Predicting the net heat of combustion of organosilicon compounds from molecular structures / Yong Pan in Industrial & engineering chemistry research, Vol. 51 N° 40 (Octobre 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 40 (Octobre 2012) . - pp. 13274-13281 Titre : Predicting the net heat of combustion of organosilicon compounds from molecular structures Type de document : texte imprimé Auteurs : Yong Pan, Auteur ; Juncheng Jiang, Auteur ; Yinyan Zhang, Auteur Année de publication : 2012 Article en page(s) : pp. 13274-13281 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Molecular structure Combustion Prediction Résumé : The net heat of combustion is one of the most important properties of flammable substances that can be used to estimate the potential fire hazards of chemicals once they ignite and bum. This study proposed a quantitative structure-property relationship model to predict the net heat of combustion of 308 organosilicon compounds from only the knowledge of their molecular structures. Various kinds of molecular descriptors, such as topological, charge, and geometric descriptors, were calculated to represent the molecular structures of organosilicon compounds. The genetic algorithm combined with multiple linear regression is employed to select optimal subset of descriptors that have significant contribution to the overall net heat of combustion property. The best resulted model is a three-variable multilinear model, with the root-mean-square error and average absolute error for the external test set being 176.8 and 111.2 kJ/mol, respectively. Model validation was also performed to check the stability and predictive capability of the presented model. The results showed that the presented model is a valid and predictive model. This study can provide a new way for predicting the net heat of combustion of organosilicon compounds for engineering. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26451478 [article] Predicting the net heat of combustion of organosilicon compounds from molecular structures [texte imprimé] / Yong Pan, Auteur ; Juncheng Jiang, Auteur ; Yinyan Zhang, Auteur . - 2012 . - pp. 13274-13281. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 40 (Octobre 2012) . - pp. 13274-13281 Mots-clés : Molecular structure Combustion Prediction Résumé : The net heat of combustion is one of the most important properties of flammable substances that can be used to estimate the potential fire hazards of chemicals once they ignite and bum. This study proposed a quantitative structure-property relationship model to predict the net heat of combustion of 308 organosilicon compounds from only the knowledge of their molecular structures. Various kinds of molecular descriptors, such as topological, charge, and geometric descriptors, were calculated to represent the molecular structures of organosilicon compounds. The genetic algorithm combined with multiple linear regression is employed to select optimal subset of descriptors that have significant contribution to the overall net heat of combustion property. The best resulted model is a three-variable multilinear model, with the root-mean-square error and average absolute error for the external test set being 176.8 and 111.2 kJ/mol, respectively. Model validation was also performed to check the stability and predictive capability of the presented model. The results showed that the presented model is a valid and predictive model. This study can provide a new way for predicting the net heat of combustion of organosilicon compounds for engineering. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26451478

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Prediction of the upper flammability limits of organic compounds from molecular structures / Yong Pan in Industrial & engineering chemistry research, Vol. 48 N° 10 (Mai 2009)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 48 N° 10 (Mai 2009) . - pp. 5064–5069 Titre : Prediction of the upper flammability limits of organic compounds from molecular structures Type de document : texte imprimé Auteurs : Yong Pan, Auteur ; Juncheng Jiang, Auteur ; Rui, Wang, Auteur Année de publication : 2009 Article en page(s) : pp. 5064–5069 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Organic compounds Upper flammability limits Genetic algorithm Multiple linear regression Résumé : A quantitative structure−property relationship (QSPR) study is performed to develop mathematical models for prediction of the upper flammability limits (UFL) of organic compounds from their molecular structures. The structural features of the compounds are numerically represented by various kinds of calculated molecular descriptors such as topological, charge, and geometric descriptors. The genetic algorithm combined with multiple linear regression (GA-MLR) is used to select an optimal subset of descriptors that have significant contribution to the overall UFL property from the large pool of calculated descriptors. The best resulted model is a four-variable multilinear model with a defined applicability range. The average absolute error and root-mean-square error obtained for the external test set are 1.75 vol % and 2.77, respectively. The proposed model can be used to predict the UFL of organic compounds with only four preselected theoretical descriptors which can be directly calculated from molecular structure alone. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900193r [article] Prediction of the upper flammability limits of organic compounds from molecular structures [texte imprimé] / Yong Pan, Auteur ; Juncheng Jiang, Auteur ; Rui, Wang, Auteur . - 2009 . - pp. 5064–5069. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 10 (Mai 2009) . - pp. 5064–5069 Mots-clés : Organic compounds Upper flammability limits Genetic algorithm Multiple linear regression Résumé : A quantitative structure−property relationship (QSPR) study is performed to develop mathematical models for prediction of the upper flammability limits (UFL) of organic compounds from their molecular structures. The structural features of the compounds are numerically represented by various kinds of calculated molecular descriptors such as topological, charge, and geometric descriptors. The genetic algorithm combined with multiple linear regression (GA-MLR) is used to select an optimal subset of descriptors that have significant contribution to the overall UFL property from the large pool of calculated descriptors. The best resulted model is a four-variable multilinear model with a defined applicability range. The average absolute error and root-mean-square error obtained for the external test set are 1.75 vol % and 2.77, respectively. The proposed model can be used to predict the UFL of organic compounds with only four preselected theoretical descriptors which can be directly calculated from molecular structure alone. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900193r

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