Documents disponibles écrits par cet auteur

Investigation of the relationships between molecular structure, molecular descriptors, and physical properties / Inga Paster in Industrial & engineering chemistry research, Vol. 48 N° 21 (Novembre 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 21 (Novembre 2009) . - pp. 9723–9734 Titre : Investigation of the relationships between molecular structure, molecular descriptors, and physical properties Type de document : texte imprimé Auteurs : Inga Paster, Auteur ; Shacham, Mordechai, Auteur ; Neima Brauner, Auteur Année de publication : 2010 Article en page(s) : pp. 9723–9734 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Molecular  Structures  Molecular  descriptors  Quantitative  structure  property  relations Résumé : The use of databases containing thousands of molecular descriptors, including 3-D descriptors, for predicting physical properties is discussed. It is shown that the use of 3-D descriptors for property prediction via quantitative structure property relations (QSPR) limits considerably their applicability, as 3-D structure files must be obtained from the same reliable source for all predictive and target compounds. A modified targeted QSPR (TQSPR) algorithm is presented, which includes a new technique for selecting training sets belonging to the homologous series of the target compound (if such compounds are available in the database). The method is employed for predicting seven properties for five homologous series. It is shown that most properties can be predicted on experimental error level, using training sets of 10 compounds and a maximum of 2 (non 3-D) descriptors. The exclusion of the 3-D descriptors enhances considerably the applicability of the TQSPRs, and the use of a small number of descriptors reduces the probability of “chance correlations”. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801318y [article] Investigation of the relationships between molecular structure, molecular descriptors, and physical properties [texte imprimé] / Inga Paster, Auteur ; Shacham, Mordechai, Auteur ; Neima Brauner, Auteur . - 2010 . - pp. 9723–9734. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 21 (Novembre 2009) . - pp. 9723–9734 Mots-clés : Molecular  Structures  Molecular  descriptors  Quantitative  structure  property  relations Résumé : The use of databases containing thousands of molecular descriptors, including 3-D descriptors, for predicting physical properties is discussed. It is shown that the use of 3-D descriptors for property prediction via quantitative structure property relations (QSPR) limits considerably their applicability, as 3-D structure files must be obtained from the same reliable source for all predictive and target compounds. A modified targeted QSPR (TQSPR) algorithm is presented, which includes a new technique for selecting training sets belonging to the homologous series of the target compound (if such compounds are available in the database). The method is employed for predicting seven properties for five homologous series. It is shown that most properties can be predicted on experimental error level, using training sets of 10 compounds and a maximum of 2 (non 3-D) descriptors. The exclusion of the 3-D descriptors enhances considerably the applicability of the TQSPRs, and the use of a small number of descriptors reduces the probability of “chance correlations”. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801318y

Predicting temperature-dependent properties by correlations based on similarities of molecular structures / Shacham, Mordechai in Industrial & engineering chemistry research, Vol. 47 N° 13 (Juillet 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N° 13 (Juillet 2008) . - p. 4496–4504 Titre : Predicting temperature-dependent properties by correlations based on similarities of molecular structures : application to liquid density Type de document : texte imprimé Auteurs : Shacham, Mordechai, Auteur ; Neima Brauner, Auteur ; Haim Shore, Auteur ; Diamanta Benson-Karhi, Auteur Année de publication : 2008 Article en page(s) : p. 4496–4504 Note générale : Bibliogr. p. 4504 Langues : Anglais (eng) Mots-clés : Molecular  structures;  Temperature-dependent  properties;  QS2PR Résumé : A novel method for predicting temperature-dependent properties is presented. The method involves the use of measured property values of predictive compounds that are structurally similar to the target compound, and molecular descriptor values. The quantitative structure−structure−property relationship (QS2PR) is used to model a linear relationship between property values of the target and the predictive compounds. Whenever necessary, response modeling methodology (RMM) can be employed to obtain a nonlinear regression model for representing property data of the predictive compounds. The application of the method is demonstrated under a variety of conditions by prediction of the temperature-dependent liquid-density variation of 1-butene, toluene, n-hexane, and n-heneicosane. It is shown that straightforward application of the proposed method provides predictions with accuracy within the experimental error level. An advantage of the proposed method over other similar prediction models is that it does not require measured property values of the target compound. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie701766m [article] Predicting temperature-dependent properties by correlations based on similarities of molecular structures : application to liquid density [texte imprimé] / Shacham, Mordechai, Auteur ; Neima Brauner, Auteur ; Haim Shore, Auteur ; Diamanta Benson-Karhi, Auteur . - 2008 . - p. 4496–4504. Bibliogr. p. 4504 Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N° 13 (Juillet 2008) . - p. 4496–4504 Mots-clés : Molecular  structures;  Temperature-dependent  properties;  QS2PR Résumé : A novel method for predicting temperature-dependent properties is presented. The method involves the use of measured property values of predictive compounds that are structurally similar to the target compound, and molecular descriptor values. The quantitative structure−structure−property relationship (QS2PR) is used to model a linear relationship between property values of the target and the predictive compounds. Whenever necessary, response modeling methodology (RMM) can be employed to obtain a nonlinear regression model for representing property data of the predictive compounds. The application of the method is demonstrated under a variety of conditions by prediction of the temperature-dependent liquid-density variation of 1-butene, toluene, n-hexane, and n-heneicosane. It is shown that straightforward application of the proposed method provides predictions with accuracy within the experimental error level. An advantage of the proposed method over other similar prediction models is that it does not require measured property values of the target compound. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie701766m

