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

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

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) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 12 (Mars 2012) . - pp. 4764–4767 Titre : QSPR molecular approach for estimating henry’s law constants of pure compounds in water at ambient conditions 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. 4764–4767 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Quantitative  structure  property  relationship Résumé : In this article, we present a comprehensive quantitative structure–property relationship (QSPR) to estimate the Henry’s law constant (H) of pure compounds in water at ambient conditions. This relationship is a multilinear equation containing eight chemical-structure-based parameters. The parameters were selected by the genetic algorithm multivariate linear regression (GA-MLR) method using more than 3000 molecular descriptors. The squared correlation coefficient of the model (R2) over 1954 pure compounds is equal to 0.983 (logarithmic-based data). Therefore, the model is comprehensive and accurate enough to be used to predict the Henry’s law constants of various compounds in water. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie202646u [article] QSPR molecular approach for estimating henry’s law constants of pure compounds in water at ambient conditions [texte imprimé] / Gharagheizi, Farhad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Seyyed Alireza Mirkhani, Auteur . - 2012 . - pp. 4764–4767. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 12 (Mars 2012) . - pp. 4764–4767 Mots-clés : Quantitative  structure  property  relationship Résumé : In this article, we present a comprehensive quantitative structure–property relationship (QSPR) to estimate the Henry’s law constant (H) of pure compounds in water at ambient conditions. This relationship is a multilinear equation containing eight chemical-structure-based parameters. The parameters were selected by the genetic algorithm multivariate linear regression (GA-MLR) method using more than 3000 molecular descriptors. The squared correlation coefficient of the model (R2) over 1954 pure compounds is equal to 0.983 (logarithmic-based data). Therefore, the model is comprehensive and accurate enough to be used to predict the Henry’s law constants of various compounds in water. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie202646u

Quantitative structure–property relationship study to predict speed of sound in diverse organic solvents from solvent structural information / Bahram Hemmateenejad in Industrial & engineering chemistry research, Vol. 51 N° 45 (Novembre 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 45 (Novembre 2012) . - pp. 14884-14891 Titre : Quantitative structure–property relationship study to predict speed of sound in diverse organic solvents from solvent structural information Type de document : texte imprimé Auteurs : Bahram Hemmateenejad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur Année de publication : 2013 Article en page(s) : pp. 14884-14891 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Organic  solvent  Property  structure  relationship Résumé : The interaction of solvents with ultrasonic waves is of drastic importance and has been the subject of many studies in recent years. In this study, the effect of solvent structural parameters on the speed of sound in chemical solvents was investigated through a quantitative structure―property relationship (QSPR). Genetic algorithm―multiple linear regression (GA-MLR) analysis was employed to select the most relevant subset of descriptors and, then, to develop the model. The validity of the obtained 10-parameter model was assessed by most widely used validation techniques. The predictive power of the model was evaluated by use of an external data set. The high level of accuracy of results approved the model. According to the model, those solvents that have stronger solvent―solvent interactions can create a more appropriate medium for passing and propagating sound waves and will result in higher speed of sounds. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26620401 [article] Quantitative structure–property relationship study to predict speed of sound in diverse organic solvents from solvent structural information [texte imprimé] / Bahram Hemmateenejad, Auteur ; Poorandokht Ilani-Kashkouli, Auteur . - 2013 . - pp. 14884-14891. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 45 (Novembre 2012) . - pp. 14884-14891 Mots-clés : Organic  solvent  Property  structure  relationship Résumé : The interaction of solvents with ultrasonic waves is of drastic importance and has been the subject of many studies in recent years. In this study, the effect of solvent structural parameters on the speed of sound in chemical solvents was investigated through a quantitative structure―property relationship (QSPR). Genetic algorithm―multiple linear regression (GA-MLR) analysis was employed to select the most relevant subset of descriptors and, then, to develop the model. The validity of the obtained 10-parameter model was assessed by most widely used validation techniques. The predictive power of the model was evaluated by use of an external data set. The high level of accuracy of results approved the model. According to the model, those solvents that have stronger solvent―solvent interactions can create a more appropriate medium for passing and propagating sound waves and will result in higher speed of sounds. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26620401