. As a result, the current study focuses on the synthesis of double hydrophilic graphene nanoplatelets (rGO-g-DHBC) via nitrogen oxide-mediated polymerization for epoxy toughening application. The prepared rGO-g-DHBC was effectively utilized for epoxy toughening applications, resulting in a 457% improvement in toughness without compromising its inherent tensile strength. The mechanism behind the improved toughness was elucidated with the help of a scanning electron microscope, and the thermal, and rheological characteristics were studied.

Enhanced magneto-dielectric characteristics of Ni–Cd ferrites/GNPs composites synthesized via sol-gel auto-combustion method

Graphene nanoplatelets (GNPs) and spinel ferrites (SFs) composites enhance their properties and enable multifunctional applications, ranging from electronics to environmental and biomedical fields. This study investigates the Ni0.4Cd0.6Fe2O4/x-GNPs (x = 0 %, 2.5 %, and 5 %) [NCF/0%GNPs, NCF/2.5%GNPs, and NCF/5%GNPs] composites prepared via sol-gel auto combustion (SGAC) synthesis and their enhanced magneto-dielectric characteristics. XRD analysis confirmed the formation of a single-phase spinel matrix of NCF/GNPs composites and observed that the crystallite size (D) was enhanced from 22.8 nm to 33.6 nm with the increasing concentration of GNPs. Moreover, the bandgap energy (Eg) was reduced with the incorporation of GNPs in the NCF sample. The dielectric constant and tangent loss were enhanced with the addition of GNPs in the NCF spinel lattice. The saturation magnetization and microwave operating frequency were reduced from 97.42 emu/g to 55.13 emu/g and 21.49 GHz–11.97 GHz, respectively, while the coercivity was observed to increase from 92.66 Oe to 263 Oe with the incorporation of GNPs in the NCF lattice. The study highlights the potential of NCF/GNPs composites for applications in electronics, energy storage, sensors, and biomedical devices.

Tribological and Mechanical Properties of Graphene Nano Platelets (GNP)-Reinforced Aluminium 7075 Nano Composites

Background:: The present need for manufacturing industries is the creation of a new class of engineered materials with high specific properties. In this regard, nanocomposite materials have shown promising results compared to monolithic materials. Recent patents also show high mechanical and tribological properties. Objective:: The tribological and mechanical properties of graphene nanoplatelets (GNP)-reinforced aluminium 7075 nanocomposites are reported in this article with the objective of finding optimum properties. Methods:: The nanocomposites were successfully produced with the stir casting technique, a liquid metallurgy route with varying weight percentages of reinforcement composition of 0.5%, 1%, and 2%. Results:: The result showed an improvement in ultimate tensile strength of 69.5% and microhardness of 76.67% in contrast to the base alloy when it was cast. The wear rate was dropped significantly by 43% and 40% in 10N and 20N loading conditions with respect to as-cast conditions. Further, a decrease in the average coefficient of friction was observed from 0.680 to 0.565. Conclusion:: Graphene nanoplatelets came out as excellent reinforcement in the aluminium 7075 alloy, as they showed an impact on improved properties. The decreasing wear rate and coefficient of friction showed their self-lubricating nature. Additionally, X-ray diffraction (XRD) results and optical microstructure were also discussed.

Preparation and characterization of high-performance water-based graphene dispersions for conductive coating on textiles

Studies on e-textile applications have gained momentum with advanced material technologies. Graphene derivatives have become the focus of e-textile advanced studies due to their high conductivity potential. The chemical selection while preparing graphene dispersions to functionalize textiles affects the dispersion quality and integration into the fabric. In this study, water-based green graphene dispersions were prepared using sodium dodecyl benzene sulfonate (SDBS) as a surfactant and polyvinyl alcohol (PVA) as a binder due to its high solubility in water. The stability of graphene nanoplatelets (GNP), GNP/SDBS and GNP/SDBS/PVA dispersions were examined with the naked eye at certain time intervals. UV–vis spectroscopy results indicated that SDBS provided better dispersion and stability of graphene. The XPS results showed a strong interaction between GNP and SDBS, while the binding of PVA and SDBS in the dispersion was supported by FTIR results. Overall, the dispersion quality of water-based graphene dispersion was enhanced using PVA and SDBS for e-textile application. The electrical conductivity and tensile strength of the graphene-coated fabrics increased up to ∼1.6 (MΩ/☐) and 388%, respectively, in compared to the intact fabric.

