AiiDA-TrainsPot introduces an automated workflow for training neural-network interatomic potentials via calibrated active learning on carbon allotropes and alloy phase transitions.
MD simulations explored tempera- tures ranging from 0 to 5000 K and pressures from−5 to 5 kbar
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AiiDA-TrainsPot: Towards automated training of neural-network interatomic potentials
AiiDA-TrainsPot introduces an automated workflow for training neural-network interatomic potentials via calibrated active learning on carbon allotropes and alloy phase transitions.