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Review

Research Progress on the Preparation and Properties of Graphene–Copper Composites

1
State Key Laboratory of Advanced Power Transmission Technology, China Electric Power Research Institute, Beijing 100192, China
2
School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083, China
*
Authors to whom correspondence should be addressed.
Metals 2025, 15(10), 1117; https://doi.org/10.3390/met15101117 (registering DOI)
Submission received: 17 September 2025 / Revised: 5 October 2025 / Accepted: 7 October 2025 / Published: 8 October 2025
(This article belongs to the Special Issue Study on the Preparation and Properties of Metal Functional Materials)

Abstract

The persistent conflict between strength and electrical conductivity in copper-based materials presents a fundamental limitation for next-generation high-performance applications. Graphene, with its unique two-dimensional architecture and exceptional intrinsic characteristics, has become a promising reinforcement phase for copper matrices. This comprehensive review synthesizes recent advancements in graphene–copper composites (CGCs), focusing particularly on structural design innovations and scalable manufacturing approaches such as powder metallurgy, molecular-level mixing, electrochemical deposition, and chemical vapor deposition. The analysis examines pathways for optimizing key properties—including mechanical strength, thermal conduction, and electrical performance—while investigating the fundamental reinforcement mechanisms and charge/heat transport phenomena. Special consideration is given to how graphene morphology, concentration, structural quality, interfacial chemistry, and processing conditions collectively determine composite behavior. Significant emphasis is placed on interface engineering strategies, graphene alignment, consolidation control, and defect management to minimize electron and phonon scattering while improving stress transfer efficiency. The review concludes by proposing research directions to resolve the strength–conductivity paradox and broaden practical implementation domains, thereby offering both methodological frameworks and theoretical foundations to support the industrial adoption of high-performance CGCs.

1. Introduction

Copper (Cu)-based materials, due to their exceptional electrical conductivity, thermal conductivity and favorable processability, hold an irreplaceable position in industrial fields such as power transportation, electronic devices and rail transit [1,2,3,4,5,6]. However, with the ongoing advancement of modern technology, conventional Cu materials increasingly fall short of meeting the stringent performance requirements of contemporary industrial systems [7,8,9]. A key limitation lies in the inherent electrical resistance of Cu, which causes a significant proportion of electrical energy to dissipate as heat during conduction, resulting in energy loss [10]. This issue is further compounded by the positive temperature coefficient of resistance; rising operational temperatures lead to increased resistance, which can trigger failures such as open circuits in power lines and constrained output in electric motors. Additionally, the relatively low mechanical strength of Cu restricts its use in structurally demanding applications. These challenges have intensified the demand for advanced copper-based materials capable of delivering superior performance. For instance, high-speed railway contact wires necessitate a combination of high strength (>600 MPa) and high electrical conductivity (>80% International Annealed Copper Standard, IACS). However, conventional Cu-based materials face an inherent trade-off between strength and electrical conductivity, which makes it challenging to achieve both properties simultaneously [1,11,12]. This limitation has emerged as a major technical bottleneck in the development of high-strength and high-conductivity Cu alloys. A widely adopted strategy to overcome this limitation involves incorporating a secondary phase that enhances mechanical strength without significantly compromising electrical performance. In this context, graphene (Gr) and its derivatives have attracted considerable interest over the past decade as ideal reinforcing fillers for high-performance Cu composites, owing to their extraordinary mechanical, electrical, and thermal properties [13,14,15,16,17,18].
Numerous studies have reported graphene–copper composites (CGCs) that exhibit simultaneous improvements in both strength and electrical conductivity [19,20,21,22,23,24]. For instance, Peng et al. developed a composite through in situ growth of N-doped graphene, which achieved an electrical conductivity of 95.1 %IACS and a tensile strength 1.94 times that of pure Cu, highlighting its potential for electronic packaging and thermal management applications [25]. Similarly, Liu et al. designed bio-inspired zebra-skin structured CGCs with an ultra-high thermal conductivity of 968 W·m⁻1·K⁻1, demonstrating great promise for heat dissipation in high-power electronic devices [26,27,28].
Current research efforts are focused on integrating the exceptional properties of Gr and Cu to enable scalable and cost-effective manufacturing of CGCs. The central approach leverages the unique advantages of Gr—including its high current density limit (>108 A·cm⁻2) [29], exceptional electron mobility (>15,000 cm2·V⁻1·s⁻1) [30], and superior thermal conductivity (~5300 W·m⁻1·K⁻1) [31]—in combination with the high charge carrier density (8.491 × 1028 m⁻3) [32] of Cu to achieve synergistic performance enhancement. Strategies for enhancing the performance of Cu-based composites primarily involve graphene reinforcement, interface engineering, and processing optimization. As an example, Ding et al. employed atmospheric pressure chemical vapor deposition (APCVD) to grow bilayer Gr on Cu foil, reporting a 7.83% improvement in electrical conductivity. Nevertheless, the uniform dispersion of Gr—a critical requirement for optimal performance—remains elusive due to its pronounced propensity to agglomerate via van der Waals forces [27]. Yang et al. employed spark plasma sintering (SPS) to minimize interfacial impurities, yielding a composite with 108.6 %IACS conductivity. Despite this success, the widespread adoption of SPS is limited by its high energy consumption and equipment costs [33]. In a separate study, Gwalani et al. incorporated Gr into a Cu matrix through shear deformation, achieving a fivefold increase in local electrical conductivity. the formation of nanoscale grains during processing may reduce ductility, potentially compromising the mechanical integrity of the composite [34].
Despite the significant progress outlined above, the development of high-performance CGCs remains fraught with complex challenges [35,36,37]. As systematically summarized in Table 1, which provides a comparative overview of CGCs produced via mainstream fabrication routes, no single methodology can simultaneously optimize all properties. Instead, each pathway presents a unique set of advantages and limitations, underscoring the critical influence of the selected synthesis strategy on the resulting graphene morphology, interfacial architecture, and ultimate composite performance. While existing reviews have often provided valuable but segmented insights into specific areas—such as fabrication methods or individual mechanical or electrical properties—a holistic and critical analysis connecting processing parameters to multiscale microstructure and the resulting trade-offs in multifunctional performance is notably absent from the literature. This review is specifically designed to fill this critical gap. Our work sets itself apart by establishing a unified ‘process-structure-property-performance’ framework, which systematically deciphers the intricate interdependencies that govern the strength–conductivity trade-off in CGCs. A central and novel theme of this article is the in-depth exploration of synergistic interface architecture, which encompasses strategies like plasma functionalization [38] and N-doping [35], and its combined effect with microstructural engineering via thermo-mechanical processing on achieving concurrent property enhancement [39].
Beyond this integrative perspective, this review provides a forward-looking assessment of the scalability and technical feasibility of prominent fabrication routes—a crucial aspect often overlooked in foundational research but essential for guiding future industrial translation. By synthesizing the current state of knowledge through this unique lens, we aim to not only offer a comprehensive knowledge base but also to identify emerging trends, persistent bottlenecks, and actionable pathways for the rational design of next-generation Cu composites. It is anticipated that the insights consolidated herein will accelerate the development of efficient and sustainable material solutions for advanced industrial applications in power transmission and electronics, thereby contributing to broader goals of energy conservation and sustainable technological development.