Enhanced anti-welding and arc erosion performance of Ag-8 wt%SnO2 contact material with different addition of graphene nanoplatelets

To improve the welding resistance of Ag-8 wt%SnO2 contact material at large current, the graphene nanoplatelets (GNPs) was selected as the additive, and Ag-8 wt%SnO2 contact materials with different GNPs addition were prepared by powder metallurgy route. The electrical contact tests were performed under 36 V/16 A and 36 V/25 A, the welding, material transfer behavior and their mechanism were investigated combined with the analysis of arc duration, arc power and eroded morphology. The results show that 0.2 wt% GNPs addition decreases the welding frequency and welding force significantly, this can be attributed to the arc extinction effect and the weaken effect of the welding area. However, the excessive GNPs addition in turn aggravates the welding, the reason is that excessive GNPs addition weakens the bond between eroded layers, resulting in the decrease of arc stability and the generation of the small protrusion which cause the concentration of the contact stress and the electric field, which further results in the serious welding. Furthermore, 0.2 wt% GNPs addition decreases the mass loss rate, increasing the combination performance of Ag-8 wt%SnO2 contact material.

Effects of the geometric characteristics of graphene nanoplatelets on the physico-rheological properties of asphalt binder

While graphene nanoplatelets (GnPs) have emerged as promising nano-modifiers of asphalt binder in recent years, much is still unknown in terms of the existing correlations between the physical, chemical, and geometric characteristics of this nanofiller and observed asphalt binder properties. In this work, we investigate the important correlation between the geometric characteristics of GnPs and the rheological properties of the GnP-modified asphalt binder at high temperatures. Our results indicate that, in general, incorporating GnPs with large mean particle diameters (> 14 μm) and thicknesses (> 8 nm) enhances the high-temperature performance of the asphalt binder. The results of the multiple stress creep and recovery tests confirm that including GnPs in asphalt binder can decrease its permanent deformation by 33.2% and enhance its elastic recovery by 53.9%. Phase contrast images obtained by atomic force microscopy further indicate that the presence of GnPs with large mean particle diameters alters the morphology of the asphalt binder, leading to improved temperature stability and less susceptibility to permanent deformation.

Ultrasonication Influence on the Morphological Characteristics of Graphene Nanoplatelet Nanocomposites and Their Electrical and Electromagnetic Interference Shielding Behavior.

Graphene nanoplatelets (GNPs)/epoxy composites have been fabricated via gravity molding. The electrical and thermal properties of the composites have been studied with variable GNP type (C300, C500, and C750, whose surface areas are ~300, 500, and 750 m2/g, respectively), GNP loading (5, 10, 12, and 15 wt.%), and dispersion time via ultrasonication (0, 30, 60, and 120 min). By increasing the time of sonication of the GNP into the epoxy matrix, the electrical conductivity decreases, which is an effect of GNP fragmentation. The best results were observed with 10-12% loading and a higher surface area (C750), as they provide higher electrical conductivity, thereby preserving thermal conductivity. The influence of sonication over electrical conductivity was further analyzed via the study of the composite morphology by means of Raman spectroscopy and X-ray diffraction (XRD), providing information about the aspect ratio of GNPs. Moreover, electromagnetic shielding (EMI) has been studied up to 4 GHz. Composites with C750 and 120 min ultrasonication show the best performance in EMI shielding, influenced by their higher electrical conductivity.

Composites with aligned and plasma-surface-modified graphene nanoplatelets and high dielectric constants

We have developed a method for designing polymer and graphene nanoplatelet (GNP) composites that show high dielectric constants over a wide range of GNP contents. GNPs are dispersed in the composites through plasma-surface modification and aligned by applying an electric field (EF). This creates a large number of microcapacitor structures of GNPs separated by the polymer. The maximum dielectric constant of the sample to which the EF is applied is approximately twice that of the sample to which the EF is not applied. Furthermore, the maximum dielectric constants of the samples with plasma-surface modified GNPs are higher than those of the samples with unmodified GNPs. The composites show high dielectric constants (∼500 at 100 Hz) over a wide range of GNP contents (6 ∼ 10 wt%) while maintaining mechanical flexibility (Young’s modulus:12 ± 4 MPa).

Effect of ethylene vinyl acetate foam-graphene composite material on the mechanical properties of sports footwear

Ethylene vinyl acetate (EVA) foam is widely used as midsole material in athletic footwear due to its lightweight and cushioning properties. However, EVA foam suffers from low mechanical strength, abrasion resistance, and fatigue resistance. Reinforcing EVA foam with graphene nanoplatelets is a promising approach to improving its mechanical performance for footwear applications. This study investigated the effect of 0.1–1 wt% graphene nanoplatelets on the properties of EVA foam composites relevant to midsole performance. The results showed that 0.1–0.2 wt% graphene provided optimal reinforcement, exhibiting 33–40% higher impact energy absorption, 50–60% lower compressive stiffness, 30% higher flexural stiffness, and up to 40% lower abrasion volume loss. Under simulated use conditions, the composites demonstrated higher energy return and fatigue resistance. The graphene nanoplatelets acted as effective reinforcements within the EVA foam by improving stress transfer, inhibiting crack propagation, and shielding the foam surface. The findings indicate that reinforcing EVA foam with small amounts of graphene nanoplatelets can develop midsole materials with enhanced mechanical performance for athletic footwear.