Accurate Prediction of the Adsorption Capabilities of Synthetic Organic Contaminants by Single‐Walled Carbon Nanotubes

Abstract

AbstractIn this work, quantitative structure‐property relationship (QSPR) was employed to predict the adsorption capabilities of 40 synthetic organic contaminants (SOCs) by single‐walled carbon nanotubes (SWCNTs). Total of 1081 molecular descriptors that consist of 102 constitutional and physicochemical properties, 342 topological properties, and 637 three‐dimensional properties were used to characterize the chemical information of the 40 SOCs. After removing redundant variables by stepwise multiple regression (SMR), an optimal partial least squares (PLS) model was established by using only 3 decriptors, i. e., BEHv, Dm, and Mor30e. The determinant R2 of the training samples, Leave‐one‐out cross validation R2 (Q2), and R2pred of test samples were 0.775, 0.675, and 0.713, respectively. Y‐random permutation test showed that the optimal PLS model is not caused by chance. Based on the optimal PLS model, it can be inferred that topological, steric, and electronic properties are dominant factors affecting the adsorption capabilities of the SOCs by SWCNTs.