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A Theoretical Approach to Model and Predict the Adsorption Coefficients of Some Small Aromatic Molecules on Carbon Nanotube
Author(s) -
Heidari Afsane,
Fatemi Mohammad H.
Publication year - 2017
Publication title -
journal of the chinese chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 45
eISSN - 2192-6549
pISSN - 0009-4536
DOI - 10.1002/jccs.201600761
Subject(s) - chemistry , quantitative structure–activity relationship , adsorption , correlation coefficient , biological system , monte carlo method , carbon nanotube , molecular descriptor , robustness (evolution) , mathematics , thermodynamics , statistics , statistical physics , nanotechnology , organic chemistry , stereochemistry , materials science , biochemistry , physics , gene , biology
In this study, for the first time, the CORAL software is used to model the quantitative structure–property relationship ( QSPR ) of adsorption coefficients of chemicals on carbon nanotubes. The new method, which includes three‐dimensional response surfaces for all subsets, is used to optimize Monte Carlo parameters in the modeling procedure. By using the 3D response surfaces, we obtained a satisfactory value for R test 2 , at the same time keeping the statistical quality of the subtraining and validation sets. Two predictive models were developed by using hydrogen‐filled graph‐based descriptors (model 1) and hybrid descriptors (model 2) with squared correlation coefficient ( R 2 ) values of 0.985 and 0.940, respectively. The prediction power of these models was evaluated on a six‐member test set, leading to R 2 values of 0.962 and 0.941 for model 1 and model 2, respectively. Moreover, the leave‐one‐out cross validation test was used to investigate the robustness of models, which lead to Q 2 values of 0.983 for model 1 and 0.932 for model 2.