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Published September 13, 2018 | Supplemental Material
Journal Article Open

In Silico Optimization of Organic-Inorganic Hybrid Perovskites for Photocatalytic Hydrogen Evolution Reaction in Acidic Solution


We previously reported the atomistic reaction mechanism for the photocatalytic hydrogen evolution reaction (HER) on the CH_3NH_3PbI_3 organic–inorganic hybrid perovskites based on quantum mechanics calculations of the transition-state barriers, including several layers of explicit acidic solvent. Here, we extend these studies using in silico optimization to discover additional promising photocatalysts. We consider replacing (i) Pb with Sn, (ii) I with Br, and (iii) CH_3NH_3 cation with several organic cations, including NH_2(CH)NH_2 cation as the photocatalyst for HER. We compared the activation barriers and reaction energies for each case. In our previous studies, we found that both H atoms of the H_2 product are extracted from surface organic cations with protons from the solution migrating along Grotthuss water chains to replace the H of the organic cations. This two-step reaction mechanism involves formation of an intermediate lead hydride bond, with the lead atoms and the surface organic cations both playing essential roles. Among the perovskites investigated here, we predict that NH_2(CH)NH_2PbI_3 exhibits the best HER performance with a predicted 10-fold improvement in the reaction rate compared to CH_3NH_3PbI_3. We also suggest that the lead-free tin iodide perovskites might exhibit a rate comparable to that of lead iodide perovskites with the same organic cations. However, replacing iodine by bromine significantly increases the activation barrier. We find for these lead iodide perovskites, the increased proton affinity of the surface organic cations enhances the photocatalytic efficiency, with NH2(CH)NH2 the best case examined.

Additional Information

© 2018 American Chemical Society. Received: July 31, 2018; Published: August 4, 2018. This work was supported by the National Key Research and Development Program of China (Grants 2018YFB0703900, 2017YFA0204800 and 2017YFB0701600), the National Natural Science Foundation of China (51761145013, 21673149). This research was also supported by the Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993. The work was carried out at National Supercomputer Center in Tianjin, and the calculations were performed on TianHe-1 (A). This project is also supported by the Fund for Collaborative Innovation Center of Suzhou Nano Science & Technology, the Priority Academic Program Development of Jiangsu Higher Education Institutions. The authors declare no competing financial interest.

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