气候变化领域集成服务门户(CCPortal): Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

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DOI	10.1039/d0ee02984j
	Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen
	Xiong Y.; Campbell Q.T.; Fanghanel J.; Badding C.K.; Wang H.; Kirchner-Hall N.E.; Theibault M.J.; Timrov I.; Mondschein J.S.; Seth K.; Katz R.; Villarino A.M.; Pamuk B.; Penrod M.E.; Khan M.M.; Rivera T.; Smith N.C.; Quintana X.; Orbe P.; Fennie C.J.; Asem-Hiablie S.; Young J.L.; Deutsch T.G.; Cococcioni M.; Gopalan V.; Abruña H.D.; Schaak R.E.; Dabo I.
发表日期	2021
ISSN	17545692
起始页码	2335
结束页码	2348
卷号	14 期号:4
英文摘要	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. This journal is © The Royal Society of Chemistry.
英文关键词	Computation theory; Conversion efficiency; Density functional theory; Energy gap; Fossil fuels; Hydrogen fuels; Density functional theory methods; Environmental consequences; Experimental validations; First-principles study; Production of hydrogen; Screening procedures; Single-phase materials; Solar-hydrogen generation; Hydrogen production; accuracy assessment; efficiency measurement; hydrogen; optimization; solar power
语种	英语
来源期刊	Energy & Environmental Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/190717
作者单位	Department of Materials Science and Engineering, Materials Research Institute, Pennsylvania State University, University Park, PA, United States; Sandia National Laboratories, Albuquerque, NM, United States; Department of Chemistry, Materials Research Institute, Pennsylvania State University, University Park, PA, United States; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States; Theory and Simulation of Materials (THEOS), National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland; School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United States; Department of Materials Science and Engineering, Northwestern University, Evanston, IL, United States; Institutes of Energy and the Environment, Pennsylvania State University, University Park, PA, United States; National Renewable Energy Laboratory, Golden, CO, United States; Department of Physics, Unive...
推荐引用方式 GB/T 7714	Xiong Y.,Campbell Q.T.,Fanghanel J.,et al. Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen[J],2021,14(4).
APA	Xiong Y..,Campbell Q.T..,Fanghanel J..,Badding C.K..,Wang H..,...&Dabo I..(2021).Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen.Energy & Environmental Science,14(4).
MLA	Xiong Y.,et al."Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen".Energy & Environmental Science 14.4(2021).