Physics-guided Inverse Design of Co-based Superalloys Using Machine Learning and Multi-objective Optimization for Enhanced γ' Solvus Temperature
Materials
Proposes a physics-informed ML framework combined with multi-objective optimization for inverse design of Co-based superalloy compositions to enhance γ' solvus temperature while considering alloy density.
New See LICENSE file superalloyinverse designmulti-objective optimization