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  • 标题:Predictions of Physicochemical Properties of Ionic Liquids with DFT
  • 本地全文:下载
  • 作者:Karl Karu ; Anton Ruzanov ; Heigo Ers
  • 期刊名称:Computation
  • 电子版ISSN:2079-3197
  • 出版年度:2016
  • 卷号:4
  • 期号:3
  • 页码:25-38
  • DOI:10.3390/computation4030025
  • 出版社:MDPI Publishing
  • 摘要:Nowadays, density functional theory (DFT)-based high-throughput computational approach is becoming more efficient and, thus, attractive for finding advanced materials for electrochemical applications. In this work, we illustrate how theoretical models, computational methods, and informatics techniques can be put together to form a simple DFT-based throughput computational workflow for predicting physicochemical properties of room-temperature ionic liquids. The developed workflow has been used for screening a set of 48 ionic pairs and for analyzing the gathered data. The predicted relative electrochemical stabilities, ionic charges and dynamic properties of the investigated ionic liquids are discussed in the light of their potential practical applications.
  • 关键词:DFT; ionic liquids; high-throughput computation; electrochemical window; partial charge transfer; activation energy; viscosity DFT ; ionic liquids ; high-throughput computation ; electrochemical window ; partial charge transfer ; activation energy ; viscosity
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