A paper “Facilitating ab initio configurational sampling of multicomponent solids using an on-lattice neural network model and active learning” related to abICS has been published in The Journal of Chemical Physics. This paper discusses structural stability using aenet, a software that uses neural networks to calculate interatomic potentials. This functionality has been implemented in abICS ver. 2.0 and is already available.
Report information：”Facilitating ab initio configurational sampling of multicomponent solids using an on-lattice neural network model and active learning” Shusuke Kasamatsu, Yuichi Motoyama, Kazuyoshi Yoshimi, Ushio Matsumoto, Akihide Kuwabara, and Takafumi Ogawa, J. Chem. Phys. 157, 104114 (2022).
DOI: https://doi.org/10.1063/5.0096645