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  • 标题:The Ionic Liquid Property Explorer: An Extensive Library of Task-Specific Solvents
  • 本地全文:下载
  • 作者:Vishwesh Venkatraman ; Sigvart Evjen ; Kallidanthiyil Chellappan Lethesh
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2019
  • 卷号:4
  • 期号:2
  • 页码:88-99
  • DOI:10.3390/data4020088
  • 出版社:MDPI Publishing
  • 摘要:Ionic liquids have a broad spectrum of applications ranging from gas separation to sensors and pharmaceuticals. Rational selection of the constituent ions is key to achieving tailor-made materials with functional properties. To facilitate the discovery of new ionic liquids for sustainable applications, we have created a virtual library of over 8 million synthetically feasible ionic liquids. Each structure has been evaluated for their-task suitability using data-driven statistical models calculated for 12 highly relevant properties: melting point, thermal decomposition, glass transition, heat capacity, viscosity, density, cytotoxicity, CO 2 solubility, surface tension, and electrical and thermal conductivity. For comparison, values of six properties computed using quantum chemistry based equilibrium thermodynamics COSMO-RS methods are also provided. We believe the data set will be useful for future efforts directed towards targeted synthesis and optimization.
  • 关键词:ionic liquids; machine learning; database; properties; combinatorial screening ionic liquids ; machine learning ; database ; properties ; combinatorial screening
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