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Models for Understanding Divergent Reactivity in Lewis Acid-Catalyzed Transformations of Carbonyls and Olefins
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Carbonyl-ene, Prins and carbonyl-olefin metathesis reactions represent powerful strategies for carbon-carbon bond formation relying on Lewis acid catalysts. Although common Lewis acids are able to provide efficient activation, the reactions often proceed with low regio-, or chemoselectivity while high selectivity frequently requires the use of well-designed metal-ligand complexes. Here we demonstrate that simple Lewis acids including Me2AlCl, FeCl3, and SnCl4 can show remarkable selectivity in dif-ferentiating between distinct transformations of carbonyl and olefin functional groups resulting in either carbonyl-ene or carbonyl-olefin metathesis products. Specifically, we report the development of predictive multivariate linear regression models that rely on kinetic and thermodynamic information obtained in DFT calculations to gain important insights into the complex potential energy surfaces (PES) of these competing reaction paths. The presented results further our understanding of Lewis acid reactivity and suggest that even simple Lewis acids have the potential to function as highly selective catalysts.
American Chemical Society (ACS)
Title: Models for Understanding Divergent Reactivity in Lewis Acid-Catalyzed Transformations of Carbonyls and Olefins
Description:
Carbonyl-ene, Prins and carbonyl-olefin metathesis reactions represent powerful strategies for carbon-carbon bond formation relying on Lewis acid catalysts.
Although common Lewis acids are able to provide efficient activation, the reactions often proceed with low regio-, or chemoselectivity while high selectivity frequently requires the use of well-designed metal-ligand complexes.
Here we demonstrate that simple Lewis acids including Me2AlCl, FeCl3, and SnCl4 can show remarkable selectivity in dif-ferentiating between distinct transformations of carbonyl and olefin functional groups resulting in either carbonyl-ene or carbonyl-olefin metathesis products.
Specifically, we report the development of predictive multivariate linear regression models that rely on kinetic and thermodynamic information obtained in DFT calculations to gain important insights into the complex potential energy surfaces (PES) of these competing reaction paths.
The presented results further our understanding of Lewis acid reactivity and suggest that even simple Lewis acids have the potential to function as highly selective catalysts.
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