2. Preparation of CGCs

Owing to its exceptional carrier mobility and ultra-high thermal conductivity (theoretically up to ~5300 W·m⁻1·K⁻1 for a monolayer), Gr serves as a promising reinforcement for Cu matrices [30,40,41,42,43,44]. The development of CGCs is fundamentally aimed at harnessing the complementary properties of both materials—combining the superior intrinsic characteristics of Gr with the high electrical/thermal conductivities and stability of Cu—to achieve synergistic multifunctional performance. Based on the preparation route of Gr, the fabrication of CGCs can be classified into two main pathways: “top-down” and “bottom-up”. Each route encompasses the key stages of Gr synthesis, dispersion, and consolidation, as summarized in Figure 1. The top-down approach exfoliates three-dimensional (3D) precursors such as graphite through physical or chemical forces (e.g., mechanical force and electrochemical intercalation). Typical methods include the reduction of graphene oxide and liquid-phase exfoliation. These processes are relatively simple but may introduce structural defects into the Gr. In contrast, the bottom-up strategy employs carbon-containing small molecules as precursors to grow graphene in a controlled manner, either on substrate surfaces or in the liquid phase, using techniques such as chemical vapor deposition (CVD) or solution-based chemical synthesis. This route can produce high-quality, low-defect graphene films and simultaneously achieve uniform dispersion of graphene within the matrix. However, it demands more advanced equipment and precise processing conditions. For graphene synthesized via the top-down route, additional techniques are often employed to achieve uniform dispersion in the Cu matrix. Common methods include ball milling, electrodeposition, and molecular-level mixing. Finally, consolidation is carried out to densify the CGCs. This involves the regulation of temperature, pressure, and duration during processes such as hot-press (HP) sintering, SPS, rapid thermal annealing (RTA), and subsequent deformation processing like extrusion, drawing, or rolling. These steps help reduce internal porosity, optimize grain size and orientation, and enhance the overall density of the composite material.
Alternatively, the preparation techniques for CGCs can be categorized based on the bonding mechanism between Gr and the Cu matrix. This classification includes physical bonding methods, such as conventional powder metallurgy (PM), and chemical bonding approaches like molecular-level mixing (MLM), electrochemical deposition (ED), and CVD. A detailed overview is provided below.
The conventional PM method is a widely used manufacturing process for CGCs, valued for its simplicity, flexibility, and strong near-net-shape capability. The process typically employs atomized pure Cu or Cu-based alloy powders as the raw material. Its key steps involve ball milling, mixing, compaction, and sintering for densification [46,47,48,49,50]. Specifically, Gr is first blended with the metal powder to form a composite powder, which is then consolidated into a bulk form through compaction and densification processes such as sintering, pressing, and/or rolling [51]. A schematic illustration of the PM process for fabricating CGCs is presented in Figure 2a. Studies have shown that several processing parameters—including ball milling speed, ball-to-powder ratio, milling medium, duration, and Gr content—significantly influence the dispersion state of Gr within the metal matrix, and consequently, the overall performance of the CGCs [10].
The MLM method enables homogeneous integration of Gr with Cu powders, either with or without surfactants and dispersion media. Its key procedural steps involve mixing Cu2⁺ ions with a graphene oxide (GO) suspension, followed by drying/reduction and consolidation. This technique enhances the interfacial reinforcement efficiency by establishing molecular-level bonding between carbon and metal atoms, effectively mitigating the poor wettability inherent between Cu and Gr [52,53,54]. Hwang et al. applied MLM to fabricate reduced graphene oxide (rGO)/Cu composites, which exhibited significant improvements in mechanical properties compared to pure Cu, including approximately 30% increase in tensile strength, 80% in yield strength, and 30% in elastic modulus [55]. In contrast to ball-milled mixtures, MLM facilitates more extensive adsorption of metal ions onto carbon nanostructures (CNs), leading to superior suppression of graphene agglomeration and a more homogeneous distribution of GO within the Cu matrix. Furthermore, the formation of Cu–O–C bonds through reactions between Cu2⁺ ions and oxygen-containing functional groups on GO surfaces enhances interfacial bonding at the molecular level.
The conventional PM process often fails to effectively prevent the agglomeration of Gr within the metal matrix. This limitation arises from the inherent poor affinity between Gr and the metal in the absence of specific bonding sites, causing graphene to readily separate from metal particles. To address this issue, alternative dispersion strategies such as ED have been developed. The core mechanism of electrochemical deposition involves the co-deposition of Cu ions and Gr (or its precursors) onto the cathode within an electrolytic cell. This method offers notable advantages, including low cost, high production efficiency, and customizable processing conditions, making it a reliable technique for fabricating Cu-based composite coatings [56]. In a typical setup, a chemical reaction occurs within the electrolyte bath, where metal salts undergo thermochemical decomposition, releasing metal ions that subsequently integrate with Gr to form the composite material [57,58,59,60]. For high-quality graphene integration in CGCs, Yu et al. proposed the EP-TS method, which combines electrodeposition, thermal reduction, and powder sintering into a single protocol (Figure 2b). This technique enhances the thermal stability of the composites and is suitable for rapid, large-scale production of high-performance CGCs [58].
CVD offers a viable route for fabricating bulk CGCs. This technique addresses several limitations commonly associated with alternative methods, such as inadequate graphene dispersion, weak interfacial bonding, and structural damage to graphene. The core procedure involves exposing Cu foil or powder to carbon-containing gases at elevated temperatures, enabling in situ growth of Gr on the metal surface. Subsequent processing steps, including stacking and compression, are then employed to consolidate the material into bulk form with optimized structural integrity [61,62,63,64]. Within a CVD system, the extended mean free path of gas molecules promotes a uniform distribution of carbon precursors on the Cu substrate. The low solubility of carbon in Cu, coupled with the self-limiting growth behavior of Gr, favors the synthesis of few-layer graphene with controlled morphology [65,66]. Moreover, CVD supports the scalable production of composites, making it particularly suitable for emerging industrial applications. Nevertheless, precise control over graphene layer number, uniformity, and defect density remains a critical challenge. Dongho Shin et al. employed CVD to fabricate multilayer graphene coatings, as illustrated in Figure 2c, demonstrating the potential of this approach for producing high-quality CGCs [67].
Figure 2. Preparation approaches of CGCs: (a) PM method. Reproduced with permission [10], Copyright. (b) ED method. Reproduced with permission [58], Copyright. (c) CVD method. Reproduced with permission [67], Copyright.
Figure 2. Preparation approaches of CGCs: (a) PM method. Reproduced with permission [10], Copyright. (b) ED method. Reproduced with permission [58], Copyright. (c) CVD method. Reproduced with permission [67], Copyright.
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3. Research Progress on Electrical Conductivity

