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Robust and synthesizable photocatalysts for CO_2 reduction: a data-driven materials discovery

Singh, Arunima K. and Montoya, Joseph H. and Gregoire, John M. and Persson, Kristin A. (2019) Robust and synthesizable photocatalysts for CO_2 reduction: a data-driven materials discovery. Nature Communications, 10 . Art. No. 443. ISSN 2041-1723. PMCID PMC6347635. http://resolver.caltech.edu/CaltechAUTHORS:20190129-080508688

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Abstract

The photocatalytic conversion of the greenhouse gas CO_2 to chemical fuels such as hydrocarbons and alcohols continues to be a promising technology for renewable generation of energy. Major advancements have been made in improving the efficiencies and product selectiveness of currently known CO_2 reduction electrocatalysts, nonetheless, materials discovery is needed to enable economically viable, industrial-scale CO_2 reduction. We report here the largest CO_2 photocathode search to date, starting with 68860 candidate materials, using a rational first-principles computation-based screening strategy to evaluate synthesizability, corrosion resistance, visible-light absorption, and compatibility of the electronic structure with fuel synthesis. The results confirm the observation of the literature that few materials meet the stringent CO_2 photocathode requirements, with only 52 materials meeting all requirements. The results are well validated with respect to the literature, with 9 of these materials having been studied for CO_2 reduction, and the remaining 43 materials are discoveries from our pipeline that merit further investigation.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1038/s41467-019-08356-1DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347635PubMed CentralArticle
ORCID:
AuthorORCID
Singh, Arunima K.0000-0002-7212-6310
Montoya, Joseph H.0000-0001-5760-2860
Gregoire, John M.0000-0002-2863-5265
Persson, Kristin A.0000-0003-2495-5509
Alternate Title:Robust and synthesizable photocatalysts for CO2 reduction: a data-driven materials discovery
Additional Information:© 2019 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received 17 July 2018; Accepted 03 January 2019; Published 25 January 2019. This work was primarily funded by the Joint Center for Artificial Photosynthesis, a US Department of Energy (DOE) Energy Innovation Hub, supported through the Office of Science of the DOE under Award Number DE-SC0004993. Computational work was additionally supported by the Materials Project Program (Grant No. KC23MP) through the DOE Office of Basic Energy Sciences, Materials Sciences, and Engineering Division, under Contract DE-AC02-05CH11231. Computational resources were provided by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the DOE under Contract No. DE-AC02-05CH11231. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. This work used XSEDE’s Stampede2 at the Texas Advanced Computing Center through allocation #TG-DMR150006. Data availability: The data that support the results within this paper and other findings of this study are available at https://materialsproject.org/#search/materials, the supplementary information and from the corresponding author upon reasonable request. Author Contributions: A.K.S. and K.A.P. conceptualized the project. A.K.S. developed the methodology, performed the simulations, conducted the data analysis reported in this paper and wrote the original draft. J.H.M. helped automate electronic structure simulations. All authors participated in design of the tiered screening pipeline and manuscript editing. K.A.P. and J.M.G. acquired funding for the work and supervised the research reported in the paper. The authors declare no competing interests.
Group:JCAP
Funders:
Funding AgencyGrant Number
Joint Center for Artificial Photosynthesis (JCAP)UNSPECIFIED
Department of Energy (DOE)DE-SC0004993
Department of Energy (DOE)KC23MP
Department of Energy (DOE)DE-AC02-05CH11231
NSFACI-1548562
NSFTG-DMR150006
Subject Keywords:Artificial photosynthesis; Computational chemistry; Corrosion; Photocatalysis
PubMed Central ID:PMC6347635
Record Number:CaltechAUTHORS:20190129-080508688
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190129-080508688
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92507
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:29 Jan 2019 16:13
Last Modified:29 Jan 2019 16:13

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