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Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using

Subhash Ajmani1,2, Stephen C Rogers3, Mark H Barley4

  • 1Centre for Molecular Design, Institute of Biomedical and Biomolecular Science, University of Portsmouth, King Henry 1 Street, Portsmouth PO1 2DY, UK, Tel/Fax: +91-20-27292268. subhasha@novaleadpharma.com.

Molecular Informatics
|July 28, 2016
PubMed
Summary

This study develops a quantitative structure-property relationship (QSPR) model to predict excess molar volume in binary mixtures. The model effectively uses specific mixture descriptors and neural networks, highlighting the importance of hydrogen bonding and thermodynamic factors.

Keywords:
Ensemble neural networkExcess molar volumeMixturesNeural networkQSPR

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