Documents disponibles écrits par cet auteur

Computation of upper flash point of chemical compounds using a chemical structure - based model / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 13 (Avril 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 13 (Avril 2012) . - pp. 5103-5107 Titre : Computation of upper flash point of chemical compounds using a chemical structure - based model Type de document : texte imprimé Auteurs : Gharagheizi, Farhad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Seyyed Alireza Mirkhani, Auteur Année de publication : 2012 Article en page(s) : pp. 5103-5107 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Modeling  Chemical  structure  Chemical  compound Résumé : In this communication, a quantitative structure-property relationship (QSPR) is presented for an estimation of the upper flash point of pure compounds. The model is a multilinear equation that has eight parameters. All the parameters are solely computed based on chemical structure. To develop this model, more than 3000 parameters were evaluated using the Genetic Algorithm Multivariate Linear Regression (GA-MLR) method to select the most statistically effective ones. The maximum average absolute relative deviation (mARD), ARD, squared correlation coefficient, and root mean squares of error of the model from database (DIPPR 801) values for 1294 pure compounds are 2S.76%, 3.56%, 0.95, and 17.42 K, respectively. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25777951 [article] Computation of upper flash point of chemical compounds using a chemical structure - based model [texte imprimé] / Gharagheizi, Farhad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Seyyed Alireza Mirkhani, Auteur . - 2012 . - pp. 5103-5107. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 13 (Avril 2012) . - pp. 5103-5107 Mots-clés : Modeling  Chemical  structure  Chemical  compound Résumé : In this communication, a quantitative structure-property relationship (QSPR) is presented for an estimation of the upper flash point of pure compounds. The model is a multilinear equation that has eight parameters. All the parameters are solely computed based on chemical structure. To develop this model, more than 3000 parameters were evaluated using the Genetic Algorithm Multivariate Linear Regression (GA-MLR) method to select the most statistically effective ones. The maximum average absolute relative deviation (mARD), ARD, squared correlation coefficient, and root mean squares of error of the model from database (DIPPR 801) values for 1294 pure compounds are 2S.76%, 3.56%, 0.95, and 17.42 K, respectively. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25777951

Corresponding states method for estimation of upper flammability limit temperature of chemical compounds / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 17 (Mai 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 17 (Mai 2012) . - pp. 6265–6269 Titre : Corresponding states method for estimation of upper flammability limit temperature of chemical compounds Type de document : texte imprimé Auteurs : Gharagheizi, Farhad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Amir H. Mohammadi, Auteur Année de publication : 2012 Article en page(s) : pp. 6265–6269 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Chemical  compounds  Flammability  limit Résumé : The accuracy and predictability of predictive methods to determine the flammability characteristics of chemical compounds are of drastic significance in the chemical industry. This work aims at continuing application of the gene expression programming (GEP) mathematical strategy to modify the existing thermophysical properties correlations available in the literature to pursue the following objectives: optimization of the number of independent parameters, amplification of the generality, and improvement of the accuracy and predictability. This work deals with presenting a simple corresponding states model to predict the upper flammability limit temperature of 1462 organic compounds from 76 chemical families. The parameters of the correlation include the critical temperature and the acentric factor of the compounds. The obtained statistical parameters including average absolute relative deviation of the results from DIPPR 801 database values (1.7, 1.8, 1.7% for training, optimization, and prediction sets, respectively) demonstrate improved accuracy of the presented correlations. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300375k [article] Corresponding states method for estimation of upper flammability limit temperature of chemical compounds [texte imprimé] / Gharagheizi, Farhad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Amir H. Mohammadi, Auteur . - 2012 . - pp. 6265–6269. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 17 (Mai 2012) . - pp. 6265–6269 Mots-clés : Chemical  compounds  Flammability  limit Résumé : The accuracy and predictability of predictive methods to determine the flammability characteristics of chemical compounds are of drastic significance in the chemical industry. This work aims at continuing application of the gene expression programming (GEP) mathematical strategy to modify the existing thermophysical properties correlations available in the literature to pursue the following objectives: optimization of the number of independent parameters, amplification of the generality, and improvement of the accuracy and predictability. This work deals with presenting a simple corresponding states model to predict the upper flammability limit temperature of 1462 organic compounds from 76 chemical families. The parameters of the correlation include the critical temperature and the acentric factor of the compounds. The obtained statistical parameters including average absolute relative deviation of the results from DIPPR 801 database values (1.7, 1.8, 1.7% for training, optimization, and prediction sets, respectively) demonstrate improved accuracy of the presented correlations. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300375k

