Graphene-reinforced metal matrix composites: fabrication, properties, and challenges

Chen, Dongju; Li, Jia; Sun, Kun; Fan, Jianqing

doi:10.1007/s00170-023-10886-4

Cited by 21 publications

(10 citation statements)

References 231 publications

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“…15,44 These finding are consistent with those of other researchers. 4,15,44,45 Ritapure et al 45 In a study by Chen et al, 46 an 18% reduction in strength was observed in a composite containing 1-wt.% graphene compared with the aluminum matrix. In the current work, the reduction was only 4% and 8% for Al-1G and Al-1TG, respectively.…”

Section: Characterization Of Mechanical Propertiesmentioning

confidence: 98%

A facile treatment of graphite as a reinforcement for Al‐based nanostructured composite

Bakhshizade,

Shokuhfar,

Zolriasatein

et al. 2024

Surface & Interface Analysis

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Aluminum‐graphite composites find extensive applications in diverse industries, including automotive and aerospace sectors. However, the fabrication of these composites faces a significant challenge due to poor wettability and weak interfacial bonding between graphite and aluminum. This work aims to modify the graphite particles to improve the characteristics of aluminum. In this study, treated graphite (TG) was synthesized using a facile method for the first time. Graphite (G) was mixed with acetone and stirred with a mechanical stirrer at 2000 rpm for 1 h, followed by drying in an electric oven at 80°C for 1 h. Mechanical milling and subsequent hot pressing were employed to manufacture composites with 1, 3, and 5 wt.% of G and TG. The results demonstrated that the addition of G and TG up to 5 wt.% substantially improved the wear rate and coefficient of friction (COF). However, it also resulted in a deterioration of the mechanical properties of aluminum. The TG‐reinforced composites exhibited enhanced mechanical and tribological properties owing to the stronger bonds formed between carbon and aluminum atoms. Notably, the composite with 5‐wt.% G and TG exhibited an 80% and 58% lower COF compared with unreinforced aluminum. Composites containing 1‐wt.% G and TG showed an 11% and 1% reduction in yield strength, respectively. Consequently, the investigated graphite treatment proves to be an effective method for modifying the interfacial bonding and enhancing the comprehensive properties of aluminum. This treatment offers a simple and cost‐effective approach to improve the tribological and mechanical characteristics of aluminum matrix composites.

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Section: Characterization Of Mechanical Propertiesmentioning

confidence: 98%

A facile treatment of graphite as a reinforcement for Al‐based nanostructured composite

Bakhshizade,

Shokuhfar,

Zolriasatein

et al. 2024

Surface & Interface Analysis

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“…Machine learning is widely used in materials testing and design due to its powerful data processing and high predictive ability with low computational cost [17][18][19], and the technique has great potential for application in the field of graphene-reinforced aluminium matrix composites [20][21][22][23]. Chaudry et al [24] used machine learning techniques to assist in the design of high-performance aluminium alloys, and the results showed that the gradient-enhanced tree model can effectively predict the hardness of unexplored alloys.…”

Section: Introductionmentioning

confidence: 99%

Explanatory Machine Learning Accelerates the Design of Graphene-Reinforced Aluminium Matrix Composites with Superior Performance

Xue,

Huang,

et al. 2023

Metals

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Addressing the exceptional properties of aluminium alloy composites reinforced with graphene, this study presents an interpretable machine learning approach to aid in the rapid and efficient design of such materials. Initially, data on these composites were gathered and optimised in order to create a dataset of composition/process-property. Several machine learning algorithms were used to train various models. The SHAP method was used to interpret and select the best performing model, which happened to be the CatBoost model. The model achieved accurate predictions of hardness and tensile strength, with coefficients of determination of 0.9597 and 0.9882, respectively, and average relative errors of 6.02% and 5.01%, respectively. The results obtained from the SHAP method unveiled the correlation between the composition, process and properties of aluminium alloy composites reinforced with graphene. By comparing the predicted and experimental data in this study, all machine learning models exhibited prediction errors within 10%, confirming their ability to generalise. This study offers valuable insights and support for designing high-performance aluminium matrix composites reinforced with graphene and showcases the implementation of machine learning in materials science.

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“…79 Other factors include; their varying wettabilities 58 and thermal expansion coefficients 59 causing structural defects and the low stability of graphene dispersion within traditional, aqueous copper-based plating solutions inhibiting uniform distribution of the nanomaterials within the matrix. 38,80 By promoting good interfacial interactions between the components of CMMCs it is possible to improve its frictional performance. Therefore, improving the dispersibility and interaction parameters between graphene and copper is key to obtaining high tribological performance.…”

Section: Introductionmentioning

confidence: 99%

Tribology of Copper Metal-Matrix Composites Reinforced with Fluorinated Graphene Oxide Nanosheets: Implications for Solid Lubricants in Mechanical Switches

Savjani

Mercadillo

Hodgeman

et al. 2023

Preprint

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Applications of copper coatings on steel switching mechanisms are abundant owing to their high conductivities and corrosion resistance that they impart on the engineered assemblies. However, applications of these coatings on such moving parts are limited due to their poor tribological properties; tendencies to generate high friction and susceptibility to degradative wear. In this study, we have fabricated a fluorinated graphene oxide-copper metal matrix composite (FGO-CMMC) on an AISI52100 bearing steel substrate by a simple electrodeposition process in water. The FGO-CMMC coatings exhibited excellent lubrication performance under pin-on-disk (PoD) tribological sliding at 1N load, which reduced CoF by 63 and 69%, compared to the GO-CMMC and pure copper coatings that were also prepared. Furthermore, FGO-CMMC achieved low friction and low wear at higher sliding loads. The lubrication enhancement of the FGO-CMMCs is attributed to the tribochemical reaction of FGO with the AISI 52100 steel counterface initiated by sliding load. The formation of an asymmetric tribofilm structure on the sliding track is critical; the performance of the FGO/Cu tribofilm formed in the track is boosted by the continued fluorination of the counterface surface during PoD sliding, passivating the tribosystem from adhesion-driven breakdown. The FGO-CMMC and GO-CMMC coatings also provide increased corrosion protection reaching 94.2 and 91.6 % compared to the bare steel substrate, allowing for the preservation of the long-term low friction performance of the coating. Other influences include the improved interlaminar shear strength of the FGO-containing composite. The excellent lubrication performance of copper coatings by FGO incorporation makes the CMMC a promising solid lubricant candidate for use in mechanical engineering applications.

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Graphene-reinforced metal matrix composites: fabrication, properties, and challenges

Cited by 21 publications

References 231 publications

A facile treatment of graphite as a reinforcement for Al‐based nanostructured composite

A facile treatment of graphite as a reinforcement for Al‐based nanostructured composite

Explanatory Machine Learning Accelerates the Design of Graphene-Reinforced Aluminium Matrix Composites with Superior Performance

Tribology of Copper Metal-Matrix Composites Reinforced with Fluorinated Graphene Oxide Nanosheets: Implications for Solid Lubricants in Mechanical Switches

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