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• W2892232092 abstract "Prediction of adsorption equilibrium coefficients (K) of organic compounds onto single walled carbon nanotubes (SWNTs) from in silico molecular descriptors is of importance for probing potential applications of SWNTs as well as for evaluating environmental behavior and ecological risks of organic pollutants and SWNTs. In this study, two models for predicting logK were developed with multiple linear regression (MLR) and support vector machine (SVM) algorithms. The two models have satisfactory goodness-of-fit, robustness and predictive ability, and the SVM model performs slightly better than the MLR model. The two models are based on the up-to-date experimental dataset consisting of 61 logK values, and the applicability domains cover diverse organic compounds with functional groups > CC<, CC, C6H5, >CO, COOH, C(O)O, OH, O, F, Cl, Br, NH2, NH, >N, >NN<, NO2, >NC(O)NH2, >NC(O)NH, S and S(O)(O). The adsorption of organic compounds toward SWNTs is mainly determined by van der Waals forces and hydrophobic interactions. Since only in silico molecular descriptors were employed for the modeling, the developed models are beneficial for prediction purposes." @default.
• W2892232092 created "2018-09-27" @default.
• W2892232092 creator A5000195058 @default.
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• W2892232092 date "2019-01-01" @default.
• W2892232092 modified "2023-10-06" @default.
• W2892232092 title "Modeling adsorption of organic pollutants onto single-walled carbon nanotubes with theoretical molecular descriptors using MLR and SVM algorithms" @default.
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• W2892232092 doi "https://doi.org/10.1016/j.chemosphere.2018.09.074" @default.
• W2892232092 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30261420" @default.
• W2892232092 hasPublicationYear "2019" @default.
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