Quantitative structure—property relationship for thermal decomposition temperature of ionic liquids

Farhad Gharagheizi, Mehdi Sattari, Poorandokht Ilani-Kashkouli, Amir H. Mohammadi, Deresh Ramjugernath, Dominique Richon

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In this study, a wide literature survey has been conducted to gather an extensive set of thermal decomposition temperature (Td) data for ionic liquids (ILs). A data set consisting of Td data for 586 ILs was collated from 71 different literature sources. Using this data set, a reliable quantitative structure-property relationship has been developed. In order to consider the effects of the anion and cation on the Td of ILs, both anion-based and cation-based molecular descriptors were considered. Finally, a genetic function approximation method was used which selected 6 molecular descriptors for anions, and 6 molecular descriptors for cations to develop the model. The predictive capability of the 12-parameter model was evaluated using several validation techniques. Its applicability domain is discussed. The proposed model produces an acceptable average relative deviation of less than 5.2% taking into consideration all 586 experimental data values.
Original languageEnglish
JournalChemical Engineering Science
Volume84
Pages (from-to)557-563
ISSN0009-2509
DOIs
Publication statusPublished - 2012

Keywords

  • Thermal decomposition temperature
  • QSPR model
  • Ionic liquids
  • Validation techniques
  • Representation/Prediction
  • Database

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