Prediction of solubility for polycyclic aromatic hydrocarbons in supercritical carbon dioxide using wavelet neural networks in quantitative structure property relationship-Reference-Cited by-同舟云学术

Prediction of solubility for polycyclic aromatic hydrocarbons in supercritical carbon dioxide using wavelet neural networks in quantitative structure property relationship

Published:2004-12 Issue:1-3 Volume:32 Page:73-78
ISSN:0896-8446
Container-title:The Journal of Supercritical Fluids
language:en
Short-container-title:The Journal of Supercritical Fluids

Author:

Khayamian T.,Esteki M.

Publisher

Elsevier BV

Subject

Physical and Theoretical Chemistry,Condensed Matter Physics,General Chemical Engineering

Reference19 articles.

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2. E. Kiran, J.F. Brennecke (Eds.), Supercritical fluid engineering science: fundamentals and applications, ACS Symposium Series 514, American Chemical Society, Washington, DC, 1993, Chapter 1.

3. Modeling supercritical mixtures: how predictive is it?;Johnston;Ind. Eng. Chem. Res,1989

4. Solubility of anthracene and phenanthrene mixtures in supercritical carbon dioxide;Kosal;J. Chem. Eng. Data,1987

5. A new two constant equation of state;Peng;Ind. Eng. Chem. Fundam,1976

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