Enhancing wear resistance of E-glass/Copper composites: a machine learning approach to graphene filler optimization

Abstract Wear resistance is a critical requirement for materials used in automotive, aerospace, and electronic components operating under severe mechanical and thermal conditions. Although copper is extensively utilized due to its superior electrical and thermal conductivity, its poor wear resistanc...

Full description

Bibliographic Details

Published in:	Journal of Materials Science: Materials in Engineering
Main Authors:	D. Aravinda, H. K. Shivanand, N. Santhosh, Ahmed Adnan Hadi, N. Channa Keshava Naik, Md Amir Khan, Addisu Frinjo Emma
Format:	Article
Language:	English
Published:	SpringerOpen 2026-04-01
Subjects:	Wear resistance E-glass Copper Composites Machine learning Optimization
Online Access:	https://doi.org/10.1186/s40712-026-00456-3