In Silico Prediction of Critical Micelle Concentration (CMC) of Classic and Extended Anionic Surfactants from Their Mole

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RESEARCH ARTICLE-CHEMICAL ENGINEERING

In Silico Prediction of Critical Micelle Concentration (CMC) of Classic and Extended Anionic Surfactants from Their Molecular Structural Descriptors S. Rahal1 · N. Hadidi1 · M. Hamadache1 Received: 13 February 2020 / Accepted: 26 April 2020 © King Fahd University of Petroleum & Minerals 2020

Abstract CMC is an important parameter for the characterization of surfactants. Compared to other properties, the CMC can be correlated with surfactants performance characteristics on an industrial scale. In this investigation, QSPR models were established to identify the relation between the molecular structures and the critical micelle concentration (CMC) of 50 anionic surfactants employing four molecular structural descriptors. Three regression methods were chosen in this work to develop robust predictive models, namely multilayer perceptron–artificial neural network (MLP/ANN), multiple linear regressions, and partial least square approach. To establish the reliability and the robustness of the developed QSPR models,   2 all available validation strategies were adopted. The best results rm  0.87; Q 2LOO  0.93; Q 2F1  0.95; rm2  0.15 were obtained for MLP/ANN with a 4-3-1 artificial neural network model trained with the Broyden–Fletcher–Goldfarb–Shanno algorithm. In this study, it is observed that electronic properties, structure and size of the molecule, as well as the number of atoms in the longest aliphatic chain play major roles in the development of the CMC model of anionic surfactants. Keywords QSPR · Anionic surfactants · CMC · Predicting · MLP–ANN · MLR

1 Introduction A large number of main properties of the surfactant solution such as conductivity, emulsification, surface tension, detergency, foam stability and conductivity are important for many industrial and biological systems [1–4]. In addition, it has been established that the values of these physicochemical properties change radically as soon as the molecules begin to aggregate to form micelles [5]. At this moment, the concentration of the surfactant is defined as critical micelle concentration (CMC). Therefore, the CMC is an important and extremely useful parameter for characterizing surfactants. Given the impact of CMC on the characteristics of surfactant, it seems obvious to pay special attention to it [4]. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13369-020-04598-0) contains supplementary material, which is available to authorized users.

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S. Rahal [email protected]; [email protected] Department of Process Engineering and Environment, Faculty of Technology, Yahia Fares University of Medea, Medea, Algeria

Anionic surfactants constitute the largest class of surfactants. Of all types of surfactants, they are the most widely used and account for about 70% of the surfactant consumption [6]. Various industrial processes are carried out with the addition of anionic surfactants. They are used as wetting agents, emulsifiers, dispersants and foami