Representation and Prediction of Molecular Diffusivity of Nonelectrolyte Organic Compounds in Water at Infinite Dilution Using the Artificial Neural Network-Group Contribution Method

Farhad Gharagheizi (1) , Ali Eslamimanesh (2) , Amir H. Mohammadi (3) , Dominique Richon (3)

1 Department of Chemical Engineering
2 CEP - Centre Énergétique et Procédés
3 CEP/Fontainebleau

The determination of diffusion coefficients of pure compounds in water at infinite dilution is of utmost interest in chemical and environmental engineering, especially wastewater treatment processes. In this work, the artificial neural network-group contribution (ANN-GC) method is applied to represent and predict the molecular diffusivity of nonelectrolyte organic compounds in water at infinite dilution and 298.15 K. A total of 4852 pure compounds from various chemical families has been investigated to propose a predictive model. The obtained results show the squared correlation coefficient of 0.996, root-mean-square error of about 0.02, and average absolute deviation lower than 1.5 % for the calculated or predicted property from existing experimental values.

Domaines: Génie des procédés

Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi, Dominique Richon. Representation and Prediction of Molecular Diffusivity of Nonelectrolyte Organic Compounds in Water at Infinite Dilution Using the Artificial Neural Network-Group Contribution Method. Journal of Chemical and Engineering Data, 2011, 56 (5), pp.1741-1750. ⟨10.1021/je101190p⟩. ⟨hal-00595545⟩