Issue 38, 2008
From the journal:

Physical Chemistry Chemical Physics

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

José S. Torrecilla,a   Francisco Rodríguez,a   José L. Bravo,b   Gadi Rothenberg,c   Kenneth R. Seddond  and  Ignacio López-Martin‡*d  

* Corresponding authors

a Department of Chemical Engineering, Faculty of Chemistry, University Complutense of Madrid, Madrid, Spain

b Departamento de Química Orgánica e Inorgánica, Universidad de Extremadura, Avenida de Elvas s/n, Badajoz, Spain

c Van’t Hoff Institute for Molecular Sciences, Universiteit van Amsterdam, Nieuwe Achtergracht 166, Amsterdam, The Netherlands

d QUILL Research Centre, School of Chemistry and Chemical Engineering, The Queen’s University of Belfast, David Keir Building, Stranmillis Road, Belfast, Northern Ireland, UK
E-mail: iglomar@unex.es
Fax: +34 927 257 203

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.

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

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Article information

DOI
https://doi.org/10.1039/B806367B
Article type
Paper
Submitted
15 Apr 2008
Accepted
16 Jun 2008
First published
04 Aug 2008

Phys. Chem. Chem. Phys., 2008,10, 5826-5831

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

J. S. Torrecilla, F. Rodríguez, J. L. Bravo, G. Rothenberg, K. R. Seddon and I. López-Martin, Phys. Chem. Chem. Phys., 2008, 10, 5826 DOI: 10.1039/B806367B

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