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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Corrigendum: Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea.

© 2018 Nature Publishing Group. All rights reserved. In the version of this article initially published, the author A. Murat Eren was listed as A.M. Eren. The corresponding affiliation was given as the Knapp Center for Biomedical Discovery, rather than Department of Medicine, University of Chicago, Chicago, Illinois, USA, and Marine Biological Laboratory, Woods Hole, Massachusetts, USA. The errors have been corrected in the HTML and PDF versions of the article as of 29 November 2017. In the version of this article initially published, the following acknowledgment was omitted: A.L. was supported by the Russian Science Foundation (grant number 14-50-00069). The error has been corrected in the HTML and PDF versions of the article as of 7 December 2017.

Bowers, Robert M↗
DOE OSTI2015

The Electrolyte Genome project: A big data approach in battery materials discovery

We present a high-throughput infrastructure for the automated calculation of molecular properties with a focus on battery electrolytes. The infrastructure is largely open-source and handles both practical aspects (input file generation, output file parsing, and information management) as well as more complex problems (structure matching, salt complex generation, and failure recovery). Using this infrastructure, we have computed the ionization potential (IP) and electron affinities (EA) of 4830 molecules relevant to battery electrolytes (encompassing almost 55,000 quantum mechanics calculations) at the B3LYP/6-31+G(*) level. We describe automated workflows for computing redox potential, dissociation constant, and salt-molecule binding complex structure generation. We present routines for automatic recovery from calculation errors, which brings the failure rate from 9.2% to 0.8% for the QChem DFT code. Automated algorithms to check duplication between two arbitrary molecules and structures are described. We present benchmark data on basis sets and functionals on the G2-97 test set; one finding is that a IP/EA calculation method that combines PBE geometry optimization and B3LYP energy evaluation requires less computational cost and yields nearly identical results as compared to a full B3LYP calculation, and could be suitable for the calculation of large molecules. Our data indicates that among the 8 functionals tested, XYGJ-OS and B3LYP are the two best functionals to predict IP/EA with an RMSE of 0.12 and 0.27 eV, respectively. Application of our automated workflow to a large set of quinoxaline derivative molecules shows that functional group effect and substitution position effect can be separated for IP/EA of quinoxaline derivatives, and the most sensitive position is different for IP and EA. Published by Elsevier B.V

Battery↗