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High throughput theoretical methods are increasingly used to identify promising photocatalytic materials for hydrogen generation from water as a clean source of energy. While most promising water splitting candidates require co-catalyst loading and electrical biasing, computational costs to predict them apriori becomes large. It is therefore important to identify bare, bias-free semiconductor photocatalysts with small initial hydrogen production rates, often in the range of tens of nano-mols per hour, as these can become highly efficient with further co-catalyst loading and biasing. Here we report a sensitive hydrogen detection system suitable for screening new photocatalysts. The hydrogen evolution rate of the prototypical rutile TiO2 loaded with 0.3 % wt Pt is detected to be 78.0+-0.8 {\mu}mol/h/0.04g, comparable with the rates reported in the literature. In contrast, sensitivity to an ultralow evolution rate of 11.4+-0.3 nmol/h/0.04g is demonstrated for bare polycrystalline TiO2 without electrical bias. Two candidate photocatalysts, ZnFe2O4 (18.1+-0.2 nmol/h/0.04g) and Ca2PbO4 (35.6+-0.5 nmol/h/0.04g), without electrical bias or co-catalyst loading, are demonstrated to be potentially superior to bare TiO2. This work expands the techniques available for sensitive detection of photocatalytic processes towards much faster screening of new candidate photocatalytic materials in their bare state

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.