MATEC Web of Conferences (Jan 2022)

Study of quantitative structure-property relationship for density of ionic liquids based on Monte Carlo optimization

  • Jia Xingang,
  • Wang Wenzhen,
  • Yang Bo,
  • Du Chunbao

DOI
https://doi.org/10.1051/matecconf/202235801011
Journal volume & issue
Vol. 358
p. 01011

Abstract

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Ionic liquids (ILs) have attracted increasing interests and applications due to its unique physiochemical properties. Density is a vital physical property of ILs. In this work, a comprehensive collection of density data is conducted on 184 variable ILs. The study of quantitative structure-property relationship (QSPR) is carried out for the selected density data of ILs using simplified molecular input line entry specification (SMILES) as the representation of the molecular structure of ILs by means of CORAL software. QSPR relationships were constructed with the balance of correlations (BC) and the classic scheme. Results from three random splits displayed desirable models for predicting the external test set with the correlation coefficient (R2) and cross validated correlation coefficient (Q2) in ranges of 0.8234–0.9770 and 0.7599–0.9745, respectively. The best predictions obtained by the balance of correlations along with the global SMILES descriptors are included in the modeling process. The average statistical characteristics of the external test set are the following: n =36, R2 =0.9770, Q2= 0.9745, standard error of estimation (s)=0.023, mean absolute error (MAE) =0.018 and Fischer F-ratio (F)=1443