3.1. Theory of Conductive Mechanism

The enhancement of electrical conductivity in CGCs is primarily attributed to the optimization of electron transport pathways and the suppression of interface-induced electron scattering [68,69,70,71,72]. When Gr is embedded between Cu layers, the continuous 2D graphene structure can become electron-doped through charge transfer from Cu. This electron-enriched graphene, combined with its intrinsically high electron mobility, facilitates the formation of highly conductive percolation networks within the composite, significantly improving overall electrical performance [73,74,75]. To achieve high electrical conductivity in CGCs, it is essential to minimize factors that impede electron motion, such as grain boundaries, dislocations, graphene oxide residues, and metal carbides [76]. Additionally, non-conductive voids, pores, and other structural defects should be reduced, along with the presence of low-conductivity secondary phases [77,78,79].
Material densification also plays a critical role in electrical conductivity. However, as the mass fraction of Gr increases, the relative density of the composite typically declines due to dispersion difficulties and interfacial incompatibility, often resulting in reduced conductivity. Compared to HP sintering, SPS not only improves densification but also lowers oxygen content, both of which contribute positively to electrical conductivity [33].
The electrical performance of CGCs is critically governed by the structural attributes of Gr, such as defect density, number of layers, and lateral dimensions. In a study by Cao et al., the influence of Gr layer count (n) on composite conductivity was systematically examined [80]. Their comparative analysis across multiple CGCs systems revealed that multilayer graphene introduces additional structural imperfections and modifies the interlayer electronic environment. These changes attenuate the charge transfer doping effect from the Cu matrix and concurrently reduce both carrier mobility and concentration, ultimately resulting in degraded conductive properties, as depicted in Figure 3 [80]. The same research also established a pronounced correlation between bulk electrical conductivity and the graphene volume fraction (VGr). By varying the thickness of stacked Cu foils to control VGr, they found that conductivity increases with thinner Cu layers and correspondingly higher Gr content [80]. In a related investigation, Zeng et al. proposed that an in situ formed, continuous graphene network can facilitate charge transport via an interfacial electron tunneling mechanism [81]. Their findings further indicated that the conductivity enhancement follows a nonlinear relationship with Gr concentration, reaching an optimum around 0.1 wt.% Gr.
Interfacial scattering plays a critical role in determining the electrical conductivity of CGCs. Using density functional theory calculations, Subedi et al. revealed that reducing the interfacial distance between Cu and Gr below 3 Å significantly mitigates electron scattering, thereby enhancing overall conductivity. Under such conditions, Gr acts as an electron-transport bridge, leading to a 20% improvement in electrical conductivity [82]. Conversely, Zhang et al. demonstrated that an increase in the number of graphene layers introduces additional interfacial defects, intensifying electron scattering and degrading conduction performance. Their simulations showed that single-layer graphene (SLG) composites exhibit optimal electrical conductivity. To model the system, graphene layers were inserted into the Cu matrix along the (111) crystallographic plane, forming a unit cell denoted as C1Cux, where x represents the number of Cu layers. Calculations of in-plane conductivity for CGCs with carbon mass ratios between 2% and 6% (Figure 4) revealed that the composite systems consistently exhibited lower conductivity than pure Cu, with values further decreasing as the carbon content increased—contradicting the conventional view that Gr addition enhances conductivity [83]. First-principles calculations conducted by Zhang et al. identified interfacial scattering at the Gr–Cu boundary as a principal mechanism responsible for conductivity degradation. Notably, their simulations revealed that imposing compressive strain along the Cu (111) plane substantially enhances electron transport, suggesting a viable pathway for optimizing interface design in CGCs [84].
Subsequent investigations have demonstrated anisotropic electrical conduction in these composites, with conductivity typically superior in the direction perpendicular to the applied sintering pressure. Nepal et al. further elucidated the role of crystallographic orientation, noting that Cu (111) and (110) planes exhibit higher epitaxial matching with graphene, facilitating the formation of a coherent electron transport pathway [85]. In contrast, impurities such as sulfur and nitrogen disrupt the conjugated carbon network of graphene, thereby degrading carrier mobility. A separate strategy involves the construction of three-dimensional graphene (3D-Gr) architectures, which minimize the number of distinct Cu–Gr interfaces and thus significantly reduce interfacial electrical resistance. For example, He et al. fabricated a continuous 3D-Gr network within a Cu matrix via chemical vapor deposition, achieving a composite conductivity approaching that of high-purity Cu, which they attributed to the establishment of low-resistance conductive channels [86]. The unusual recrystallization and grain coarsening that occur during the CVD process further contribute to enhanced conduction. The observed dependence of conductivity on VGr and its anisotropic nature collectively underscore graphene’s active role in modifying charge transport behavior [80]. Consequently, promising approaches for enhancing electrical performance include the fabrication of 3D-Gr networks via in situ synthesis combined with spark plasma sintering, the judicious incorporation of highly conductive metallic elements, and the improvement of overall composite density.
Overall, the fundamental conduction mechanism in CGCs hinges on the synergistic optimization of interfacial conditions and electron transmission pathways [86], providing a theoretical foundation for targeted interface engineering.

3.2. Structural Design Innovation

Strategic control over graphene orientation and composite architecture represents a pivotal approach for enhancing electrical conductivity in CGCs. Chen et al. utilized a laser-induced 3D-Gr network combined with a Cu matrix to create a dual conductive architecture. Through optimized electrodeposition, they achieved aligned graphene structures that delivered a current-carrying capacity of 1.34 × 105 A·cm⁻2—76% superior to pure Cu [87]. Similarly, He et al. demonstrated that a 3D-Gr network not only provides structural reinforcement but also establishes efficient conductive pathways, yielding composites with electrical conductivity approaching that of high-purity Cu [86].
In a notable study, Cao et al. employed chemical vapor deposition to integrate high-mobility Gr with high-carrier-density Cu. Through meticulous interface design and morphological control, they realized a composite exhibiting both high electron mobility and density. Remarkably, with a graphene volume fraction of merely 0.008%, the composite achieved an electrical conductivity of 117 %IACS, surpassing the silver standard (108 %IACS) [80]; the corresponding fabrication process and microstructure are illustrated in Figure 5. However, reproducibility studies by Khanbolouki et al. revealed that certain exceptional results reported in the literature—including conductivities up to 114 %IACS—may represent measurement artifacts arising from dimensional inaccuracies, particularly in thin or soft specimens [88]. This highlights the critical importance of precise metrology in characterizing low-dimensional materials such as fine wires and thin films. Slight inaccuracies in measuring diameter, thickness, or cross-sectional uniformity can be substantially amplified, leading to significantly distorted property evaluations.
Significant progress has been achieved in the development of gradient composite architectures for CGCs. Jiang et al. fabricated CGCs through CVD followed by vacuum hot rolling (Figure 6). The composite processed with 30% thickness reduction exhibited a tensile strength of 223 MPa, elongation of 45%, and electrical conductivity of 101.52 %IACS. This balanced property profile stems from grain refinement combined with optimized graphene dimensions and spatial distribution, which collectively enhance both load transfer efficiency and electron transport pathways [89]. In a complementary approach, Xing et al. designed a bimodal grain structure architecture. Through precise control of the coarse-to-fine grain ratio via thermomechanical processing, they achieved a remarkable yield strength of 315 MPa while maintaining 95.7 %IACS electrical conductivity, demonstrating how microstructural engineering can simultaneously enhance mechanical and electrical properties [90]. Peng et al. developed an alternative strategy involving in situ growth of oriented N-doped graphene within layered Cu composites. The aligned distribution of interlayer graphene significantly minimized electron scattering probability, thereby improving conduction efficiency [25]. Meanwhile, Yang et al. created a Cu-decorated Gr reinforcement system. Using chemical reduction methodology, they uniformly anchored Cu nanoparticles onto Gr surfaces, effectively suppressing graphene aggregation while optimizing interfacial bonding. This interfacial modification increased the composite conductivity to 93.96 %IACS [91]. These innovative approaches highlight how sophisticated structural design and interface engineering can overcome traditional performance trade-offs in metal matrix composites.
Researchers explored how the microstructure of CGCs is related to its electrical performance. A two-phase mixture model, namely the Hashin–Shtrikman model, was used [92,93,94]. The upper and lower limits of the electrical conductivity of the CGCs system (σU and σL respectively) are shown as Equations (1) and (2):
σ U = σ C u + V G r 1 σ G r σ C u + V C u 3 σ C u
σ L = σ G r + V C u 1 σ C u σ G r + V G r 3 σ G r
Among them, σCu and σGr are the electrical conductivities of Cu and Gr, and VCu and VGr are the volume fractions of Cu and Gr, respectively. In this analysis, we adopt a consistent value of σCu = 5.81 MS·m−1 across all scenarios. To account for the influence of Gr quality on the overall conductivity of CGCs, two distinct values of σGr are employed [45]. Specifically, a value of σGr = 0.1 MS·m−1 is used for Gr with low conductivity—such as in situ grown Gr, rGO, and mass-produced mechanically exfoliated flakes [95]. In contrast, a higher value of σGr = 100 MS·m−1 [96] is applied to high-conductivity Gr, typified by CVD-grown Gr.

