Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential.

Azo dyes are broadly used in different industries through their chemical stability and ease of synthesis. However, these dyes are usually identified as critical environmental pollutants. Hence, a mathematical model for the adsorption affinity of azo dyes can be applied for solving tasks of medicine and ecology. Quantitative structure-property relationships for the adsorption affinity of azo dyes to a substrate (DAF, kJ/mol) were established using the Monte Carlo method by generating optimal SMILES-based descriptors. The index of ideality of correlation ( IIC ) and the correlation intensity index ( CII ) improved the model's predictive potential, especially when they were used simultaneously. The statistical quality of the best model on the validation set was characterized by n = 18, r 2  = 0.9468, and RMSE = 1.26 kJ/mol.