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Title: High-throughput calculations of catalytic properties of bimetallic alloy surfaces

Abstract

A comprehensive database of chemical properties on a vast set of transition metal surfaces has the potential to accelerate the discovery of novel catalytic materials for energy and industrial applications. In this data descriptor, we present such an extensive study of chemisorption properties of important adsorbates - e.g., C, O, N, H, S, CH x, OH, NH, and SH - on 2,035 bimetallic alloy surfaces in 5 different stoichiometric ratios, i.e., 0%, 25%, 50%, 75%, and 100%. To our knowledge, it is the first systematic study to compile the adsorption properties of such a well-defined, large chemical space of catalytic interest. We propose that a collection of catalytic properties of this magnitude can assist with the development of machine learning enabled surrogate models in theoretical catalysis research to design robust catalysts with high activity for challenging chemical transformations. This database is made publicly available through the platform www.Catalysis-hub.org for easy retrieval of the data for further scientific analysis.

Authors:
 [1]; ORCiD logo [1];  [1];  [2]
  1. SLAC National Accelerator Lab., Menlo Park, CA (United States). SUNCAT Center for Interface Science and Catalysis; Stanford Univ., CA (United States). SUNCAT Center for Interface Science and Catalysis, Dept. of Chemical Engineering
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States). SUNCAT Center for Interface Science and Catalysis
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1532485
Grant/Contract Number:  
AC02-76SF00515
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Data
Additional Journal Information:
Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 2052-4463
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
96 KNOWLEDGE MANAGEMENT AND PRESERVATION; 36 MATERIALS SCIENCE; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Mamun, Osman, Winther, Kirsten T., Boes, Jacob R., and Bligaard, Thomas. High-throughput calculations of catalytic properties of bimetallic alloy surfaces. United States: N. p., 2019. Web. doi:10.1038/s41597-019-0080-z.
Mamun, Osman, Winther, Kirsten T., Boes, Jacob R., & Bligaard, Thomas. High-throughput calculations of catalytic properties of bimetallic alloy surfaces. United States. doi:10.1038/s41597-019-0080-z.
Mamun, Osman, Winther, Kirsten T., Boes, Jacob R., and Bligaard, Thomas. Tue . "High-throughput calculations of catalytic properties of bimetallic alloy surfaces". United States. doi:10.1038/s41597-019-0080-z. https://www.osti.gov/servlets/purl/1532485.
@article{osti_1532485,
title = {High-throughput calculations of catalytic properties of bimetallic alloy surfaces},
author = {Mamun, Osman and Winther, Kirsten T. and Boes, Jacob R. and Bligaard, Thomas},
abstractNote = {A comprehensive database of chemical properties on a vast set of transition metal surfaces has the potential to accelerate the discovery of novel catalytic materials for energy and industrial applications. In this data descriptor, we present such an extensive study of chemisorption properties of important adsorbates - e.g., C, O, N, H, S, CHx, OH, NH, and SH - on 2,035 bimetallic alloy surfaces in 5 different stoichiometric ratios, i.e., 0%, 25%, 50%, 75%, and 100%. To our knowledge, it is the first systematic study to compile the adsorption properties of such a well-defined, large chemical space of catalytic interest. We propose that a collection of catalytic properties of this magnitude can assist with the development of machine learning enabled surrogate models in theoretical catalysis research to design robust catalysts with high activity for challenging chemical transformations. This database is made publicly available through the platform www.Catalysis-hub.org for easy retrieval of the data for further scientific analysis.},
doi = {10.1038/s41597-019-0080-z},
journal = {Scientific Data},
number = 1,
volume = 6,
place = {United States},
year = {2019},
month = {5}
}

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