Predicting critical micelle concentration values of non-ionic surfactants by using artificial neural networks / Gonzalo Astray in TENSIDE, SURFACTANTS, DETERGENTS, Vol. 50, N° 2 (03-04/2013)

[article]  inTENSIDE, SURFACTANTS, DETERGENTS > Vol. 50, N° 2 (03-04/2013) . - p. 118-124 Titre : Predicting critical micelle concentration values of non-ionic surfactants by using artificial neural networks Type de document : texte imprimé Auteurs : Gonzalo Astray, Auteur ; A. Iglesias-Otero, Auteur ; Oscar Adrian Moldes, Auteur ; Juan Carlos Mejuto, Auteur Année de publication : 2013 Article en page(s) : p. 118-124 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Concentration micellaire critique Réseaux neuronaux (informatique) Surfactants Index. décimale : 668.1 Agents tensioactifs : savons, détergents Résumé : Critical Micelle Concentration is a fundamental property on studying behaviour of surfactants. In general terms it depends on temperature, pressure and on the existence and concentration of other surface-active substances and electrolytes. In this work it is presented a model based on Artificial Neural Networks to obtain predictive values of Critical Micelle Concentration (CMC) of some non-ionic surfactants. ANN model works using topological descriptors of the molecules involved together with already known CMC values and provides predictive values for new cases. It is proposed a specific architecture for ANN consisting of an input layer with seven neurons, one intermediate layer with fourteen neurons and one neuron in the output layer. This ANN model seems to be a good method for forecast CMC. DOI : 10.3139/113.110242 Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=17890 [article]

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