Optimal compositional and structural design of a LaMnO3/ZrO2/Pd-based catalyst for methane combustion

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Title: Optimal compositional and structural design of a LaMnO3/ZrO2/Pd-based catalyst for methane combustion
Authors: Civera, A.1, Negro, G.1, Specchia, S. stefania.specchia@polito.it, Saracco, G.1, Specchia, V.1
Source: Catalysis Today. Feb2005, Vol. 100 Issue 3/4, p275-281. 7p.
Subjects: Perovskite, Oxide minerals, Palladium, Catalysts
Abstract: Abstract: The aim of this work was to identify the optimum synthesis conditions and the most effective technique for noble metal deposition in a perovskite/palladium-based catalyst for natural gas combustion. The solution combustion synthesis (SCS) of perovskite/zirconia-based materials was investigated, by starting from metal nitrates/glycine mixtures. Characterization and catalytic activity tests were performed on as-prepared powders and then repeated after calcination for 2h at 900°C in calm air. Calcination appeared to be beneficial in that, despite lowering the specific surface area, it promoted the simultaneous crystallization of both LaMnO3 and ZrO2 and the half-conversion temperature (T 50), regarded as an index of catalytic activity, was lowered. Two phases, both active towards methane oxidation – lanthanum manganate and palladium oxide – were combined so as to evaluate their synergism in terms of catalytic activity. Pd was therefore added either via incipient wetness impregnation on LaMnO3·2ZrO2 or through a one-step SCS-based route. Characterization and catalytic activity tests followed suit. Optimal composition and preparation routes were found: T 50 was lowered from 507°C – pure LaMnO3 prepared via SCS – to 432°C attained with a 2% (w/w) Pd load on pre-calcined LaMnO3·2ZrO2. [Copyright &y& Elsevier]
Copyright of Catalysis Today is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Catalysis+Today%22">Catalysis Today</searchLink>. Feb2005, Vol. 100 Issue 3/4, p275-281. 7p.
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  Data: Abstract: The aim of this work was to identify the optimum synthesis conditions and the most effective technique for noble metal deposition in a perovskite/palladium-based catalyst for natural gas combustion. The solution combustion synthesis (SCS) of perovskite/zirconia-based materials was investigated, by starting from metal nitrates/glycine mixtures. Characterization and catalytic activity tests were performed on as-prepared powders and then repeated after calcination for 2h at 900°C in calm air. Calcination appeared to be beneficial in that, despite lowering the specific surface area, it promoted the simultaneous crystallization of both LaMnO3 and ZrO2 and the half-conversion temperature (T 50), regarded as an index of catalytic activity, was lowered. Two phases, both active towards methane oxidation – lanthanum manganate and palladium oxide – were combined so as to evaluate their synergism in terms of catalytic activity. Pd was therefore added either via incipient wetness impregnation on LaMnO3·2ZrO2 or through a one-step SCS-based route. Characterization and catalytic activity tests followed suit. Optimal composition and preparation routes were found: T 50 was lowered from 507°C – pure LaMnO3 prepared via SCS – to 432°C attained with a 2% (w/w) Pd load on pre-calcined LaMnO3·2ZrO2. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Catalysis Today is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.cattod.2004.09.062
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              Text: Feb2005
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