Ionic surfactants critical micelle concentration prediction in water/organic solvent mixtures by artificial neural network
Abstract: Critical micellar concentration (CMC) is a key physicochemical property of surfactants used to study their behaviour. This property is affected by factors such as temperature, pressure, pH, the type of organic solvent/water mixture, the chemical structure of the surfactants and the presence of electrolytes. Most of the existing studies in the literature have predicted the CMC under fixed conditions based on the chemical parameters of the surfactant. In this study, a machine learning approach using artificial neural network (ANN) models was used to estimate the CMC of some ionic surfactants. These models considered variables defining both the organic solvent-water mixture (T, molecular weight, molar fraction and log P) and the chemical structure of the surfactant (number of atoms of each element). A database consisting of a total of 258 CMC values for 10 ionic surfactants was collected from the literature. The ANN architecture consisting of an input layer with 12 neurons, an intermediate layer with 25 neurons and one neuron in the output layer is proposed. According to the results, the normalized ANN models provided the best statistical adjustments for the CMC prediction. These ANN models could be a promising method for CMC estimation.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Ionic surfactants critical micelle concentration prediction in water/organic solvent mixtures by artificial neural network ; volume:61 ; number:6 ; year:2024 ; pages:519-529 ; extent:11
Tenside, surfactants, detergents ; 61, Heft 6 (2024), 519-529 (gesamt 11)
- Urheber
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Soria-Lopez, Anton
García-Martí, María
Barreiro, Enrique
Mejuto, Juan C.
- DOI
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10.1515/tsd-2024-2623
- URN
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urn:nbn:de:101:1-2411061603598.841027603475
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:38 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Soria-Lopez, Anton
- García-Martí, María
- Barreiro, Enrique
- Mejuto, Juan C.
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