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This content will become publicly available on February 21, 2018

Title: Screening for High Conductivity/Low Viscosity Ionic Liquids Using Product Descriptors

We seek to optimize Ionic liquids (ILs) for application to redox flow batteries. As part of this effort, we have developed a computational method for suggesting ILs with high conductivity and low viscosity. Since ILs consist of cation-anion pairs, we consider a method for treating ILs as pairs using product descriptors for QSPRs, a concept borrowed from the prediction of protein-protein interactions in bioinformatics. We demonstrate the method by predicting electrical conductivity, viscosity, and melting point on a dataset taken from the ILThermo database on June 18th, 2014. The dataset consists of 4,329 measurements taken from 165 ILs made up of 72 cations and 34 anions. In conclusion, we benchmark our QSPRs on the known values in the dataset then extend our predictions to screen all 2,448 possible cation-anion pairs in the dataset.
Authors:
 [1] ;  [1] ;  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Report Number(s):
SAND-2016-3631J
Journal ID: ISSN 1868-1743; 638469
Grant/Contract Number:
AC04-94AL85000
Type:
Accepted Manuscript
Journal Name:
Molecular Informatics
Additional Journal Information:
Journal Volume: 36; Journal Issue: 7; Journal ID: ISSN 1868-1743
Publisher:
Wiley
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
OSTI Identifier:
1375027