Group contribution model for determination of molecular diffusivity of non-electrolyte organic compounds in air at ambient conditions
Résumé
Determination of diffusion coefficients of pure compounds in air is of great interest for modeling of air pollution control processes. In this communication, a Group Contribution (GC) method is applied to represent/predict the molecular diffusivity of chemical compounds in air at 298.15 K and atmospheric pressure. 4661 compounds from various chemical families have been investigated to propose a comprehensive and predictive model. The final model is resulted from coupling the Artificial Neural Network (ANN) with group contributions. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.995, Standard Deviation Error=0.02, and Average Absolute Deviation=1.4% for the calculated/predicted properties from existing experimental values.