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Application of random-pore model to SO2 capture by lime / H. Ale Ebrahim in Industrial & engineering chemistry research, Vol. 49 N° 1 (Janvier 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 1 (Janvier 2010) . - pp. 117–122 Titre : Application of random-pore model to SO2 capture by lime Type de document : texte imprimé Auteurs : H. Ale Ebrahim, Auteur Année de publication : 2010 Article en page(s) : pp. 117–122 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Application--Random-Pore--Model--SO2  Capture--Lime Résumé : Flue gas desulfurization by lime (CaO) is widely used for coal-based power plants. The incomplete conversion of CaO poses a significant problem for such systems. An interesting method for increasing the pore radius of lime by a weak acid has been presented in the literature as a means to solve this problem. In this article, the random-pore model was applied to model the above experimental work successfully. Therefore, the effect of the CaO pore size distribution on the final conversion for SO2 removal can be predicted by this model. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901077b [article] Application of random-pore model to SO2 capture by lime [texte imprimé] / H. Ale Ebrahim, Auteur . - 2010 . - pp. 117–122. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 1 (Janvier 2010) . - pp. 117–122 Mots-clés : Application--Random-Pore--Model--SO2  Capture--Lime Résumé : Flue gas desulfurization by lime (CaO) is widely used for coal-based power plants. The incomplete conversion of CaO poses a significant problem for such systems. An interesting method for increasing the pore radius of lime by a weak acid has been presented in the literature as a means to solve this problem. In this article, the random-pore model was applied to model the above experimental work successfully. Therefore, the effect of the CaO pore size distribution on the final conversion for SO2 removal can be predicted by this model. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901077b