Metal-organic frameworks as kinetic modulators for branched selectivity in hydroformylation.
Bauer, Gerald; Ongari, Daniele; Tiana, Davide; Gäumann, Patrick; Rohrbach, Thomas; Pareras, Gerard; Tarik, Mohamed; Smit, Berend; Ranocchiari, Marco
Date:
2020-02-26
Copyright:
© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Citation:
Bauer, G., Ongari, D., Tiana, D., Gäumann, P., Rohrbach, T., Pareras, G., Tarik, M., Smit, B. and Ranocchiari, M. (2020) 'Metal-organic frameworks as kinetic modulators for branched selectivity in hydroformylation', Nature Communications, 11(1), 1059 (8 pp). doi: 10.1038/s41467-020-14828-6
Abstract:
Finding heterogeneous catalysts that are superior to homogeneous ones for selective catalytic transformations is a major challenge in catalysis. Here, we show how micropores in metal-organic frameworks (MOFs) push homogeneous catalytic reactions into kinetic regimes inaccessible under standard conditions. Such property allows branched selectivity up to 90% in the Co-catalysed hydroformylation of olefins without directing groups, not achievable with existing catalysts. This finding has a big potential in the production of aldehydes for the fine chemical industry. Monte Carlo and density functional theory simulations combined with kinetic models show that the micropores of MOFs with UMCM-1 and MOF-74 topologies increase the olefins density beyond neat conditions while partially preventing the adsorption of syngas leading to high branched selectivity. The easy experimental protocol and the chemical and structural flexibility of MOFs will attract the interest of the fine chemical industries towards the design of heterogeneous processes with exceptional selectivity.
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