Monte Carlo Simulation of Aromatic Molecule Adsorption on Multi-Walled Carbon Nanotube Surfaces Using Coefficient of Conformism of a Correlative Prediction (CCCP)

Using the Monte Carlo technique via CORAL-2024 software, models of aromatic substance adsorption on multi-walled nanotubes were constructed. Possible mechanistic interpretations of such models and the corresponding applicability domains were investigated. In constructing the models, criteria of the predictive potential such as the iIndex of Ideality of Correlation (IIC), the Correlation Intensity Index (CII), and the Coefficient of Conformism of a Correlative Prediction (CCCP) were used. It was assumed that the CCCP could serve as a tool for increasing the predictive potential of adsorption models of organic substances on the surface of nanotubes. The developed models provided good predictive potential. The perspectives on the improvement of the nano-QSPR/QSAR were discussed.