4.8 Article

Interrogating selectivity in catalysis using molecular vibrations

期刊

NATURE
卷 507, 期 7491, 页码 210-+

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NATURE PUBLISHING GROUP
DOI: 10.1038/nature13019

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资金

  1. US National Science Foundation [CHE-0749506]
  2. Center for High Performance Computing at the University of Utah
  3. Division Of Chemistry
  4. Direct For Mathematical & Physical Scien [1110599] Funding Source: National Science Foundation

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The delineation of molecular properties that underlie reactivity and selectivity is at the core of physical organic chemistry(1-5), and this knowledge can be used to inform the design of improved synthetic methods or identify new chemical transformations(6-9). For this reason, the mathematical representation of properties affecting reactivity and selectivity trends, that is, molecular parameters, is paramount. Correlations produced by equating these molecular parameters with experimental outcomes are often defined as free-energy relationships and can be used to evaluate the origin of selectivity and to generate new, experimentally testable hypotheses(6,10-12). The premise behind successful correlations of this type is that a systematically perturbed molecular property affects a transition-state interaction between the catalyst, substrate and any reaction components involved in the determination of selectivity(10,11). Classic physical organic molecular descriptors, such as Hammett(4), Taft(3) or Charton(5) parameters, seek to independently probe isolated electronic or steric effects(3-6,13,14). However, these parameters cannot address simultaneous, non-additive variations to more than one molecular property, which limits their utility. Here we report a parameter system based on the vibrational response of a molecule to infrared radiation that can be used to mathematically model and predict selectivity trends for reactions with interlinked steric and electronic effects at positions of interest. The disclosed parameter system is mechanistically derived and should find broad use in the study of chemical and biological systems.

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