Calculation Technique of the Equilibrium Distance in Two-Particle Interatomic Potential Based on the Analysis of Solid Body Lattice Energy by A.A. Gaisha

Subjects: “…Interatomic potential…”
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Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data by Bowen Han, Yongqiang Cheng

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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

Subjects: “…machine learning interatomic potential…”
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LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields by Joshua A Vita, Amit Samanta, Fei Zhou, Vincenzo Lordi

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Technique for the Determination of the Elastic Stiffness Coefficient of Interatomic Connection Based on the Experimental Weight-Loading Curve by K.D. Evfimko, A.A. Gaisha, A.A. Mochalov

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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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Technique of Heat Capacity Calculation of Solid Body Lattice Using Interatomic Potential by A.A. Gaisha

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Finite‐temperature properties of NbO2 from a deep‐learning interatomic potential by Xinhang Li, Yongqiang Wang, Tianyu Jiao, Zhaoxin Liu, Chuanle Yang, Ri He, Liang Si

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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

Subjects: “…Machine-learning interatomic potentials…”
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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

Subjects: “…machine learning interatomic potentials…”
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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

Subjects: “…machine learning interatomic potentials…”
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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

Subjects: “…machine-learning interatomic potentials…”
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