Entropy in materials design: Accelerated discovery of disordered solid electrolytes

Design of new materials is essential for the green transition of our society, but materials discovery is a slow process dominated by trial-and-error synthesis. Computational methods based on quantum chemistry and machine learning promise to accelerate materials discovery, but current methods neglect the effects of entropy, and therefore disorder and temperature, on the stability of materials. In this project, we will develop new methods to efficiently include entropic effects to enable computational design of disordered materials, and we will apply these methods to predict and experimentally verify new, disordered solid electrolytes with applications in next-generation batteries. The grant will fund two PhD students and one postdoc.