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水中合成有机化合物在单壁碳纳米管上吸附的线性溶剂化能关系

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

作者信息

Ding H, Chen C, Zhang X

机构信息

a School of Environment, Tsinghua University , Beijing , China.

出版信息

SAR QSAR Environ Res. 2016;27(1):31-45. doi: 10.1080/1062936X.2015.1132764.

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.

摘要

线性溶剂化能关系(LSER)被用于预测合成有机化合物(SOCs)在单壁碳纳米管(SWCNTs)上的吸附系数(K)。总共40个log K值被用于开发和验证LSER模型。34种SOCs的吸附数据来自13篇已发表的文章,另外6种是在我们的实验中获得的。通过逐步多元线性回归(MLR)方法开发了由四个描述符组成的最优模型。调整后的r(2)(r(2)adj)和均方根误差(RMSE)分别为0.84和0.49,表明拟合良好。留一法交叉验证Q(2)([公式:见正文])为0.79,表明模型的稳健性令人满意。外部Q(2)([公式:见正文])和RMSE(RMSEext)分别为0.72和0.50,表明模型具有很强的预测能力。氢键供体相互作用(bB)以及空穴形成和色散相互作用(vV)是控制SOCs在SWCNTs上吸附的两个最具影响力的因素。平衡浓度会影响模型的拟合度和预测能力,而系数略有变化。

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