On the performance of Fe-Cu-ZSM-5 catalyst for the selective catalytic reduction of NO with NH3: the influence of preparation method

Autor: Houda Jouini, Teresa Blasco, Gérard Delahay, Mourad Mhamdi, Imène Mejri, Joaquin Martinez-Ortigosa
Přispěvatelé: Laboratoire de Chimie des Matériaux et Catalyse, Faculté des Sciences Mathématiques, Physiques et Naturelles de Tunis (FST), Université de Tunis El Manar (UTM)-Université de Tunis El Manar (UTM)-Département de Chimie, Institut Charles Gerhardt Montpellier - Institut de Chimie Moléculaire et des Matériaux de Montpellier (ICGM ICMMM), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut de Chimie du CNRS (INC)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Research on Chemical Intermediates
Research on Chemical Intermediates, Springer Verlag, 2019, 45 (3), pp.1057-1072. ⟨10.1007/s11164-018-3658-8⟩
ISSN: 0922-6168
1568-5675
DOI: 10.1007/s11164-018-3658-8⟩
Popis: The selective catalytic reduction of NO with ammonia (NH3-SCR) in the presence of H2O was studied over a series of Fe-Cu-ZSM-5 catalysts prepared by solid-state ion exchange (SSIE), aqueous ion exchange and impregnation methods. The prepared samples were characterized by various techniques (ICP-AES, N2 physisorption at 77 K, XRD, STEM-EDX, XPS, H2-TPR and DRS UV–vis) to investigate the effect of the preparation method on the activity, texture, structure and metal speciation of the studied catalysts. It was found that the aqueous ion exchange method induced a significant metal loss during the preparation procedure but without any activity deterioration of the catalyst which encloses highly dispersed metal species. The catalysts prepared by SSIE and impregnation showed the highest metal contents and a large number of oxide aggregates leading to an activity decline at high reaction temperatures due to the ammonia oxidation phenomenon.
Databáze: OpenAIRE