Corresponding states method for evaluation of the solubility parameters of chemical compounds / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 9 (Mars 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 9 (Mars 2012) . - pp. 3826-3831 Titre : Corresponding states method for evaluation of the solubility parameters of chemical compounds Type de document : texte imprimé Auteurs : Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Sattari, Mehdi, Auteur Année de publication : 2012 Article en page(s) : pp. 3826-3831 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Chemical  compound  Solubility Résumé : In this study, our objective is to apply the gene expression programming mathematical algorithm to propose a correlation based on the corresponding states method to determine the solubility parameters of 1641 pure compounds (mostly organic ones) at 298.15 K and atmospheric pressure. The studied compounds are from the 80 chemical families. The parameters of the method include the critical temperature, critical pressure, molecular weight, and acentric factor. Around 1477 solubility parameter data are randomly selected for developing (training + optimization) the correlation, and about 164 data are used for checking its prediction capability. The obtained statistical parameters, including average absolute relative deviation of the results from the applied data (about 6%), show the accuracy of the proposed method along with its simplicity and wide range of applicability. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25595813 [article] Corresponding states method for evaluation of the solubility parameters of chemical compounds [texte imprimé] / Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Sattari, Mehdi, Auteur . - 2012 . - pp. 3826-3831. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 9 (Mars 2012) . - pp. 3826-3831 Mots-clés : Chemical  compound  Solubility Résumé : In this study, our objective is to apply the gene expression programming mathematical algorithm to propose a correlation based on the corresponding states method to determine the solubility parameters of 1641 pure compounds (mostly organic ones) at 298.15 K and atmospheric pressure. The studied compounds are from the 80 chemical families. The parameters of the method include the critical temperature, critical pressure, molecular weight, and acentric factor. Around 1477 solubility parameter data are randomly selected for developing (training + optimization) the correlation, and about 164 data are used for checking its prediction capability. The obtained statistical parameters, including average absolute relative deviation of the results from the applied data (about 6%), show the accuracy of the proposed method along with its simplicity and wide range of applicability. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25595813

Determination of parachor of various compounds using an artificial neural network-group contribution method / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 50 N° 9 (Mai 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 5815-5823 Titre : Determination of parachor of various compounds using an artificial neural network-group contribution method Type de document : texte imprimé Auteurs : Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Amir H. Mohammadi, Auteur Année de publication : 2011 Article en page(s) : pp. 5815-5823 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Group  contribution  method  Neural  network Résumé : In this communication, an Artificial Neural Network―Group Contribution algorithm is applied to represent/predict the parachor of pure chemical compounds. To propose a reliable and predictive tool, 227 pure chemical compounds are investigated. Using the developed method, we obtain satisfactory results that are quantified by the following statistical parameters: absolute average deviations of the represented/predicted parachor values from existing experimental ones, %AAD = 1.2%; and squared correlation coefficient, R2 = 0.997. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128707 [article] Determination of parachor of various compounds using an artificial neural network-group contribution method [texte imprimé] / Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Amir H. Mohammadi, Auteur . - 2011 . - pp. 5815-5823. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 9 (Mai 2011) . - pp. 5815-5823 Mots-clés : Group  contribution  method  Neural  network Résumé : In this communication, an Artificial Neural Network―Group Contribution algorithm is applied to represent/predict the parachor of pure chemical compounds. To propose a reliable and predictive tool, 227 pure chemical compounds are investigated. Using the developed method, we obtain satisfactory results that are quantified by the following statistical parameters: absolute average deviations of the represented/predicted parachor values from existing experimental ones, %AAD = 1.2%; and squared correlation coefficient, R2 = 0.997. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24128707

