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 R2test, at the same time keeping the statistical quality of the subtrainingand validation sets. Two predictive models were developed by using hydrogen-filledgraph-based descriptors (model 1) and hybrid descriptors (model 2) with squared correlation coefficient(R2) values of 0.985 and 0.940, respectively. The prediction power of these models was evaluated on a six-member test set, leading to R2values of 0.962 and 0.941 for model 1 and model2, respectively. Moreover, the leave-one-out cross validation test was used to investigate therobustness of models, which lead to Q2 values of 0.983 for model 1 and 0.932 for model 2.
