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cond-mat.mtrl-sci2025
Bridging Theory and Experiment in Materials Discovery: Machine-Learning-Assisted Prediction of Synthesizable Structures
Yu Xin, Peng Liu, Zhuohang Xie +6
Even though thermodynamic energy-based crystal structure prediction (CSP) has revolutionized materials discovery, the energy-driven CSP approaches often struggle to identify experi…
cond-mat.mtrl-sci2025
Self-Optimizing Machine Learning Potential Assisted Automated Workflow for Highly Efficient Complex Systems Material Design
Jiaxiang Li, Junwei Feng, Jie Luo +9
Machine learning interatomic potentials have revolutionized complex materials design by enabling rapid exploration of material configurational spaces via crystal structure predicti…