Determination of vapor pressure of chemical compounds / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 20 (Mai 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 20 (Mai 2012) . - pp. 7119-7125 Titre : Determination of vapor pressure of chemical compounds : A group contribution model for an extremely large database Type de document : texte imprimé Auteurs : Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Poorandokht Ilani-Kashkouli, Auteur Année de publication : 2012 Article en page(s) : pp. 7119-7125 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Database  Modeling  Chemical  compound  Vapor  pressure Résumé : In the present study, a group contribution model is developed for determination of the vapor pressure of pure chemical compounds at temperatures from 55 to 3040 K. About 42 000 vapor pressure values belonging to around 1400 chemical compounds (mostly organic ones) at different temperatures are treated to propose a reliable and predictive model. A three-layer artificial neural network is optimized using the Levenberg―Marquardt (LM) optimization algorithm to establish the final relationship between the functional groups and the vapor pressure values. The obtained results indicate the average absolute relative deviation (AARD%) of the calculations/estimations from the applied data to be about 6% and a squared correlation coefficient of 0.994. Furthermore, the outliers of the model are detected using the leverage value statistics method. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25925054 [article] Determination of vapor pressure of chemical compounds : A group contribution model for an extremely large database [texte imprimé] / Gharagheizi, Farhad, Auteur ; Ali Eslamimanesh, Auteur ; Poorandokht Ilani-Kashkouli, Auteur . - 2012 . - pp. 7119-7125. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 20 (Mai 2012) . - pp. 7119-7125 Mots-clés : Database  Modeling  Chemical  compound  Vapor  pressure Résumé : In the present study, a group contribution model is developed for determination of the vapor pressure of pure chemical compounds at temperatures from 55 to 3040 K. About 42 000 vapor pressure values belonging to around 1400 chemical compounds (mostly organic ones) at different temperatures are treated to propose a reliable and predictive model. A three-layer artificial neural network is optimized using the Levenberg―Marquardt (LM) optimization algorithm to establish the final relationship between the functional groups and the vapor pressure values. The obtained results indicate the average absolute relative deviation (AARD%) of the calculations/estimations from the applied data to be about 6% and a squared correlation coefficient of 0.994. Furthermore, the outliers of the model are detected using the leverage value statistics method. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25925054

Estimation of aniline point temperature of pure hydrocarbons / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 48 N°3 (Février 2009) 

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Evaluation of thermal conductivity of gases at atmospheric pressure through a corresponding states method / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 9 (Mars 2012) 

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Group contribution-based method for determination of solubility parameter of nonelectrolyte organic compounds / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 50 N° 17 (Septembre 2011) 

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New neural network group contribution model for estimation of lower flammability limit temperature of pure compounds / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 48 N° 15 (Août 2009) 

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Phase equilibrium modeling of structure H clathrate hydrates of methane + water “insoluble” hydrocarbon promoter using group contribution - support vector machine technique / Ali Eslamimanesh in Industrial & engineering chemistry research, Vol. 50 N° 22 (Novembre 2011) 

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Prediction of henry’s law constant of organic compounds in water from a new group - contribution - based model / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 49 N° 20 (Octobre 2010) 

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Prediction of the θ(UCST) of polymer solutions / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 48 N° 19 (Octobre 2009) 

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Prediction of triple-point temperature of pure components using their Chemical Structures / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 49 N° 2 (Janvier 2010) 

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QSPR molecular approach for estimating henry’s law constants of pure compounds in water at ambient conditions / Gharagheizi, Farhad in Industrial & engineering chemistry research, Vol. 51 N° 12 (Mars 2012) 

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