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

被引：79

作者：

Torrecilla, Jose S. ^{[1
]}

Rodriguez, Francisco ^{[1
]}

Bravo, Jose L. ^{[2
]}

Rothenberg, Gadi ^{[3
]}

Seddon, Kenneth R. ^{[4
]}

Lopez-Martin, Ignacio ^{[4
]}

机构：

[1] Univ Complutense Madrid, Fac Chem, Dept Chem Engn, E-28040 Madrid, Spain

[2] Univ Extremadura, Dept Quim Organ & Inorgan, E-06071 Badajoz, Spain

[3] Univ Amsterdam, Vant Hoff Inst Mol Sci, NL-1018 WV Amsterdam, Netherlands

[4] Queens Univ Belfast, Sch Chem & Chem Engn, QUILL Res Ctr, Belfast BT9 5AG, Antrim, North Ireland

来源：

PHYSICAL CHEMISTRY CHEMICAL PHYSICS | 2008年 / 10卷 / 38期

基金：

英国工程与自然科学研究理事会;

关键词：

D O I：

10.1039/b806367b

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

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.

引用

页码：5826 / 5831

页数：6

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