Solar thermal water splitting (STWS) involves using concentrated solar energy to drive a two step redox process. In the first step a metal oxide is reduced to produce oxygen. The second step involves exposure of the reduced metal oxide to steam, which reoxidizes the material and produces hydrogen. A successful STWS process relies on the discovery of redox materials which can be reduced at reasonable temperatures, have the driving force while in their reduced state to split water and which have reduction and oxidation kinetics that are sufficiently high so that many cycles can be run each day. The thermodynamics of reduction and oxidation depend on the formation energy of oxygen vacancies in these materials. The kinetics of the surface reactions during reduction and oxidation steps could be determined by either surface reactions or by bulk diffusion of oxygen vacancies. We will present our results on using quantum chemical and machine learned models to rapidly predict the thermodynamic and kinetic materials properties to computationally screen candidate materials for STWS.

Accelerated discovery of materials for solar thermal water splitting using computational chemistry and machine learning

255th National Meeting (2018)

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