Geng Li

Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

A hybrid physics-informed machine learning (Hybrid PIML) framework for accelerated hardness prediction, integrating classical solid solution strengthening theory with a residual learning artificial neural network (ANN), which establishes a precise, physically consistent pathway for inverse material design under data-co...