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Neural Network Modeling of Adsorption Equilibria of Mixtures in Supercritical Fluids

Jha, Sujit Kumar and Madras, Giridhar (2005) Neural Network Modeling of Adsorption Equilibria of Mixtures in Supercritical Fluids. In: Industrial and Engineering Chemistry Research, 44 (17). pp. 7038-7041.

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Abstract

A neural network model was used to predict the ternary adsorption equilibria of 2,6- and 2,7-dimethylnaphthalene isomers dissolved in supercritical carbon dioxide on NaY-type zeolite. The neural network was trained using binary (pure solute dissolved in supercritical carbon dioxide onto NaY-type zeolite) and ternary adsorption equilibrium data. Despite a limited number of data points available for the training of the network, the model was capable of predicting the ternary adsorption equilibria using the binary adsorption equilibrium data very precisely.

Item Type: Journal Article
Publication: Industrial and Engineering Chemistry Research
Publisher: American Chemical Society
Additional Information: The copyright for this article belongs to American Chemical Society.
Department/Centre: Division of Mechanical Sciences > Chemical Engineering
Date Deposited: 21 Sep 2005
Last Modified: 27 Aug 2008 11:28
URI: http://eprints.iisc.ac.in/id/eprint/3686

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