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Quan Zhang

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#machine learning Preprint Oct 2026

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their activation barriers. Discovering the associated saddle points is a major computational bottleneck: multiple rearrangements may originate from one metastable state, while...

Yu-Cheng Zhao, Quan Zhang, Shao-Xiang Qin et al. · 0 citations

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