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Quantitative structure–property relations (QSPRs) for predicting the standard absolute entropy (S298 K°) of gaseous organic compounds / Lailong Mu in Industrial & engineering chemistry research, Vol. 50 N° 14 (Juillet 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 14 (Juillet 2011) . - pp. 8764–8772 Titre : Quantitative structure–property relations (QSPRs) for predicting the standard absolute entropy (S298 K°) of gaseous organic compounds Type de document : texte imprimé Auteurs : Lailong Mu, Auteur ; Hongmei He, Auteur Année de publication : 2011 Article en page(s) : pp. 8764–8772 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Gaseous  organic  compounds Résumé : To predict the standard absolute entropies of gaseous organic compounds, the variable molecular connectivity index (mχ′) and Ring parameter (H), based on adjacency matrix of molecular graphs, variable atomic valence connectivity index (δi′), and the numbers of atomic chains (cycles) of molecule niR were proposed. The optimal values of parameters b, c, mi, and y included in the definition of δi′, and mχ′ can be found by using an optimization method. When b = 1.3, c = 0.91, and y = 0.22, a good four-parameter model can be constructed from H and mχ′ by using the best subsets regression analysis method for the standard absolute entropies of gaseous organic compounds. The correlation coefficient (r), standard error (s), and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9988, 8.16 J K–1 mol–1, and 6.13 J K–1 mol–1, respectively, for the 726 gaseous organic compounds (training set). The AAD of predicted values of the standard absolute entropy of another 364 gaseous organic compounds (test set) is 6.14 J K–1 mol–1 for the MLR model. The results show that the MLR method can provide an accurate model for the prediction of the standard absolute entropies of gaseous organic compounds. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2003335 [article] Quantitative structure–property relations (QSPRs) for predicting the standard absolute entropy (S298 K°) of gaseous organic compounds [texte imprimé] / Lailong Mu, Auteur ; Hongmei He, Auteur . - 2011 . - pp. 8764–8772. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 14 (Juillet 2011) . - pp. 8764–8772 Mots-clés : Gaseous  organic  compounds Résumé : To predict the standard absolute entropies of gaseous organic compounds, the variable molecular connectivity index (mχ′) and Ring parameter (H), based on adjacency matrix of molecular graphs, variable atomic valence connectivity index (δi′), and the numbers of atomic chains (cycles) of molecule niR were proposed. The optimal values of parameters b, c, mi, and y included in the definition of δi′, and mχ′ can be found by using an optimization method. When b = 1.3, c = 0.91, and y = 0.22, a good four-parameter model can be constructed from H and mχ′ by using the best subsets regression analysis method for the standard absolute entropies of gaseous organic compounds. The correlation coefficient (r), standard error (s), and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9988, 8.16 J K–1 mol–1, and 6.13 J K–1 mol–1, respectively, for the 726 gaseous organic compounds (training set). The AAD of predicted values of the standard absolute entropy of another 364 gaseous organic compounds (test set) is 6.14 J K–1 mol–1 for the MLR model. The results show that the MLR method can provide an accurate model for the prediction of the standard absolute entropies of gaseous organic compounds. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2003335

Variable molecular connectivity indices for predicting the diamagnetic susceptibilities of organic compounds / Lailong Mu in Industrial & engineering chemistry research, Vol. 48 N° 8 (Avril 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 8 (Avril 2009) . - pp. 4165–4175 Titre : Variable molecular connectivity indices for predicting the diamagnetic susceptibilities of organic compounds Type de document : texte imprimé Auteurs : Lailong Mu, Auteur ; Hongmei He, Auteur ; Weihua Yang, Auteur Année de publication : 2009 Article en page(s) : pp. 4165–4175 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Molar  diamagnetic  susceptibilities  Organic  compounds  Average  absolute  deviation  Multivariate  linear  regression Résumé : For predicting the molar diamagnetic susceptibilities of organic compounds, a variable molecular connectivity index mχ′ and its converse index mχ′′ based on the adjacency matrix of molecular graphs and the variable atomic valence connectivity index δi′ were proposed. The optimal values of parameters a, b, and y included in definition of δi′, mχ′ and mχ′′ can be found by optimization methods. When a = 1.10, b = 2.8, and y = 0.36, a good five-parameter model can be constructed from mχ′ and mχ′′ by using the best subsets regression analysis method for the molar diamagnetic susceptibilities of organic compounds. The correlation coefficient r, standard error s, and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9930, 4.99, and 3.72 cgs, respectively, for the 720 organic compounds (training set). The AAD of predicted values of the molar diamagnetic susceptibility of another 361 organic compounds (test set) is 4.37 cgs for the MLR model. The results show that the current method is more effective than literature methods for estimating the molar diamagnetic susceptibility of an organic compound. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801252j [article] Variable molecular connectivity indices for predicting the diamagnetic susceptibilities of organic compounds [texte imprimé] / Lailong Mu, Auteur ; Hongmei He, Auteur ; Weihua Yang, Auteur . - 2009 . - pp. 4165–4175. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 8 (Avril 2009) . - pp. 4165–4175 Mots-clés : Molar  diamagnetic  susceptibilities  Organic  compounds  Average  absolute  deviation  Multivariate  linear  regression Résumé : For predicting the molar diamagnetic susceptibilities of organic compounds, a variable molecular connectivity index mχ′ and its converse index mχ′′ based on the adjacency matrix of molecular graphs and the variable atomic valence connectivity index δi′ were proposed. The optimal values of parameters a, b, and y included in definition of δi′, mχ′ and mχ′′ can be found by optimization methods. When a = 1.10, b = 2.8, and y = 0.36, a good five-parameter model can be constructed from mχ′ and mχ′′ by using the best subsets regression analysis method for the molar diamagnetic susceptibilities of organic compounds. The correlation coefficient r, standard error s, and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9930, 4.99, and 3.72 cgs, respectively, for the 720 organic compounds (training set). The AAD of predicted values of the molar diamagnetic susceptibility of another 361 organic compounds (test set) is 4.37 cgs for the MLR model. The results show that the current method is more effective than literature methods for estimating the molar diamagnetic susceptibility of an organic compound. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801252j