Issue 4, 2021

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

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.

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

Associated articles

Supplementary files

Article information

Article type
Paper
Submitted
16 Sep 2020
Accepted
10 Mas 2021
First published
11 Mas 2021

Energy Environ. Sci., 2021,14, 2335-2348

Author version available

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

Y. Xiong, Q. T. Campbell, J. Fanghanel, C. K. Badding, H. Wang, N. E. Kirchner-Hall, M. J. Theibault, I. Timrov, J. S. Mondschein, K. Seth, R. R. Katzbaer, A. M. Villarino, B. Pamuk, M. E. Penrod, M. M. Khan, T. Rivera, N. C. Smith, X. Quintana, P. Orbe, C. J. Fennie, S. Asem-Hiablie, J. L. Young, T. G. Deutsch, M. Cococcioni, V. Gopalan, H. D. Abruña, R. E. Schaak and I. Dabo, Energy Environ. Sci., 2021, 14, 2335 DOI: 10.1039/D0EE02984J

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements