Molecular Simulations and Machine Learning for Computational Design of Materials with Fast Oxygen Kinetics

Rapid transport of oxygen across and through materials is at the heart of technologies from solid oxide fuel cells to gas separation membranes to memristors. In recent years, developments in computational approaches, including accurate high-throughput molecular simulations and data-centric descriptor and machine learning methods, have emerged as powerful tools in the search for the next generation of fast oxygen materials.