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We present a highly efficient workflow for designing semiconductor structureswith specific physical properties, which can be utilized for a range ofapplications, including photocatalytic water splitting. Our algorithm generatescandidate structures composed of earth-abundant elements that exhibit optimallight-trapping, high efficiency in \ce{H2} and/or \ce{O2} production, andresistance to reduction and oxidation in aqueous media. To achieve this, we usean ionic translation model trained on the Inorganic Crystal Structure Database(ICSD) to predict over thirty thousand undiscovered semiconductor compositions.These predictions are then screened for redox stability under HydrogenEvolution Reaction (HER) or Oxygen Evolution Reaction (OER) conditions beforegenerating thermodynamically stable crystal structures and calculating accurateband gap values for the compounds. Our approach results in the identificationof dozens of promising semiconductor candidates with ideal properties forartificial photosynthesis, offering a significant advancement toward theconversion of sunlight into chemical fuels.

Transforming Materials Discovery for Artificial Photosynthesis: High-Throughput Screening of Earth-Abundant Semiconductors