MAST
Metallic Amorphous Structures Toolkit for generating Special Glass Structures.
Computational materials science · Shenyang, China
Siya Zhu, Ph.D.
Project Researcher · Institute of Metal Research, Chinese Academy of Sciences
I develop atomistic, thermodynamic, and machine-learning methods for compositionally complex materials, connecting atomic configurations with finite-temperature phase stability, defects, and mechanical behavior.
Profile
Modeling how complex alloys choose their structures and phases.
My research connects first-principles calculations, statistical sampling, CALPHAD, and machine-learning interatomic potentials. I also build open-source tools that turn these methods into reproducible workflows for phase diagrams, metallic glasses, and defect-rich alloys.
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Now recruiting
Postdoctoral positions at IMR, CAS
Our group in the Interdisciplinary Science Research Division is seeking researchers interested in alloy thermodynamics, machine learning, and computational materials science. Annual compensation starts from RMB 300,000.
Read the full announcementSelected software