abICS

abICS is a software framework for training a machine learning model to reproduce first-principles calculations 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, neural network potentials implemented in aenet can be used as machine learning models. abICS also provides interfaces for Quantum Espresso, VASP, aenet, and OpenMX.