3.3. Optimization of Preparation Process

In PM-processed CGCs, electrical conductivity is highly sensitive to Gr content and dispersion quality. Albartouli and Uzun reported that agglomeration at Gr loads above 1.5 wt.% caused conductivity to drop to 43.49 %IACS, whereas optimization of the dispersion process enabled a 0.5 wt.% composite to reach 76.59 %IACS [97]. Similarly, Salvo et al. observed a 22% increase in conductivity with only 1 wt.% Gr incorporated via PM at 600 °C, while hardness values remained comparable to similarly processed pure Cu [98].
ED techniques also facilitate performance improvements. Yu et al. demonstrated that N-doped graphene introduced via pulsed electrodeposition promotes electron transfer within the Cu matrix, an effect particularly pronounced at elevated temperatures—enabling the composite to retain superior conductivity at 180 °C [99]. Pavithra et al. utilized reverse pulse ED to fabricate CGCs foil composites that maintained conductivity levels similar to pure Cu while achieving a hardness of 2.5 GPa and an elastic modulus of 137 GPa [56].
CVD-based routes produce particularly clean and well-bonded interfaces. Ding et al. grew bilayer graphene (BLG) on Cu foil via atmospheric pressure CVD, which reduced interfacial impurities and increased electrical conductivity by 7.83% [27]. Pan et al. fabricated an alternating Cu–Gr layered composite with six graphene layers, reporting a conductivity of 104.2 %IACS at a VGr of only 0.008%—4.5% higher than the international annealed copper standard under identical conditions [100]. This enhancement is attributed to charge transfer from Cu to Gr, which preserves the high carrier mobility of Gr. Further increases in Gr content within such architectures may offer additional conductivity gains.
Collectively, these studies confirm that process-induced improvements in graphene dispersion and interfacial bonding are critical to the electrical performance of CGCs, as further summarized in Table 2. Analysis of the data compiled in Table 2 reveals a critical insight: the simple incorporation of highly conductive Gr into a Cu matrix does not guarantee an enhancement in electrical conductivity. Paradoxically, a significant portion of the reported CGCs exhibit conductivity values lower than those of pure Cu. Notably, conductivities reaching or exceeding 100 %IACS are predominantly observed in composites fabricated via CVD, and these instances are consistently associated with a low VGr (typically <0.09 vol.%). This superior performance is likely attributable to the distinctive attributes of CVD-synthesized graphene, which often features fewer layers, minimal structural defects, and a clean, intimately bonded interface with the Cu substrate. Such characteristics are crucial for mitigating interfacial electron scattering. Furthermore, the CVD process can favorably influence the grain size and orientation of the Cu matrix, thereby collectively enhancing the electron transport efficiency of the composite. It is also paramount to note the considerable variation in the sample geometry and dimensions across different studies, coupled with the employment of diverse conductivity measurement techniques. The discrepancies in accuracy and applicability among these methods underscore the necessity for establishing standardized testing protocols to ensure the reliability and cross-comparability of reported data.
Novel processing strategies continue to advance the performance of CGCs. Chen et al. implemented laser direct writing to create patterned Gr distributions, which—when combined with electrodeposition—yielded composites with substantially enhanced current-carrying density [87]. Shu et al. achieved uniform dispersion of Gr-encapsulated Cu particles through in situ surface modification followed by vacuum hot pressing, extending the electrical contact life of the resulting composite to three times that of pure Cu [111]. Through planetary ball milling of Gr with chromium and subsequent rapid HP, Zhang et al. generated nanoscale chromium carbide precipitates that refined the Cu grain structure while retaining 85.7 %IACS conductivity [83]. Zeng et al. developed a combined ball milling and vacuum hot-pressing method that constructed a continuous graphene network, simultaneously increasing electrical conductivity and reducing the friction coefficient by 52% relative to pure Cu [81]. He et al. further demonstrated that the structural nature of carbon layers on Cu powder—and thus the resulting composite properties—can be precisely tuned by controlling the hydrogen atmosphere ratio during spark plasma sintering, leading to concurrent gains in conductivity and hardness [86].
These innovations underscore that the orchestration of interfacial reactions and the optimization of sintering parameters are central to scaling up high-performance CGCs. Looking forward, exploiting multiscale synergistic effects—such as optimized electron transport via interfacial charge transfer, scattering suppression through 3D-Gr networks, and uniform reinforcement distribution via advanced processing—will be crucial to overcoming challenges in large-scale production and deployment under extreme service environments.

4. Research Progress on Thermal Conductivity

4.1. Theory of Heat Conduction Mechanism

The fundamental mechanisms of heat conduction differ significantly between metals and non-metals. Cu primarily facilitates thermal transport through electron movement, whereas Gr excels via phonon propagation [112]. This complementary behavior makes Gr an exceptionally promising reinforcement for enhancing the thermal conductivity of Cu-based composites, where heat transfer involves a synergistic combination of phonon transport and electron-phonon interactions [113]. A critical factor governing overall performance is the interfacial thermal resistance (ITR), which is strongly influenced by the spatial distribution of the reinforcement and the quality of the Gr–Cu interface. Interestingly, the introduction of specific metal oxides or carbides can promote interfacial electron-phonon coupling and energy exchange, thereby reducing ITR and improving composite thermal properties.
Substantial research confirms the role of Gr as an effective thermal reinforcement in Cu matrix [114,115,116]. This enhancement stems from two primary mechanisms: first, a uniformly dispersed Gr network facilitates efficient interactions between electrons and phonons; second, robust interfacial bonding strengthens adhesion, improves electronic interaction, and enhances electron transfer efficiency across the interface. Collectively, these effects improve thermal transport by enabling both electrons and phonons to traverse the Gr–Cu interface more effectively [117]. Moreover, strong interfacial adhesion reduces phonon scattering and minimizes thermal resistance caused by lattice mismatch, further boosting the overall thermal conductivity of CGCs.
Film-based composite architectures often report the most substantial thermal improvements, with conductivity enhancements of 20–35% [118]. However, achieving high thermal conductivity remains complex and is governed by multiple factors, including Gr content, layer number, interfacial treatment, chemical modification, and processing conditions.
The number of graphene layers profoundly influences thermal conductivity. SLG offers an ideal, densely packed structure that provides a highly efficient heat transfer path. Jagannadham reported that in multi-layer graphene systems (MLGS) with three or more layers, phonon attenuation occurs predominantly in the outer layer, while inner layers remain relatively unaffected by interface scattering, thereby preserving excellent heat transfer capability [119]. However, increasing layer count introduces additional interfacial resistance, leading to a nonlinear relationship between layer number and composite thermal conductivity. Zhu et al. further demonstrated through simulation that ITR decreases with increasing layer number, stabilizing when the number of layers reaches five or more. Among different crystallographic orientations, the Cu (011) plane exhibited the highest ITR (3.2 GW·m⁻1·K⁻1), attributed to its atomic close-packing alignment with graphene. Notably, within a defect density range of 0–4%, vacancies can serve as phonon scattering centers that unexpectedly enhance thermal conductivity [120].
Lateral flake size also significantly affects thermal performance. Yang et al. observed that micrometer-wide carbon-rich regions suppress phonon transport, thereby reducing thermal conductivity [121]. In contrast, smaller graphene sheets with nanoscale thickness and uniform dispersion minimize phonon scattering and facilitate higher conductivity. Appropriate interface treatment can enhance the thermal conductivity of composite materials. Liu et al. pre-treated the surface of Gr paper to increase its surface roughness. The “embedding points” or “dots” form mechanical anchor points, enhancing the adhesion between Cu and Gr paper and increasing the interfacial contact area. The resulting zebra-skin structure dramatically enhanced thermal transfer, achieving a remarkable thermal conductivity of 968 W·m⁻1·K⁻1 for 70 vol.% GP/Cu composites [26].
Strain engineering presents further opportunities for tuning thermal properties. Samal et al. found that applying a 0.20% compressive strain induced a dramatic increase in the electronic thermal conductivity (κₑ) of Cu–Gr heterosystems—from 320.72 W·m⁻1·K⁻1 to 869.76 W·m⁻1·K⁻1—primarily due to strain-induced electron density of states reconstruction and increased free electron concentration near the Fermi level [122]. Conversely, Kazakov et al. revealed through molecular dynamics simulations that embedding finite-length graphene into Cu induces lattice distortion, reducing thermal conductivity (e.g., three 15 nm graphene layers decreased Cu’s thermal conductivity from 380 to 163.6 W·m⁻1·K⁻1). In contrast, infinitely long graphene layers formed continuous phonon channels, increasing conductivity to 803.3 W·m⁻1·K⁻1 [123]. These findings highlight the significant potential of strain engineering and structural design for optimizing electronic and thermal transport.

