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  • abICS

abICS

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Software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. It has been developed with an emphasis on multi-component solid-state systems such as metal and oxide alloys. At present, Quantum Espresso, VASP and OpenMX can be used as first-principles energy calculators, and aenet can be used to construct neural network potentials.

Understanding superionic conductivity in disordered systems using machine learning potential molecular dynamics and Monte Carlo sampling

Shusuke KASAMATSU

ISSP Activity Report 2021, p. 51-52

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