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cond-mat.mtrl-sci2026
Symmetry- and Property-Aware Crystal Generation with Reinforcement Learning for Inverse Materials Design
Ting-Wei Hsu, Arun Bansil, Qimin Yan
The inverse design of crystalline materials ultimately seeks structures with desired physical properties. However, for many functional responses, a favorable numerical value is mea…
cond-mat.mtrl-sci2026
A Multi-Scale Machine Learning Framework for Coupled Chemical, Spin, and Structural Disorder in Alloys
Zhenyao Fang, Qimin Yan
Understanding the thermodynamic properties of disordered magnetic alloys requires a unified treatment of configurational (chemical, spin, etc.) and structural degrees of freedom, w…