Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

TL;DR

This paper presents a combined computational and experimental approach to identify effective photocatalysts for solar hydrogen production, achieving a high validation rate and demonstrating the utility of a cost-effective density functional theory method.

Contribution

It introduces a systematic screening protocol integrating theory and experiment, significantly improving the discovery process of photocatalysts for water splitting.

Findings

Six compounds confirmed to generate hydrogen with favorable properties

The protocol reduced the candidate pool from over 70,000 to 11 synthesized materials

The Hubbard-corrected DFT method accurately predicts band gaps at lower computational cost

Abstract

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed (Pinaud et al., Energy Environ. Sci., 2013, 6, 1983). While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Starting with 70,150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.