Computational Design Principles of Two-Center First-Row Transition Metal Oxide Oxygen Evolution Catalysts

Computational screens for oxygen evolution reaction (OER) catalysts based on Sabatier analysis have seen great success in recent years; however, the concept of using chemical descriptors to form a reaction coordinate has not been put under scrutiny for complex systems. In this paper, we examine critically the use of chemical descriptors as a method for conducting catalytic screens. Applying density functional theory calculations to a two-center metal oxide model system, we show that the Sabatier analysis is quite successful for predicting activities and capturing the chemical periodic trends expected for the first-row transition metal series, independent of the proposed mechanism. We then extend this analysis to heterodimer metallic systemsmetal oxide catalysts with two different catalytically active metal centersand find signs that the Sabatier analysis may not hold for these more complex systems. By performing a principal component analysis on the computed redox potentials, we show (1) that a single chemical descriptor inadequately describes heterodimer overpotentials and (2) mixed-metal overpotentials cannot be predicted using only pure-metal redox potentials. We believe that the analysis presented in this article shows a need to move beyond the simple chemical descriptor picture when studying more complex mixed metal oxide OER catalysts

What Can Density Functional Theory Tell Us about Artificial Catalytic Water Splitting?

Water splitting by artificial catalysts is a critical process in the production of hydrogen gas as an alternative fuel. In this paper, we examine the essential role of theoretical calculations, with particular focus on density functional theory (DFT), in understanding the water-splitting reaction on these catalysts. First, we present an overview of DFT thermochemical calculations on water-splitting catalysts, addressing how these calculations are adapted to condensed phases and room temperature. We show how DFT-derived chemical descriptors of reactivity can be surprisingly good estimators for reactive trends in water-splitting catalysts. Using this concept, we recover trends for bulk catalysts using simple model complexes for at least the first-row transition-metal oxides. Then, using the CoPi cobalt oxide catalyst as a case study, we examine the usefulness of simulation for predicting the kinetics of water splitting. We demonstrate that the appropriate treatment of solvent effects is critical for computing accurate redox potentials with DFT, which, in turn, determine the rate-limiting steps and electrochemical overpotentials. Finally, we examine the ability of DFT to predict mechanism, using ruthenium complexes as a focal point for discussion. Our discussion is intended to provide an overview of the current strengths and weaknesses of the state-of-the-art DFT methodologies for condensed-phase molecular simulation involving transition metals and also to guide future experiments and computations toward the understanding and development of novel water-splitting catalysts