Augmenting zero-Kelvin quantum mechanics with machine learning for the prediction of chemical reactions at high temperatures

Abstract

Computational material design often does not account for temperature effects. The present manuscript combines quantum-mechanics based calculations with a machine-learned correction to establish a unified thermodynamics framework for accurate prediction of high temperature reaction free energies in oxides.