The Power of Entropy: Dynamically Disordered Solids as Advanced Energy Materials

The project aims to develop and apply a theory based on quantum mechanics and artificial intelligence, which will revolutionize the search for dynamically disordered solid materials (DDSM) for advanced green energy applications.

DDSM are a class of materials that exhibit a time-averaged long-range crystalline order within a certain temperature range, but with some atomic species lacking equilibrium crystallographic positions. An example is superionic conductors, where some of the ions diffuse through the solid in a “liquid-like” fashion.

The physical properties of these materials are profoundly impacted by entropy.

DDSM hold great promise for various green energy applications, such as fuel cells and solid-state batteries, thermoelectrics, photovoltaics, and barocalorics. However, their stability is often limited to a narrow temperature range. To improve it by, e.g., alloying the theoretical guidance of experiments is urged.

Standard techniques that assume the existence of well-defined equilibrium atomic positions fail.

We have invented a method overcoming these difficulties that we will combine with a new type of machine learning, which will allow us to perform probably the fastest possible high-throughput search for best DDSM.

Particular DDSM that will be studied are relevant for fuel cells (bismuth oxide), solid-state batteries (lithium hydroxide chloride), and solar cells (various perovskite materials).