Optimized deep learning regression assisted wear rate analysis of Cu–AlCoCrCuFe HEA composite

• Published in: AIP advances Vol. 14; no. 5; pp. 055002 - 055002-8
• Main Authors: S., Seenivasan, P., Satishkumar, Prakash K., Soorya, Giri, Jayant, Al-Lohedan, Hamad A., Sathish, T.
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01.05.2024; AIP Publishing LLC
• Subjects: Coefficient of friction; Composite materials; Copper; Correlation analysis; Feature extraction; High entropy alloys; Machine learning; Neural networks; Parameters; Sliding; Wear rate; Wear tests

At present, composites have brought materials to a new era with superior characteristics. The proper selection of materials with optimal processing conditions is one of the prime factors in determining the efficiency of composites. This article introduces a new composite by fabricating a copper matr...