Optimising an artificial neural network for predicting the melting point of ionic liquids

Authors
  • K.R. Seddon
  • I. López-Martin
Publication date 10-09-2008
Journal Physical Chemistry Chemical Physics
Volume | Issue number 10 | 38
Pages (from-to) 5826-5831
Number of pages 6
Organisations
  • Faculty of Science (FNWI) - Van 't Hoff Institute for Molecular Sciences (HIMS)
Abstract

We present an optimised artificial neural network (ANN) model for predicting the melting point of a group of 97 imidazolium salts with varied anions. Each cation and anion in the model is described using molecular descriptors. Our model has a mean prediction error of 1.30%, a regression coefficient of 0.99 and a mean P-value of 0.92. The ANN’s prediction performance depends mainly on the anion size. In particular, the prediction error decreases as the anion size increases. The high statistical relevance makes this model a useful tool for predicting the melting points of imidazolium-based ionic liquids.

Document type Article
Note With supplementary file.
Language English
Published at https://doi.org/10.1039/b806367b
Other links https://www.scopus.com/pages/publications/52949140198
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