(351b) A High-Throughput Computational Screening Approach for Solar Fuels Photoelectrocatalysis | AIChE

(351b) A High-Throughput Computational Screening Approach for Solar Fuels Photoelectrocatalysis

Authors 

Persson, K., Lawrence Berkeley Lab
In recent years, theoretical overpotential has become increasingly popular as a metric for characterizing the suitability of oxygen evolution electrocatalysts using density functional theory (DFT). In addition, DFT has become an invaluable tool for characterizing photoabsorbing materials in a number of high-throughput screening studies aimed at designing materials for solar fuels production from stability and bandstructure criteria. In this work, we present an approach which integrates calculations of theoretical overpotential with those of band-gap and band-edge positions on mixed metal oxides. Given that the prospect of discovering lone materials fulfilling the criteria of stability, catalytic activity, and photoabsorption efficiency, we also report on how materials with suitable surface chemistry may be more effectively paired with suitable photoabsorbing substrates using interfacial matching. Lastly, we benchmark our approach comparing potential combined metrics with experimentally measured photoelectrocatalytic activity.