Finite‐temperature properties of NbO2 from a deep‐learning interatomic potential

Abstract Using first‐principles‐based machine‐learning potential, molecular dynamics (MD) simulations are performed to investigate the micro‐mechanism in phase transition of NbO2. Treating the DFT results of the low‐ and intermediate‐temperature phases of NbO2 as training data in the deep‐learning m...

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Bibliographic Details
Main Authors: Xinhang Li, Yongqiang Wang, Tianyu Jiao, Zhaoxin Liu, Chuanle Yang, Ri He, Liang Si
Format: Article
Language:English
Published: Wiley-VCH 2025-06-01
Series:Materials Genome Engineering Advances
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Online Access:https://doi.org/10.1002/mgea.70011
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