Selective Alkyne Hydrogenation over Nano-metal Systems: Closing the Gap between Model and Real Catalysts for Industrial Applications
The relationship between catalytic response and properties of the active phase is difficult to establish in classical heterogeneous catalysis due to the number of variables that can affect catalytic performance. Ultrahigh-vacuum surface methods applied to model catalyst surfaces are useful...
| Main Authors: | , , |
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| Format: | Article |
| Language: | deu |
| Published: |
Swiss Chemical Society
2012-09-01
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| Series: | CHIMIA |
| Subjects: | |
| Online Access: | https://www.chimia.ch/chimia/article/view/5267 |
| Summary: | The relationship between catalytic response and properties of the active phase is difficult to establish in classical heterogeneous catalysis due to the number of variables that can affect catalytic performance. Ultrahigh-vacuum surface methods applied to model catalyst surfaces are
useful tools to assess fundamental issues related to catalytic processes but they are limited by the significant differences with catalysts in the working state. In an attempt to overcome this issue, (unsupported) nano-metal systems with controlled size and shape have been synthesized and
tested in selective alkyne hydrogenation. The results revealed a dependency of nano-particles (NPs) morphology (size and shape) and allowed the identification of the active sites for this type of reaction. The nature of the stabilizer (steric and electrostatic stabilization) used in the NPs
preparation has been shown to influence catalytic performance. The tailored active phase was subsequently immobilized on suitable nano- and micro-structured inorganic (e.g. 3D sintered metal fibers) supports with controlled surface properties in order to corroborate if the results obtained
on the optimized nano-metal systems could be extrapolated to real catalysts. This article highlights the advantages and limitations of the analysis of selective alkyne hydrogenation over nano-metal systems that close the gap between model and real catalysts where the main challenges that lie
ahead are summarized.
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| ISSN: | 0009-4293 2673-2424 |