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Highly efficient and transferable interatomic potentials for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.svg" display="inline" id="d1e1011"><mml:mi>α</mml:mi></mml:math>-iron and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.svg" display="inline" id="d1e1016"><mml:mi>α</mml:mi></mml:math>-iron/hydrogen binary systems using deep neural networks

Shihao Zhang, Fan-Shun Meng, Rong Fu, Shigenobu Ogata

2024Computational Materials Science15 citationsDOI

Topics & Concepts

HydrogenHydrogen embrittlementEmbrittlementMaterials scienceNucleationAtomic unitsMetallurgyChemistryPhysicsThermodynamicsQuantum mechanicsOrganic chemistryHydrogen embrittlement and corrosion behaviors in metalsNuclear Materials and PropertiesMaterial Properties and Failure Mechanisms
Highly efficient and transferable interatomic potentials for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.svg" display="inline" id="d1e1011"><mml:mi>α</mml:mi></mml:math>-iron and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.svg" display="inline" id="d1e1016"><mml:mi>α</mml:mi></mml:math>-iron/hydrogen binary systems using deep neural networks | Litcius