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Issue 5, 2015
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Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: computing infrastructure and collective properties

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Abstract

A volunteer computing approach is presented for the purpose of screening a large number of molecular structures with respect to their suitability as new battery electrolyte solvents. Collective properties like melting, boiling and flash points are evaluated using COSMOtherm and quantitative structure–property relationship (QSPR) based methods, while electronic structure theory methods are used for the computation of electrochemical stability window estimators. Two application examples are presented: first, the results of a previous large-scale screening test (PCCP, 2014, 16, 7919) are re-evaluated with respect to the mentioned collective properties. As a second application example, all reasonable nitrile solvents up to 12 heavy atoms are generated and used to illustrate a suitable filter protocol for picking Pareto-optimal candidates.

Graphical abstract: Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: computing infrastructure and collective properties

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Publication details

The article was received on 25 Sep 2014, accepted on 09 Dec 2014 and first published on 10 Dec 2014


Article type: Paper
DOI: 10.1039/C4CP04338C
Citation: Phys. Chem. Chem. Phys., 2015,17, 3394-3401
  • Open access: Creative Commons BY-NC license
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    Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: computing infrastructure and collective properties

    T. Husch, N. D. Yilmazer, A. Balducci and M. Korth, Phys. Chem. Chem. Phys., 2015, 17, 3394
    DOI: 10.1039/C4CP04338C

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