Machine-learning potentials for structurally and chemically complex MAB phases: Strain hardening and ripplocation-mediated plasticity by Nikola Koutná, Shuyao Lin, Lars Hultman, Davide G. Sangiovanni, Paul H. Mayrhofer

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Elemental augmentation of machine learning interatomic potentials by Haibo Xue, Guanjian Cheng, Wan-Jian Yin

Subjects: “…Machine learning interatomic potentials…”
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Hydrogen Diffusion in Garnet: Insights From Atomistic Simulations by Xin Zhong, Felix Höfling, Timm John

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Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials by Julia H. Yang, Xinqiang Rao, Amanda Whai Shin Ooi

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Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations by Yaohuang Huang, Yi-Fan Hou, Pavlo O Dral

Subjects: “…machine learning interatomic potentials…”
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TiAlNb alloy interatomic potentials: comparing passive and active machine learning techniques with MTP and DeePMD by Anju Chandran, Archa Santhosh, Claudio Pistidda, Paul Jerabek, Roland C. Aydin, Roland C. Aydin, Christian J. Cyron, Christian J. Cyron

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Automated and Efficient Sampling of Chemical Reaction Space by Minhyeok Lee, Umit V. Ucak, Jinyoung Jeong, Islambek Ashyrmamatov, Juyong Lee, Eunji Sim

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Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys by Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey

Subjects: “…universal machine learning interatomic potential…”
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