4.2. Structural Design Innovation

By designing 3D heterogeneous structures and implementing topological optimization in layered composites, it is possible to overcome the thermal conductivity limitations of conventional composite materials. Wang et al. developed a Cu-CF-Cu “sandwich” structure using vacuum filtration and hot-pressing sintering. This process established a long-range ordered carbon fiber layer and a graphene-like 3D network, resulting in an in-plane thermal conductivity of 510 W·m⁻1·K⁻1 for composites with 40 vol% carbon fiber—45.7% higher than that of pure Cu. This enhancement is attributed to reduced interfacial phonon scattering and improved electron mobility [124]. Cakir et al. utilized plasma-enhanced chemical vapor deposition (PECVD) to fabricate 3D Gr-coated Cu powder, forming a multi-layered graphene network. The resulting composite exhibited a thermal diffusion coefficient of 1.38 cm2·s⁻1, surpassing that of pure Cu by 40%. The Gr coating also acts as a lubricant during sintering, promoting densification and reducing porosity to 0.8%, while simultaneously inhibiting grain growth—the average grain size decreased from 12 μm to 3.5 μm [125]. Almonti et al. introduced a multi-layer electrodeposition strategy involving alternating Cu and Gr deposition to form a gradient interface. This method increased the thermal diffusion coefficient by 65%, primarily due to the introduction of interlayer stress gradients that mitigate interfacial thermal mismatch [126].

4.3. Optimization of Preparation Process

Innovations in fabrication techniques are critical for enhancing interfacial bonding and reinforcement dispersion uniformity.
Gao et al. implemented an electrostatic self-assembly strategy in which negatively charged GO was adsorbed onto cation-functionalized Cu powder, yielding a uniformly hybridized GO-Cu composite powder (Figure 7a). Their analysis of the correlation between Gr content and thermal conductivity (Figure 7b) identified an optimum loading of 0.3 wt.%, corresponding to a maximum thermal conductivity of 396 W·m⁻1·K⁻1 [127]. This enhancement is attributable to three main factors: (1) the uniform graphene distribution enabled by electrostatic self-assembly; (2) clean, tightly bonded Gr–Cu interfaces with low ITR; and (3) the use of large graphene flakes, which mitigate the adverse effect of porosity on phonon transport. Beyond 0.3 wt.%, however, graphene aggregation perturbs Cu grain connectivity, and increased porosity and interfacial defects collectively degrade thermal performance.
Cakir et al. developed a low-temperature (400 °C) PECVD process that achieved a conformal 5–15 nm graphene coating on Cu powder, overcoming the agglomeration issues common in conventional high-temperature treatments [125]. In a different approach, Almonti et al. introduced a multilayer electrodeposition-coating technique that effectively suppressed graphene agglomeration through alternating Cu and Gr deposition, increasing the composite’s thermal diffusivity by 65% [126]. Pu et al. demonstrated in situ Gr growth directly on Cu nanoparticles, which reinforced the interfacial bonding and resulted in a composite thermal conductivity of 376 W·m⁻1·K⁻1, along with a 30% reduction in corrosion rate [128]. The combination of low-temperature PECVD and pressureless sintering offers a scalable route to produce agglomeration-free, uniformly coated Cu powders [125]. Separately, Wang et al. showed that precise control of hot-pressing parameters—such as a pressure of 50 MPa and a dwell time of 60 min—can reduce interfacial porosity from 12% to 2.1% and extend the average phonon mean free path by a factor of 1.8 [124].
In a study by Seungchan Cho et al., carbon nanotubes (CNTs) were investigated as an effective reinforcing phase for improving the thermal conductivity of Cu matrix composites. The researchers fabricated CNTs-Cu composites and systematically investigated the influence of CNT dispersion and Cu–CNT interfacial quality on thermal transport properties. Thermal conductivity (λ) was determined using the relationship λ = α·ρ·Cp, where α represents thermal diffusivity, ρ is bulk density, and Cp denotes specific heat capacity. As summarized in Table 3, which lists the measured thermophysical parameters, the thermal conductivity initially rises with increasing CNT content but declines beyond a certain threshold. This non-monotonic behavior is attributed to progressive CNT agglomeration into bundles at higher concentrations, which creates high-resistance thermal junctions between nanotubes and reduces the effective contact area with the Cu matrix, thereby impairing overall heat transfer efficiency [129,130].
As illustrated in Figure 8a, Cu-35 vol% GNP composites were produced from powders prepared via vortex mixing or ball milling, subsequently consolidated by vacuum filtration and SPS. Composites originating from ball-milled powders showed an 18.5% reduction in in-plane thermal conductivity relative to those made from vortex-mixed powders. Raman spectroscopy (Figure 8b) revealed heightened D-band intensity in ball-milled specimens, indicating a greater density of structural defects in the graphene. These imperfections serve as phonon scattering centers, degrading the intrinsic thermal conduction of GNPs and thereby compromising the macroscopic thermal performance of the CGCs [10].
A summary of thermal conductivity values for CGCs prepared via various methods is provided in Table 4. Enhancing the thermal conductivity of CGCs relies on strategic design and processing approaches: constructing continuous thermal conduction pathways, minimizing interfacial thermal resistance, optimizing morphological architecture, and achieving uniform graphene dispersion. Future advancements will likely emerge from the development of 3D interconnected graphene networks, architecturally aligned layered structures, and hybrid interface engineering techniques. Such innovations are essential to meet the escalating thermal management demands of high-power electronic devices and next-generation thermal modules, facilitating the broader industrial adoption of CGCs.

5. Research Progress on Mechanical Properties

5.1. Mechanical Mechanism Theory

CGCs have demonstrated superior mechanical strength compared to conventional Cu materials [55,135,136]. Recent research on their mechanical mechanisms has centered on interfacial co-deformation, defect engineering, and nanostructural evolution. However, achieving a simultaneous improvement in both strength and toughness remains a fundamental challenge in metallic material design. The strengthening behavior of CGCs involves multiple mechanisms that have not yet been fully integrated into a unified theoretical framework. The primary reinforcement mechanisms reported in the literature can be categorized as follows:
Load transfer mechanism: Under external stress, load is effectively transferred from the Cu matrix to Gr via interfacial shear. This mechanism, commonly described by shear-lag theory, is particularly prominent in CGCs due to the 2D planar structure of Gr [137,138,139]. A 3D-Gr network further enhances this effect by interlocking with the Cu matrix, providing improved crack bridging and deflection.
Thermal mismatch mechanism: The significant difference in the coefficients of thermal expansion between Cu and Gr induces dislocation generation near Gr interfaces during cooling [64,140]. These dislocations impede slip under mechanical loading, although the overall contribution of this mechanism to strength is generally limited.
Grain refinement strengthening: Also known as Hall–Petch strengthening, this mechanism arises from grain boundaries acting as both dislocation sources and barriers [141]. Refined grain structures can enhance both strength and ductility within certain size ranges [142]. Studies indicate that grain refinement accounts for approximately half of the yield strength improvement in CGCs during tensile deformation.
Orowan strengthening: This mechanism occurs when dislocations bypass Gr obstacles rather than cutting through them, leading to additional strengthening [143]. It requires homogeneous dispersion of Gr within Cu grains [144]; however, in practice, graphene tends to segregate along grain boundaries, limiting the effectiveness of Orowan strengthening in CGCs.
Jiang et al. employed molecular dynamics simulations to investigate the cooperative deformation mechanism in 3D continuous network CGCs. Their results indicated that both the architecture of the graphene network (GN) and the concentration of defects significantly influence the plastic coordination behavior by modulating the bonding strength at the Gr–Cu interface [145]. For example, introducing an appropriate density of intrinsic defects was shown to improve the continuity of the 3D-GN, thereby optimizing interfacial stress transfer. Yang et al. further examined the interfacial behavior between Gr and Cu across different crystallographic planes ({100}, {111}, {110}). They demonstrated that the Gr−Cu{100} interface is more susceptible to plastic deformation under compressive loading, whereas Gr effectively suppresses dislocation propagation at the {111} and {110} interfaces. This behavior is closely associated with the evolution of Shockley partial dislocations (1/6<112>) [146]. From the perspective of defect engineering, Pang et al. revealed that cross-layer vacancy clusters can induce the formation of sp3 hybrid bonds in BLG, enhancing interfacial adhesion with the Cu matrix and increasing the composite’s tensile strength by approximately 30% [147]. Additionally, Zhang et al. compared two BLG stacking configurations (Hollow vs. Top) and found that the Hollow configuration exhibits superior mechanical strength and plasticity, which they attributed to its higher electron charge density (0.118 e·Å⁻3) and greater resistance to dislocation slip [148]. The application of coarse-grained molecular dynamics (CGMD) has further extended the feasible scale of simulations. For instance, Nan et al. utilized a CG model to evaluate the effect of VGr (48.57%) on the thermal and tensile properties of composites, achieving an error of only 4.2%—offering a robust tool for multi-scale mechanism research [149].
In experimental studies, Wei et al. fabricated CNTs-rGO/Cu composites through pH-controlled molecular-level mixing. The resulting composite with 2.5 vol% carbon nanostructures (CNS-RGO) exhibited an optimal strength–ductility balance, achieving an ultimate tensile strength of 601 MPa while maintaining an electrical conductivity of 83 %IACS [150]. This simultaneous enhancement of strength and conductivity is attributed to the formation of carbon-rich and carbon-lean regions: the former refines grains and impedes dislocation motion (via grain refinement and load-transfer mechanisms), while the latter facilitates uninterrupted electron transport.

