journal article·2021-08

Remarkable anisotropic wear resistance with 100-fold discrepancy in a copper matrix laminated composite with only 0.2 vol% graphene

Guangyuan Lin, Yifei Peng, Yusen Li, Hanzheng Liang, Zhilei Dong, Yihu Zhou, Zhenming Yue, Jie Zhang, Ding-Bang Xiong, Di Zhang

Acta Materialia· Volume 215
Publisher page

Abstract

Abstract Graphene has attracted intensive attentions as a promising emerging lubricant and additive in metal matrix composites for tribological applications. Graphene itself has strong anisotropic physical and mechanical properties, but how its orientation in metal matrix influences the friction and wear properties of the composite remains unexplored. Herein, by successfully fabricating a graphene/copper matrix laminated composite, the effect of graphene orientation on the friction and wear properties of the composite is systematically investigated by both experimental and finite element simulation. The friction test results show that, with only ~0.2 vol% graphene, the maximum anisotropy ratio of wear resistance reaches a level as high as 100-fold in the laminated composite. Mechanism analyses indicates that the wear mechanisms of the three different sliding directions investigated with respect to graphene orientation are decided by a competition between graphene strengthening on Cu matrix, lubricating effect of graphene and interface delamination. The lowest coefficient of friction (~77% of pure Cu) and also the highest wear resistance (10 time higher than pure Cu) are recorded as sliding on the cross-sectional surface with a direction vertical to graphene edge, because of the synergic effect of strengthening and lubricating effect of graphene; while interface delamination results in the lowest wear resistance (about one tenth of pure Cu) as sliding on the in-plane surface.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Aluminum Alloys Composites Properties · MXene and MAX Phase Materials · Tribology and Wear Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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