Documents disponibles écrits par cet auteur

Selective extraction of copper, mercury, silver, and palladium ions from water using hydrophobic ionic liquids / Nicolas Papaiconomou in Industrial & engineering chemistry research, Vol. 47 n°15 (Août 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 n°15 (Août 2008) . - p. 5080–5086 Titre : Selective extraction of copper, mercury, silver, and palladium ions from water using hydrophobic ionic liquids Type de document : texte imprimé Auteurs : Nicolas Papaiconomou, Auteur ; Jong Min Lee, Auteur ; Justin Salminen, Auteur Année de publication : 2008 Article en page(s) : p. 5080–5086 Note générale : Bibliogr. p. 5085-5086 Langues : Anglais (eng) Mots-clés : Dilute  metal  ions  Ionic  liquids Résumé : Extraction of dilute metal ions from water was performed near room temperature with a variety of ionic liquids. Distribution coefficients are reported for fourteen metal ions extracted with ionic liquids containing cations 1-octyl-4-methylpyridinium[4MOPYR]+, 1-methyl-1-octylpyrrolidinium[MOPYRRO]+, or 1-methyl-1-octylpiperidinium[MOPIP]+ and anions tetrafluoroborate[BF4]+, trifluoromethyl sulfonate[TfO]+, or nonafluorobutyl sulfonate[NfO]+. Ionic liquids containing octylpyridinium cations are good for extracting mercury ions. However, other metal ions were not significantly extracted by any of these ionic liquids. Extractions were also performed with four new task-specific ionic liquids. When these liquids contain a disulfide functional group, they are efficient and selective for mercury and copper, whereas those containing a nitrile functional group are efficient and selective for silver and palladium. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie0706562 [article] Selective extraction of copper, mercury, silver, and palladium ions from water using hydrophobic ionic liquids [texte imprimé] / Nicolas Papaiconomou, Auteur ; Jong Min Lee, Auteur ; Justin Salminen, Auteur . - 2008 . - p. 5080–5086. Bibliogr. p. 5085-5086 Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 n°15 (Août 2008) . - p. 5080–5086 Mots-clés : Dilute  metal  ions  Ionic  liquids Résumé : Extraction of dilute metal ions from water was performed near room temperature with a variety of ionic liquids. Distribution coefficients are reported for fourteen metal ions extracted with ionic liquids containing cations 1-octyl-4-methylpyridinium[4MOPYR]+, 1-methyl-1-octylpyrrolidinium[MOPYRRO]+, or 1-methyl-1-octylpiperidinium[MOPIP]+ and anions tetrafluoroborate[BF4]+, trifluoromethyl sulfonate[TfO]+, or nonafluorobutyl sulfonate[NfO]+. Ionic liquids containing octylpyridinium cations are good for extracting mercury ions. However, other metal ions were not significantly extracted by any of these ionic liquids. Extractions were also performed with four new task-specific ionic liquids. When these liquids contain a disulfide functional group, they are efficient and selective for mercury and copper, whereas those containing a nitrile functional group are efficient and selective for silver and palladium. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie0706562

Stochastic nonlinear optimization for robust design of catalysts / Chang Jun Lee in Industrial & engineering chemistry research, Vol. 50 N° 7 (Avril 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 7 (Avril 2011) . - pp. 3938–3946 Titre : Stochastic nonlinear optimization for robust design of catalysts Type de document : texte imprimé Auteurs : Chang Jun Lee, Auteur ; Vinay Prasad, Auteur ; Jong Min Lee, Auteur Année de publication : 2011 Article en page(s) : pp. 3938–3946 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Optimal  catalyst Résumé : Computational methods for designing an optimal catalyst have recently received much attention, especially for energy-related applications. What is lacking in the previous methods is an explicit method to handle uncertainties in the complex models used, so that a robust design is achieved. This work proposes a stochastic optimization method for designing a robust catalyst. In particular, reactions involved in catalytic decomposition of ammonia are presented, and uncertainties associated with experimental determination of kinetic parameters are represented as exogenous variables with assumed probability distributions. The problem is formulated in terms of finding the optimal binding energies that maximize conversion in a microreactor. The resulting stochastic optimization problem is nonlinear, and involves the expectation operator as well as integration in the objective function. This difficult optimization problem is tackled by a population sample based approach, referred to as particle swarm optimization. The results show that the value of solving the stochastic problem is significant, and that it can provide a more robust solution compared to the certainty equivalence approach. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie102103w [article] Stochastic nonlinear optimization for robust design of catalysts [texte imprimé] / Chang Jun Lee, Auteur ; Vinay Prasad, Auteur ; Jong Min Lee, Auteur . - 2011 . - pp. 3938–3946. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 7 (Avril 2011) . - pp. 3938–3946 Mots-clés : Optimal  catalyst Résumé : Computational methods for designing an optimal catalyst have recently received much attention, especially for energy-related applications. What is lacking in the previous methods is an explicit method to handle uncertainties in the complex models used, so that a robust design is achieved. This work proposes a stochastic optimization method for designing a robust catalyst. In particular, reactions involved in catalytic decomposition of ammonia are presented, and uncertainties associated with experimental determination of kinetic parameters are represented as exogenous variables with assumed probability distributions. The problem is formulated in terms of finding the optimal binding energies that maximize conversion in a microreactor. The resulting stochastic optimization problem is nonlinear, and involves the expectation operator as well as integration in the objective function. This difficult optimization problem is tackled by a population sample based approach, referred to as particle swarm optimization. The results show that the value of solving the stochastic problem is significant, and that it can provide a more robust solution compared to the certainty equivalence approach. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie102103w