5.2. Structural Design Innovation

Structural design innovation plays a central role in enhancing the performance of CGCs. Jiang et al. proposed a 3D continuous network architecture, which promotes uniform stress distribution during tensile deformation through a 3D interlocking effect between Gr and the Cu matrix. This configuration results in a 25% increase in yield strength compared to conventional dispersion-strengthened structures [145]. Zhang et al. designed a BLG stacking configuration (Cu/Gr/Gr/Cu) and systematically compared its thermoelectric properties under strain. They found that the “Hollow” structural variant exhibited a thermal conductivity 2.55 times higher than that of the “Top” configuration at 15% longitudinal strain. Meanwhile, the “Top” configuration demonstrated superior electrical conductivity under high strain (20–25%), which was attributed to enhanced electron localization effects [148]. Furthermore, Liu et al. fabricated layered CGCs via in situ CVD. By leveraging the high electron mobility of graphene and its grain-boundary pinning effect, the annealed composite achieved an electrical conductivity exceeding 100 %IACS while maintaining a tensile strength of 238 MPa [151]. In addition, Li et al. employed a graphene powder spraying technique to produce layered composites. This method enhanced the material’s strength by 17% without compromising electrical conductivity (105.12 %IACS). The improvement is mainly due to the effective obstruction of dislocation motion by the interlayer graphene [152]. These innovative structural strategies highlight the significance of microstructural engineering in simultaneously enhancing mechanical and functional properties in CGCs.

5.3. Optimization of Preparation Process

The performance and interfacial integrity of CGCs are highly dependent on the optimization of fabrication techniques. Both the manufacturing route and the Gr content significantly influence the mechanical properties of CGCs. As summarized in Table 5, different preparation methods lead to considerably varied mechanical performances. Composites incorporating RGO often exhibit superior mechanical characteristics, mainly due to efficient load transfer within the Cumatrix facilitated by the formation of Cu-O-C covalent bonds, which enhance interfacial adhesion and stress transmission.
Mutlu et al. explored various manufacturing methods with an emphasis on maximizing reinforcement efficiency while minimizing Gr content [156]. Similarly, Hidalgo-Manrique et al. provided a comprehensive overview of processing technologies, detailing improvements in strength, stiffness, and ductility, and discussed the roles of preparation conditions, Gr content, and functionalization [10].
In powder metallurgy, Yue et al. examined the effect of ball milling time (1–7 h) on CGCs. Prolonged milling improved graphene dispersion but also induced structural defects, as indicated by the increase in the ID/IG ratio in Raman spectra (Figure 9a) [51]. Similarly, Cui et al. reported a decrease in the I2D/IG ratio from 0.6 to 0.5 with increasing milling speed (100 to 300 r·min⁻1), reflecting greater defect density (Figure 9b) [157].
Wei et al. studied electrochemical deposition and found that a Gr concentration of 0.4 kg·m⁻3 in the plating bath resulted in the highest ID/IG value within the range of 0.04–1.6 kg·m−3 [154]. As shown in Figure 10, the ultimate tensile strength (UTS) and Vickers hardness of CGCs initially increase and then decrease with rising Gr content. The optimum mechanical properties were achieved at 0.3 wt.% Gr, whereas elongation at break gradually declined with higher Gr content [127].
Phuong et al. compared high-energy ball milling (HEB) with nano-dispersion (ND) technology, noting that ND resulted in more uniform grain sizes (≤50 nm), leading to improvements of 40% in hardness, 66% in tensile strength, and 38% in wear resistance—attributed to stronger Gr−Cu interfacial bonding [158]. Yu et al. investigated extrusion temperature effects and found that room-temperature extrusion yielded the highest yield strength (221.4 MPa) and electrical conductivity (111.5 %IACS), while extrusion at 600 °C increased elongation to 42.3% due to dynamic recrystallization and twinning [157]. Da Cruz et al. employed accumulative rolling and heat treatment to enhance hardness by 28% via oxide layer control and mechanical interlocking aided by oxygen vacancy repair [159]. Wang et al. fabricated composites with 0–1.5 wt.% Gr via powder metallurgy and reported a 65% increase in yield strength with 0.5% Gr compared to pure Cu [160]. Luo et al. deposited silver on reduced graphene oxide (Ag-rGO) and used powder metallurgy to produce composites, significantly improving tensile strength with only 0.6 vol.% Ag-rGO [161]. The experimental results show that the tensile strength of the composite material is significantly improved by adding 0.6% (volume fraction) of Ag-rGO. Hwang et al. applied molecular-level mixing to achieve homogeneous dispersion, considerably enhancing tensile strength, yield strength, and elastic modulus [55]. Wei et al. used pH-controlled MLM to fabricate CNTs-rGO/Cu composites, reaching a tensile strength of 601 MPa and conductivity of 83 %IACS at 2.5 vol.% CNS-RGO [153]. To improve interfacial wettability and bonding, Han et al. metallized Gr with nickel via CVD to produce Ni-rGO, then fabricated a 0.33% Ni-rGO/Cu composite through molecular-level mixing, increasing yield strength by 90%. The improvement stems from Ni-enhanced interfacial resistance to deformation and improved load transfer.
Progress in optimizing the mechanical properties of CGCs ultimately converges on the strategic management of interfaces and microstructure. While the fundamental strengthening mechanisms—load transfer, grain refinement, and dislocation interaction—are well-understood, their effective harnessing is dictated by material architecture. The overarching goal is the rational design of heterogeneous structures (e.g., 3D networks, laminates) that optimally distribute graphene to reconcile strength with other vital properties like ductility and electrical conductivity. Translating these designed microstructures into reliable, bulk components through scalable processes represents the final frontier for their industrial adoption in cutting-edge sectors.

