title: Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.
abstract: The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.
authors: a School of Environment, Tsinghua University , Beijing , China.
authors: H
authors: H
authors: Ding
authors: a School of Environment, Tsinghua University , Beijing , China.
authors: C
authors: C
authors: Chen
authors: a School of Environment, Tsinghua University , Beijing , China.
authors: X
authors: X
authors: Zhang
mesh_terms: D000327:Adsorption; D008962:Models, Theoretical; D037742:Nanotubes, Carbon / Q000737:chemistry*; D009930:Organic Chemicals / Q000737:chemistry*; D014867:Water / Q000737:chemistry*
chemical_list: D037742:Nanotubes, Carbon; D009930:Organic Chemicals; D014867:Water
keywords: Linear solvation energy relationship; adsorption; single-walled carbon nanotubes; stepwise multiple linear regression; synthetic organic compounds