Issue 56, 2017

Solubility prediction of gases in polymers based on an artificial neural network: a review

Abstract

As an important physical chemistry property, solubility is still a popular research topic. Its theoretical calculation method has developed rapidly. In particular, the artificial neural network (ANN) has attracted the attention of researchers because of its unique nonlinear processing ability. This review provides a brief explanation of the ANN approaches that are most commonly applied to predict gas solubility in polymers, and states the implementation principle, progress, and performance analysis of hybrid ANNs based on the intelligence algorithm. The prospect of solubility prediction based on current research trends is then proposed. This review attempts to analyze the solubility calculation method and provides an insight into and reference for the application of the artificial intelligence method in chemistry and material fields, and can expand in the future because of the increasing number of solubility prediction approaches being introduced.

Graphical abstract: Solubility prediction of gases in polymers based on an artificial neural network: a review

Article information

Article type
Review Article
Submitted
13 4月 2017
Accepted
08 7月 2017
First published
13 7月 2017
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2017,7, 35274-35282

Solubility prediction of gases in polymers based on an artificial neural network: a review

L. Mengshan, W. Wei, C. Bingsheng, W. Yan and H. Xingyuan, RSC Adv., 2017, 7, 35274 DOI: 10.1039/C7RA04200K

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