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Predicting the Surface Tension of Liquids: Comparison of Four Modeling Approaches and Application to Cosmetic Oils

Goussard, Valentin and Duprat, Arthur and Gerbaud, Vincent and Ploix, Jean-Luc and Dreyfus, Gérard and Nardello-Rataj, Véronique and Aubry, Jean-Marie Predicting the Surface Tension of Liquids: Comparison of Four Modeling Approaches and Application to Cosmetic Oils. (2017) Journal of Chemical Information and Modeling, 57 (12). 2986-2995. ISSN 1549-9596

(Document in English)

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The efficiency of four modeling approaches, namely group contributions, corresponding-states principle, σ-moment-based neural networks, and graph machines, are compared for the estimation of the surface tension (ST) of 269 pure liquid compounds at 25 °C from their molecular structure. This study focuses on liquids containing only carbon, oxygen, hydrogen or silicon atoms since our purpose is to predict the surface tension of cosmetic oils. Neural network estimations are performed from σ-moment descriptors as defined in the COSMO-RS model, while methods based on group contributions, corresponding-states principle and graph machines use 2D molecular information (SMILES codes). The graph machine approach provides the best results, estimating the surface tensions of 23 cosmetic oils, such as hemisqualane, isopropyl myristate or decamethylcyclopentasiloxane (D5), with accuracy better than 1 mN.m–1. A demonstration of the graph machine model using the recent Docker technology is available for download in the Supplementary Information.

Item Type:Article
Additional Information:Thanks to American Chemical Society editor. The original PDF of the article can be found at Journal of Chemical Information and Modeling website : https://pubs.acs.org/doi/abs/%2010.1021%2Facs.jcim.7b00512
HAL Id:hal-03512685
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Other partners > PSL Research University (FRANCE)
Other partners > Université Lille 1, Sciences et Technologies - Lille 1 (FRANCE)
Laboratory name:
Deposited On:16 Feb 2018 14:17

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