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Catalytic behaviour of the Cu(i)/L/TEMPO system for aerobic oxidation of alcohols - a kinetic and predictive model.

Afnan Al-HunaitiBatool Abu-RadahaDarren WraithTimo Repo
Published in: RSC advances (2022)
Here, we disclose a new copper(i)-Schiff base complex series for selective oxidation of primary alcohols to aldehydes under benign conditions. The catalytic protocol involves 2,2,6,6-tetramethylpiperidine- N -oxyl (TEMPO), N -methylimidazole (NMI), ambient air, acetonitrile, and room temperature. This system provides a straightforward and rapid pathway to a series of Schiff bases, particularly, the copper(i) complexes bearing the substituted (furan-2-yl)imine bases N -(4-fluorophenyl)-1-(furan-2-yl)methanimine (L2) and N -(2-fluoro-4-nitrophenyl)-1-(furan-2-yl)methanimine (L4) have shown excellent yields. Both benzylic and aliphatic alcohols were converted to aldehydes selectively with 99% yield (in 1-2 h) and 96% yield (in 16 h). The mechanistic studies via kinetic analysis of all components demonstrate that the ligand type plays a key role in reaction rate. The basicity of the ligand increases the electron density of the metal center, which leads to higher oxidation reactivity. The Hammett plot shows that the key step does not involve H-abstraction. Additionally, a generalized additive model (GAM, including random effect) showed that it was possible to correlate reaction composition with catalytic activity, ligand structure, and substrate behavior. This can be developed in the form of a predictive model bearing in mind numerous reactions to be performed or in order to produce a massive data-set of this type of oxidation reaction. The predictive model will act as a useful tool towards understanding the key steps in catalytic oxidation through dimensional optimization while reducing the screening of statistically poor active catalysis.
Keyphrases
  • electron transfer
  • room temperature
  • hydrogen peroxide
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  • machine learning
  • particulate matter
  • ionic liquid
  • high intensity
  • crystal structure
  • sensitive detection
  • electron microscopy