Prediction of vaporization enthalpy of pure compounds using a group contribution-based method / Farhad Gharagheizi in Industrial & engineering chemistry research, Vol. 50 N° 10 (Mai 2011)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 50 N° 10 (Mai 2011) . - pp. 6503-6507 Titre : Prediction of vaporization enthalpy of pure compounds using a group contribution-based method Type de document : texte imprimé Auteurs : Farhad Gharagheizi, Auteur ; Omid Babaie, Auteur ; Sahar Mazdeyasna, Auteur Année de publication : 2011 Article en page(s) : pp. 6503-6507 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Thermodynamic properties Enthalpy Vaporization Prediction Résumé : In this work, the artificial neural network-group contribution (ANN-GC) method is applied to estimate the vaporization enthalpy of pure chemical compounds at their normal boiling point. A group of 4907 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coeffident (R2) of 0.993, root mean square error of 1.1 kJ/mol, and average absolute deviation lower than 1.5% for the estimated properties from existing experimental values. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24158948 [article] Prediction of vaporization enthalpy of pure compounds using a group contribution-based method [texte imprimé] / Farhad Gharagheizi, Auteur ; Omid Babaie, Auteur ; Sahar Mazdeyasna, Auteur . - 2011 . - pp. 6503-6507. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 10 (Mai 2011) . - pp. 6503-6507 Mots-clés : Thermodynamic properties Enthalpy Vaporization Prediction Résumé : In this work, the artificial neural network-group contribution (ANN-GC) method is applied to estimate the vaporization enthalpy of pure chemical compounds at their normal boiling point. A group of 4907 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coeffident (R2) of 0.993, root mean square error of 1.1 kJ/mol, and average absolute deviation lower than 1.5% for the estimated properties from existing experimental values. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24158948

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