摘要
Wepresent a method combining first-principles calculations and machine learning to predict the redox potentials of half-cell reactions on the absolute scale.By applying machine learning force fields for thermodynamic integration from the oxidized to the reduced state,we achieve efficient statistical sampling over a broad phase space.Furthermore,through thermodynamic integration from machine learning force fields to potentials of semi-local functionals,and from semi-local functionals to hybrid functionals usingΔ-machine learning,we refine the free energy with high precision step-by-step.
