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A neural network approach to predict activity coefficients

Published:2009-09-22 Issue:5 Volume:87 Page:748-760
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can. J. Chem. Eng.

Author:

Ramírez‐Beltrán Nazario D.¹,Vallés Harry Rodríguez²,Estévez L. Antonio³,Duarte Horacio⁴

Affiliation:

1. Department of Industrial Engineering, University of Puerto Rico, Mayaguez, Puerto Rico 00680

2. Cordis LLC a Johnson & Johnson Company, San German, Puerto Rico 00683

3. Department of Chemical Engineering, University of Puerto Rico, Mayaguez, Puerto Rico 00680

4. Department of Chemical Engineering, Texas A&M University, Kingsville, Texas

Publisher

Wiley

Subject

General Chemical Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjce.20212

Reference26 articles.

1. Statistical thermodynamics of liquid mixtures: A new expression for the excess Gibbs energy of partly or completely miscible systems

2. Método Modificado Lydersen‐Joback‐Reid para Estimar Propiedades Críticas de Biomoléculas;Álvarez V. H.;Alimentaria,2004

3. Using Backpropagation Networks for the Estimation of Aqueous Activity Coefficients of Aromatic Organic Compounds

4. New group contribution method for estimating properties of pure compounds

5. Group-contribution estimation of activity coefficients in nonideal liquid mixtures

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3. Vapor-Liquid equilibria modeling using gray-box neural networks as binary interaction parameters predictor;DYNA;2017-10-01

4. Prediction of Henry’s Law Constant of Organic Compounds in Water from a New Group-Contribution-Based Model;Industrial & Engineering Chemistry Research;2010-10-20

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