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Evaluation of group-contribution methods to predict VLE and odor intensity of fragrances / Miguel A. Teixeira in Industrial & engineering chemistry research, Vol. 50 N° 15 (Août 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 15 (Août 2011) . - pp. 9390-9402 Titre : Evaluation of group-contribution methods to predict VLE and odor intensity of fragrances Type de document : texte imprimé Auteurs : Miguel A. Teixeira, Auteur ; Oscar Rodriguez, Auteur ; Fatima L. Mota, Auteur Année de publication : 2011 Article en page(s) : pp. 9390-9402 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Odor  Group  contribution  method Résumé : Several predictive GE methods based on the group-contribution concept have been tested for prediction of multicomponent vapor-liquid equilibria (VLE) of fragrance mixtures. The evaluation covered 24 binary, 20 ternary, and 21 quaternary mixtures combining six different fragrances typically used in perfume formulation and ethanol as the solvent. The selected predictive methods are the original UNIFAC (updated to the last revision), the UNIFAC-Dortmund, the ASOG, and the A-UNIFAC. The equilibrium compositions were experimentally measured at 23 °C by headspace gas chromatography (HS-GC). For each liquid composition, the corresponding experimental and predicted vapor compositions were compared. This study confirmed that the UNIFAC method is the best predictive model for prediction of VLE, while the A-UNIFAC performed poorer than other evaluated methods for the mixtures studied in this work. Moreover, from the vapor composition the odor intensity and character of the fragrance mixtures was calculated using a previous developed model which considers the Stevens' power law for the olfaction intensity scale and the stronger component model for quality perception. In this way, the odor intensity and character of fragrance mixtures was predicted and compared to experimental and sensorial evaluations. From this work it can be concluded that the UNIFAC and UNIFAC-Dortmund methods allow obtaining optimal predictions of the character of the fragrance mixtures with an agreement of 95.4% when compared to experimental measurements. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24395884 [article] Evaluation of group-contribution methods to predict VLE and odor intensity of fragrances [texte imprimé] / Miguel A. Teixeira, Auteur ; Oscar Rodriguez, Auteur ; Fatima L. Mota, Auteur . - 2011 . - pp. 9390-9402. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 15 (Août 2011) . - pp. 9390-9402 Mots-clés : Odor  Group  contribution  method Résumé : Several predictive GE methods based on the group-contribution concept have been tested for prediction of multicomponent vapor-liquid equilibria (VLE) of fragrance mixtures. The evaluation covered 24 binary, 20 ternary, and 21 quaternary mixtures combining six different fragrances typically used in perfume formulation and ethanol as the solvent. The selected predictive methods are the original UNIFAC (updated to the last revision), the UNIFAC-Dortmund, the ASOG, and the A-UNIFAC. The equilibrium compositions were experimentally measured at 23 °C by headspace gas chromatography (HS-GC). For each liquid composition, the corresponding experimental and predicted vapor compositions were compared. This study confirmed that the UNIFAC method is the best predictive model for prediction of VLE, while the A-UNIFAC performed poorer than other evaluated methods for the mixtures studied in this work. Moreover, from the vapor composition the odor intensity and character of the fragrance mixtures was calculated using a previous developed model which considers the Stevens' power law for the olfaction intensity scale and the stronger component model for quality perception. In this way, the odor intensity and character of fragrance mixtures was predicted and compared to experimental and sensorial evaluations. From this work it can be concluded that the UNIFAC and UNIFAC-Dortmund methods allow obtaining optimal predictions of the character of the fragrance mixtures with an agreement of 95.4% when compared to experimental measurements. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24395884

Perfumery Radar: / Miguel A. Teixeira in Industrial & engineering chemistry research, Vol. 49 N° 22 (Novembre 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 22 (Novembre 2010) . - pp. 11764–11777 Titre : Perfumery Radar: : a predictive tool for perfume family classification Type de document : texte imprimé Auteurs : Miguel A. Teixeira, Auteur ; Oscar Rodriguez, Auteur ; Alirio E. Rodrigues, Auteur Année de publication : 2011 Article en page(s) : pp. 11764–11777 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Perfumery  radar Résumé : The classification of perfumes into olfactory families has been done for years on the basis of sensorial analysis or odor descriptors, but none of these methods has attained universal acceptance. In this work is presented a methodology called perfumery radar (PR) that predicts the classification of perfumes using the olfactive families that perfumers use. The PR introduces some scientific basis, reducing the arbitrariness of perfume classification to the empirical classification of pure odorants. The odor intensity of pure fragrances in a liquid mixture is predicted using the odor value concept, considering molecular interactions between components. Radar plots are used to represent olfactory families and transform quantitative information into qualitative. Perfumery radars have been obtained for several commercial perfumes and compared with existing experimental classifications. Another validation using headspace GC analysis was also performed with satisfactory results. It is shown that the PR methodology is able to predict the primary olfactive family of perfumes, according to the experimental classification given by perfumers. The prediction of secondary and tertiary families agreed with some of the empirical classifications in most cases, although there was little agreement among those at this level. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101161v [article] Perfumery Radar: : a predictive tool for perfume family classification [texte imprimé] / Miguel A. Teixeira, Auteur ; Oscar Rodriguez, Auteur ; Alirio E. Rodrigues, Auteur . - 2011 . - pp. 11764–11777. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 22 (Novembre 2010) . - pp. 11764–11777 Mots-clés : Perfumery  radar Résumé : The classification of perfumes into olfactory families has been done for years on the basis of sensorial analysis or odor descriptors, but none of these methods has attained universal acceptance. In this work is presented a methodology called perfumery radar (PR) that predicts the classification of perfumes using the olfactive families that perfumers use. The PR introduces some scientific basis, reducing the arbitrariness of perfume classification to the empirical classification of pure odorants. The odor intensity of pure fragrances in a liquid mixture is predicted using the odor value concept, considering molecular interactions between components. Radar plots are used to represent olfactory families and transform quantitative information into qualitative. Perfumery radars have been obtained for several commercial perfumes and compared with existing experimental classifications. Another validation using headspace GC analysis was also performed with satisfactory results. It is shown that the PR methodology is able to predict the primary olfactive family of perfumes, according to the experimental classification given by perfumers. The prediction of secondary and tertiary families agreed with some of the empirical classifications in most cases, although there was little agreement among those at this level. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101161v