Quantitative structure−property relationships for prediction of phase equilibrium related properties / Shacham, Mordechai in Industrial & engineering chemistry research, Vol. 49 N° 2 (Janvier 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 2 (Janvier 2010) . - pp 900–912 Titre : Quantitative structure−property relationships for prediction of phase equilibrium related properties Type de document : texte imprimé Auteurs : Shacham, Mordechai, Auteur ; Cholakov, Georgi St., Auteur ; Stateva, Roumiana P., Auteur Année de publication : 2010 Article en page(s) : pp 900–912 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Predicting  vapor  Binary  interaction  Homologous  series  Structure  property  Phase  equilibrium. Résumé : In this work, novel techniques for predicting vapor pressure and binary interaction coefficients for homologous series are developed based on the previously proposed targeted quantitative structure−property relationship (TQSPR) and QS2PR methods. For predicting vapor pressure variation as a function of temperature, a two-reference compound (TRC) QSPR method is suggested. This method uses two, structurally similar predictive compounds with available vapor pressure data to predict point by point the vapor pressure or the saturation temperature of a target compound. For the target compound, only structural information is required. The two variants of the method were applied to several homologous series. They demonstrate prediction of vapor pressure within experimental uncertainty, depending on the level of similarity between the predictive compounds and the target compound. A targeted QSPR method for prediction of the binary interaction coefficients (kij) in cubic equations of state for a compound with the members of its homologous series is also presented. The coefficients for the Soave−Redlich−Kwong and Peng−Robinson equations, used to test the method, were reproduced within the deviation of those obtained from regressed experimental data. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900807j [article] Quantitative structure−property relationships for prediction of phase equilibrium related properties [texte imprimé] / Shacham, Mordechai, Auteur ; Cholakov, Georgi St., Auteur ; Stateva, Roumiana P., Auteur . - 2010 . - pp 900–912. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 2 (Janvier 2010) . - pp 900–912 Mots-clés : Predicting  vapor  Binary  interaction  Homologous  series  Structure  property  Phase  equilibrium. Résumé : In this work, novel techniques for predicting vapor pressure and binary interaction coefficients for homologous series are developed based on the previously proposed targeted quantitative structure−property relationship (TQSPR) and QS2PR methods. For predicting vapor pressure variation as a function of temperature, a two-reference compound (TRC) QSPR method is suggested. This method uses two, structurally similar predictive compounds with available vapor pressure data to predict point by point the vapor pressure or the saturation temperature of a target compound. For the target compound, only structural information is required. The two variants of the method were applied to several homologous series. They demonstrate prediction of vapor pressure within experimental uncertainty, depending on the level of similarity between the predictive compounds and the target compound. A targeted QSPR method for prediction of the binary interaction coefficients (kij) in cubic equations of state for a compound with the members of its homologous series is also presented. The coefficients for the Soave−Redlich−Kwong and Peng−Robinson equations, used to test the method, were reproduced within the deviation of those obtained from regressed experimental data. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900807j