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

Abstract : 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.
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00595545
Contributeur : Bibliothèque Mines Paristech <>
Soumis le : mercredi 25 mai 2011 - 10:01:40
Dernière modification le : jeudi 24 septembre 2020 - 17:22:04

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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, American Chemical Society, 2011, 56 (5), pp.1741-1750. ⟨10.1021/je101190p⟩. ⟨hal-00595545⟩

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