6. Interface Engineering: Decoupling the Strength–Conductivity Trade-Off

The macroscopic properties of CGCs are fundamentally determined by the characteristics of their micro-interfaces. These interfacial regions function as critical pathways for mechanical load transfer while simultaneously acting as primary sites for electron scattering, representing the physical origin of the inherent strength–conductivity trade-off [35,82]. Optimal interface design must reconcile two seemingly competing requirements: establishing robust interfacial adhesion to enable efficient stress transfer and mechanical strengthening, while maintaining low-resistance, defect-minimized interfaces to minimize electron scattering and preserve high conductivity. However, strong interfacial bonding is frequently accompanied by chemical reactions or complex atomic reconstructions that may introduce high-resistivity phases (e.g., metal carbides) or intensify phonon/electron scattering, thereby compromising conductive performance [83]. Consequently, precise interface engineering is essential for overcoming this fundamental compromise.
Current interfacial modification strategies primarily focus on tailoring the chemical and physical structure of the interface. Nitrogen doping represents an effective approach for modulating the interfacial electronic structure [25]. The incorporation of N atoms into the graphene lattice alters its local electron density distribution, thereby reducing the work function difference between Gr and Cu. This modification lowers the interfacial potential barrier and enhances electron tunneling, significantly benefiting electrical conductivity. Simultaneously, the formation of C–N–Cu covalent bonds provides superior interfacial strength compared to van der Waals interactions, contributing to mechanical enhancement. Plasma functionalization introduces controlled functional groups and defect sites onto graphene surfaces through physical bombardment and chemical activation [38]. These active sites serve as anchoring points for Cu atom deposition and bonding, substantially improving interfacial adhesion and load transfer efficiency through the formation of strong chemical bonds such as Cu–O–C. However, this process requires precise parameter control to avoid excessive damage to the sp2-conjugated structure of graphene, which would compromise its intrinsic high conductivity and mechanical properties. Furthermore, interfacial phase engineering involves the introduction of carbide-forming elements (e.g., Cr, Ti). During processing, these elements form in situ nanometric carbides (e.g., Cr₃C₂) at the Gr−Cu interface [83]. These nanoparticles effectively pin dislocations, significantly enhancing material strength through the Orowan strengthening mechanism. When their size and distribution are carefully controlled, the scattering effect on electrons can be minimized, enabling substantial strength improvement with only marginal conductivity reduction.
Notably, the composite fabrication process intrinsically determines the resulting interfacial structure. For instance, the CVD method typically produces clean, coherent interfaces dominated by van der Waals interactions, which favor electron transport. In contrast, MLM and surface-modified PM routes are more conducive to establishing strong chemically bonded interfaces, advantageous for stress transfer [55,66]. Therefore, the understanding and control of interfacial architecture must be integrated with the specific synthesis methodology.
In a word, interface engineering serves as the crucial bridge connecting material synthesis with performance optimization. The meticulous micro-nano scale modulation of the Gr–Cu interface through strategies such as doping, functionalization, and second-phase design enables the synergistic optimization of mechanical and electrical properties, providing essential guidance for designing next-generation high-performance Cu-based materials.

7. Summary and Prospects

Despite significant advances in CGCs, their transition from laboratory research to broad industrial implementation requires resolving several fundamental and application-oriented challenges. The following critical issues and promising research directions are specifically highlighted:
(1)
Atomic-level interface engineering. While current studies often correlate processing parameters with macroscopic properties, a deeper understanding of atomic-scale interfacial phenomena remains essential. Fundamental mechanisms governing charge transfer, chemical bonding states, and defect-mediated adhesion at the graphene–copper interface need further elucidation. Given the high reactivity of metallic copper, precise control of interfacial reactions is crucial—not only to prevent the formation of resistive phases but also to exploit potential synergistic effects. Such knowledge is imperative for the rational design of composites with predictable and tailored properties.
(2)
Spatial organization of graphene. Realizing the full potential of CGCs depends critically on achieving uniform graphene dispersion and controlled alignment within the copper matrix. Although surface modification strategies can improve wettability, the underlying principles governing nanoscale distribution and orientation require systematic investigation. Advanced processing techniques that enable the directional alignment of two-dimensional graphene sheets could yield composites with designed anisotropic characteristics, opening up applications in directional heat management and structured load-bearing components.
(3)
Architectural design of composites. Current composite systems primarily utilize graphene as a discrete reinforcing phase. Future designs should pursue more sophisticated architectures, such as metal-decorated graphene interfaces or graphene-encapsulated metal particles, to construct hierarchical and multifunctional material systems. These novel configurations could significantly broaden the application horizons of CGCs into fields including catalytic systems, energy storage devices, and advanced electronic packaging.
In conclusion, addressing these challenges will necessitate interdisciplinary collaboration spanning materials synthesis, interface science, and advanced manufacturing technologies. Continued innovation in material architectures and processing methodologies will ultimately pave the way for the next generation of high-performance, application-ready CGCs.

Author Contributions

Conceptualization, W.L. and X.Z.; validation, H.L. and Y.D.; formal analysis, W.L.; investigation, X.Z.; writing—original draft preparation, H.L.; writing—review and editing, W.L. and X.Z.; supervision, Y.D.; funding acquisition, H.L. and Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the State Key Laboratory of Advanced Power Transmission Technology (Grant No. GEIRI-SKL-2023-010).

Data Availability Statement

No new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GrGraphene
CGCsGraphene–copper composites
CuCopper
IACSInternational Annealed Copper Standard
APCVDAtmospheric pressure chemical vapor deposition
CVDChemical vapor deposition
SPSSpark plasma sintering
HPHot-press
RTARapid thermal annealing
PMPowder metallurgy
MLMMolecular-level mixing
RGOReduced graphene oxide
GOGraphene oxide
2DTwo-dimensional
3DThree-dimensional
PECVDPlasma-enhanced chemical vapor deposition
CNsCarbon nanostructures
VGrVolume fraction of graphene
GNGraphene network
ITRInterfacial thermal resistance
UTSUltimate tensile strength
HEBHigh-energy ball milling

