4.8 Article

Accessing and predicting the kinetic profiles of homogeneous catalysts from volcano plots

期刊

CHEMICAL SCIENCE
卷 7, 期 9, 页码 5723-5735

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ROYAL SOC CHEMISTRY
DOI: 10.1039/c6sc01660j

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资金

  1. National Center of Competence in Research (NCCR) Materials' Revolution: Computational Design
  2. Discovery of Novel Materials (MARVEL) of the Swiss National Science Foundation (SNSF)
  3. EPFL

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Volcano plots are frequently used as aids in the search for new heterogeneous and electrochemical catalysts. These tools successfully predict catalytic processes based solely on thermodynamic descriptions, which also capably describe many aspects of the catalytic cycles of homogeneous species. However, homogeneous catalysts also frequently depend upon the kinetic influences brought about by steric interactions to promote or prevent specific chemical reactions. Here, a prototypical transformation facilitated by a homogeneous catalysis, the hydroformylation of an olefin using CO and H-2, is examined to establish the viability of creating kinetic volcano plots and to determine their ability to ascertain the influences steric bulk plays on catalytic cycle energetics. Similar to their thermodynamic counterparts, kinetic volcanoes successfully reproduce many experimentally known facets of the hydroformylation reaction. In contrast to thermodynamic volcanoes, kinetic volcanoes emphasize changes in the height of the different activation barriers brought about by steric interactions. This crucial information, however, comes with considerable computational cost, since the transition states of catalysts bearing large bulky ligands must be identified and characterized. To overcome this drawback, a procedure is proposed that relates a simple steric parameter, the Tolman cone angle, with the descriptors used to create the kinetic volcano plots. In this way, the activation barriers of bulky catalysts can be estimated without requiring expensive transition state computations. These newly derived structure-activity relationship volcano plots represent useful tools for identifying new homogeneous catalysts.

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