English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The production of hydrogen fuels, via water splitting, is of practicalrelevance for meeting global energy needs and mitigating the environmentalconsequences of fossil-fuel-based transportation. Water photoelectrolysis hasbeen proposed as a viable approach for generating hydrogen, provided thatstable and inexpensive photocatalysts with conversion efficiencies over 10% canbe discovered, synthesized at scale, and successfully deployed (Pinaud et al.,Energy Environ. Sci., 2013, 6, 1983). While a number of first-principlesstudies have focused on the data-driven discovery of photocatalysts, in theabsence of systematic experimental validation, the success rate of thesepredictions may be limited. We address this problem by developing a screeningprocedure with co-validation between experiment and theory to expedite thesynthesis, characterization, and testing of the computationally predicted, mostdesirable materials. Starting with 70,150 compounds in the Materials Projectdatabase, the proposed protocol yielded 71 candidate photocatalysts, 11 ofwhich were synthesized as single-phase materials. Experiments confirmedhydrogen generation and favorable band alignment for 6 of the 11 compounds,with the most promising ones belonging to the families of alkali andalkaline-earth indates and orthoplumbates. This study shows the accuracy of anonempirical, Hubbard-corrected density-functional theory method to predictband gaps and band offsets at a fraction of the computational cost of hybridfunctionals, and outlines an effective strategy to identify photocatalysts forsolar hydrogen generation.

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