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Figure 1. Fabrication of CGCs involving Gr synthesis, dispersion, and consolidation is shown in gray, green, and blue, respectively. Reproduced with permission [45]. Copyright.
Figure 1. Fabrication of CGCs involving Gr synthesis, dispersion, and consolidation is shown in gray, green, and blue, respectively. Reproduced with permission [45]. Copyright.
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Figure 3. Influence of graphene layer count on electrical conductivity. (a) Raman spectra of CVD-grown Gr on Cu foil with varying layer numbers (1 to 10). (b) Spatial mapping of the I2D/IG intensity ratio across a 30 µm × 30 µm region. (c) Current-carrying capacity of CGCs as a function of graphene layers. Reproduced with permission [80], Copyright.
Figure 3. Influence of graphene layer count on electrical conductivity. (a) Raman spectra of CVD-grown Gr on Cu foil with varying layer numbers (1 to 10). (b) Spatial mapping of the I2D/IG intensity ratio across a 30 µm × 30 µm region. (c) Current-carrying capacity of CGCs as a function of graphene layers. Reproduced with permission [80], Copyright.
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Figure 4. (a) Conductivity versus carbon ratio in CGCs, with the C1Cu19 atomic structure provided as a representative model. (b) Cross-sectional profile of the average in-plane local conductivity normal to the Cu (111) plane. Reproduced with permission [83], Copyright.
Figure 4. (a) Conductivity versus carbon ratio in CGCs, with the C1Cu19 atomic structure provided as a representative model. (b) Cross-sectional profile of the average in-plane local conductivity normal to the Cu (111) plane. Reproduced with permission [83], Copyright.
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Figure 5. CGCs were prepared by depositing Gr via CVD method. (ac) Schematic of the multilayer stacking and hot-pressing process. (d) Cross-sectional structure of the Cu/Gr-layers/Cu interface. (e,f) EBSD images of the Cu foil before and after graphene deposition. (g) TEM image and grayscale analysis of the interface, revealing predominantly bilayer graphene with occasional tri- and tetralayer regions. Reproduced with permission [80], Copyright.
Figure 5. CGCs were prepared by depositing Gr via CVD method. (ac) Schematic of the multilayer stacking and hot-pressing process. (d) Cross-sectional structure of the Cu/Gr-layers/Cu interface. (e,f) EBSD images of the Cu foil before and after graphene deposition. (g) TEM image and grayscale analysis of the interface, revealing predominantly bilayer graphene with occasional tri- and tetralayer regions. Reproduced with permission [80], Copyright.
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Figure 6. Schematic of the fabrication process for CGCs, involving the synthesis of aligned graphene by CVD followed by consolidation via vacuum hot rolling. Reproduced with permission, Copyright [89].
Figure 6. Schematic of the fabrication process for CGCs, involving the synthesis of aligned graphene by CVD followed by consolidation via vacuum hot rolling. Reproduced with permission, Copyright [89].
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Figure 7. (a) Fabrication process of CGCs. (b) Thermal conductivity as a function of graphene content. Reproduced with permission [127], Copyright.
Figure 7. (a) Fabrication process of CGCs. (b) Thermal conductivity as a function of graphene content. Reproduced with permission [127], Copyright.
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Figure 8. (a) Comparison of in-plane thermal conductivity for Cu–35 vol% GNP composites fabricated from vortex-mixed and ball-milled powders. (b) Corresponding Raman spectra of the powder blends. Reproduced with permission [10], Copyright.
Figure 8. (a) Comparison of in-plane thermal conductivity for Cu–35 vol% GNP composites fabricated from vortex-mixed and ball-milled powders. (b) Corresponding Raman spectra of the powder blends. Reproduced with permission [10], Copyright.
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Figure 9. Effect of (a) milling time and (b) milling speed on the mechanical properties of CGCs. Reproduced with permission [51,157], Copyright.
Figure 9. Effect of (a) milling time and (b) milling speed on the mechanical properties of CGCs. Reproduced with permission [51,157], Copyright.
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Figure 10. Correlation between Gr content and the electrical/mechanical properties of CGCs. Reproduced with permission [127], Copyright. (a) UTS/MPa; (b) Hardness.
Figure 10. Correlation between Gr content and the electrical/mechanical properties of CGCs. Reproduced with permission [127], Copyright. (a) UTS/MPa; (b) Hardness.
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Table 1. Performance overview of CGCs fabricated via primary routes.
Table 1. Performance overview of CGCs fabricated via primary routes.
Fabrication MethodTypical Graphene StateKey MeritsTypical Electrical Conductivity (%IACS)Typical Tensile Strength (MPa)Typical Thermal Conductivity (W·m⁻1·K⁻1)Primary Challenges
Powder metallurgyNanosheets, potential agglomerationProcess simplicity, cost-effectiveness, near-net-shape capability~75–95~250–400~350–400Dispersion homogeneity, weak interfacial bonding
Molecular-level mixingGO/rGO, abundant functional groupsMolecular-level dispersion, strong interfacial bonding~80–97~300–500~370–410Graphene quality (defects), residual oxygen groups
Electrochemical depositionNanosheets, potentially vertically alignedLow-temperature processing, complex shapes/coatings~85–100~250–450~360–400Solution stability, limited deposit thickness
Chemical vapor depositionIn situ grown, large-area, low defectsClean interface, superior graphene quality~95–117~220–350~400–500+High equipment cost, complex process, scalability
Table 2. Electrical conductivity of CGCs prepared using different methods.
Table 2. Electrical conductivity of CGCs prepared using different methods.
Electrical ConductivityPreparation MethodGr ContentTesting Method/InstrumentReferences
84.2 %IACSLiquid-phase mixing0.3 wt.%Digital eddy current conductivity meter (Sigma 2008B, Xiamen Tianyan Instrument Co., Ltd., Xiamen, China)[101]
86.2 %IACSRTA + roll0.12 wt.%Eddy current method[102]
92.5 %IACSMLM + SPS0.2 vol.%Eddy current method[103]
94 %IACS CVD + HPFour-probe method[104]
95.7 %IACS CVD + ball milling + SPS0.28 vol.%Eddy current method[63]
95.9 %IACS Powder metallurgy + HP0.5 wt.%Digital conductivity meter (D60K-1201, Xiamen Xinbote Technology Co., Ltd., Xiamen, China)[105]
97.1 %IACS Ball milling + RTA + HP + Hot rolling1.6 vol.%Four-point probe instrument (Ecopia EPS-300, Ecopia, Republic of Korea)[106]
97.5 %IACS Wet ball milling + HP0.6 wt.%A conductivity meter (Sigmascope SMP10, Helmut Fischer GmbH, Sindelfingen, Germany)[107]
Sintering: 98.05 %IACS; Cold drawing: 94.85 %IACS;
Anneal: 97.28 %IACS
RTA+sintering/cold drawing/annealing0.021 wt.%Digital eddy current conductivity meter (Sigma 2008B, Xiamen Tianyan Instrument Co., Ltd., Xiamen, China), high precision Casley current voltmeter, CMT6104 general purpose machine of MTS, MTS Systems (China) Co., Ltd., Shanghai, China[64]
100.5 %IACS CVD + vacuum hot pressing, hot extrusion, and cold drawing0.08–0.09 vol.%Eddy current conductivity method and four-probe conductivity method[65]
102 %IACS CVD + shear extrusion25 ppmElectrical properties (HAHPE) measurement system, Four-point probe instrument (Ecopia EPS-300, Ecopia, Republic of Korea)[108]
103.4 %IACS RTA + HP + hot rolling0.387 vol.%Eddy current conductivity meter (FQR-7501, Xiamen Xinsha Instrument Co., Ltd., Xiamen, China)[61]
103.65 ± 0.072 %IACS CVD+hot extrusion0.0025 wt.% (250 ppm)Standard four-point probe method according to ASTM B193 standard [109][46]
110 %IACSCVD + magnetron sputtering deposited Cu<0.0008 vol.%Four-probe method[110]
117 %IACSCVD + HP0.008 vol.%Four-probe method[80]
Table 3. Thermal properties of CNT-Cu composites fabricated by means of SPS at 823 K. Reproduced with permission [129,130], Copyright.
Table 3. Thermal properties of CNT-Cu composites fabricated by means of SPS at 823 K. Reproduced with permission [129,130], Copyright.
CNTs Contents (vol.%)
00.51.01.52.03.05.010.0
Thermal diffusivity (cm2·s−1)1.033691.050681.064191.073291.056101.065711.044161.04468
Specific heat (J·g−1·K−1)0.384000.384360.384720.385090.385460.386200.387730.39177
Thermal conductivity (W·m−1·K−1)348.7353.1359.2357.2351.3354.2340.5335.2
Table 4. Comparative summary of the thermal conductivity of CGCs fabricated via different routes.
Table 4. Comparative summary of the thermal conductivity of CGCs fabricated via different routes.
Gr SourceMaterialPreparation MethodThermal Conductivity
(W·m−1·K−1)
References
RGOPTG/Cu-CuxO + Cu + 0.1wt%PTGsintered168.5[131]
UTG + Cu + 0.1wt%UTG64.8
Pure Cucharge adsorption +
thermal reduction +
HP sintering
375[132]
0.3wt%RGO + Cu405
0.6wt%RGO + Cu413
0.9wt%RGO + Cu364
FGr/Cupulsed-current co-electrodeposition497[133]
Gr5%GNP/Cuelectroless plating method298.7[134]
20%GNP/Cu221.4
GP/Cuvacuum hot pressing968[26]
Table 5. Comparative summary of the mechanical properties of CGCs fabricated via different routes.
Table 5. Comparative summary of the mechanical properties of CGCs fabricated via different routes.
Gr SourceMaterialPreparation MethodYield Strength (MPa)Maximum Strength (MPa)Elongation (%)References
RGO2.5 vol% RGO/CuMLM + SPS 284 [55]
Pure CuMLM + self-assemble + SPS73.92947.2[153]
2.5 vol% RGO/Cu82.24507.5
2.5 vol%CNT-RGO/Cu107.460111.8
0.3 wt%RGO + Cucharge adsorption + thermal reduction + HP sintering90.8191.314.4 [132]
0.6 wt%RGO + Cu188206.321
0.9 wt%RGO + Cu158226.712
Pure Cu3964221.66
GrGr/Cu-50vacuum HP sintering4745160.80 [64]
Gr/Cu-805055490.96
1.6 g·L⁻1Gr/Cupulse electrodeposition15627418.7[154]
Gr/Cuaccumulative roll-compositing28168616.5 [155]
0.6 wt%Gr/Cuwet ball milling + HP65.2290.4749.3[107]
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Liu, W.; Zhao, X.; Li, H.; Ding, Y. Research Progress on the Preparation and Properties of Graphene–Copper Composites. Metals 2025, 15, 1117. https://doi.org/10.3390/met15101117

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Liu W, Zhao X, Li H, Ding Y. Research Progress on the Preparation and Properties of Graphene–Copper Composites. Metals. 2025; 15(10):1117. https://doi.org/10.3390/met15101117

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Liu, Wenjie, Xingyu Zhao, Hongliang Li, and Yi Ding. 2025. "Research Progress on the Preparation and Properties of Graphene–Copper Composites" Metals 15, no. 10: 1117. https://doi.org/10.3390/met15101117

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Liu, W., Zhao, X., Li, H., & Ding, Y. (2025). Research Progress on the Preparation and Properties of Graphene–Copper Composites. Metals, 15(10), 1117. https://doi.org/10.3390/met15101117

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