Dynamic Workflows for Routine Materials Discovery in Surface Science

Tran, Kevin; Palizhati, Aini; Back, Seoin; Ulissi, Zachary W.

doi:10.1021/acs.jcim.8b00386

Dynamic Workflows for Routine Materials Discovery in Surface Science

Journal Article · Mon Nov 19 00:00:00 EST 2018 · Journal of Chemical Information and Modeling

DOI:https://doi.org/10.1021/acs.jcim.8b00386· OSTI ID:1543623

Tran, Kevin ^[1]; Palizhati, Aini ^[1]; Back, Seoin ^[1]; ^[1]

Carnegie Mellon Univ., Pittsburgh, PA (United States). Dept. of Chemical Engineering

The rising application of informatics and data science tools for studying inorganic crystals and small molecules has revolutionized approaches to materials discovery and driven the development of accurate machine learning structure/property relationships. In this paper, we discuss how informatics tools can accelerate research, and we present various combinations of workflows, databases, and surrogate models in the literature. This paradigm has been slower to infiltrate the catalysis community due to larger configuration spaces, difficulty in describing necessary calculations, and thermodynamic/kinetic quantities that require many interdependent calculations. We present our own informatics tool that uses dynamic dependency graphs to share, organize, and schedule calculations to enable new, flexible research workflows in surface science. This approach is illustrated for the large-scale screening of intermetallic surfaces for electrochemical catalyst activity. Similar approaches will be important to bring the benefits of informatics and data science to surface science research. Lastly, we provide our perspective on when to use these tools and considerations when creating them.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Univ. of California, Oakland, CA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1543623

Journal Information:: Journal of Chemical Information and Modeling, Journal Name: Journal of Chemical Information and Modeling Journal Issue: 12 Vol. 58; ISSN 1549-9596

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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