Randomized trial evaluates wear and friction in bi-directional carbon fiber composites, suggesting material performance enhancement with graphene.
In this work, epoxy nanographene composites containing bi-directional carbon fibers were evaluated for sliding wear and friction characteristics with respect to sliding distance and load at a constant sliding speed. The data reveal that the specific wear rate decreased with increasing sliding distance for all graphene containing samples. The wear rate decreased with increasing graphene concentration 0–0.8 wt.%, then increased slightly with further increases in nanographene content (1.2 wt.%). The coefficient of friction decreased with increasing graphene content up to 0.8 wt.%, but increased marginally at 1.2 wt.% graphene. Nanographene improved the mechanical properties of the epoxy resin and the wear mechanism appeared to be influenced by the fiber/resin interface. Wear testing typically involves many parameters, making it difficult to assess the individual effect of each parameter on the wear properties. In such cases, Machine Learning (ML) algorithms have provided an efficient tool to analyze material performance.
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Jagadeesh et al. (2026) studied this question.
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