Experimental and Computational
Investigation of the
Mechanism of Carbon Dioxide/Cyclohexene Oxide Copolymerization Using
a Dizinc Catalyst
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Abstract
A detailed study of the mechanism by which a dizinc catalyst
copolymerizes
cyclohexene oxide and carbon dioxide is presented. The catalyst, previously
published by Williams et al. (Angew. Chem. Int. Ed. 2009, 48, 931), shows high activity under just
1 bar pressure of CO<sub>2</sub>. This work applies <i>in situ</i> attenuated total reflectance infrared spectroscopy (ATR-FTIR) to
study changes to the catalyst structure on reaction with cyclohexene
oxide and, subsequently, with carbon dioxide. A computational investigation,
using DFT with solvation corrections, is used to calculate the relative
free energies for various transition states and intermediates in the
cycle for alternating copolymerization catalyzed by this dinuclear
complex. Two potentially competing side reactions, sequential epoxide
enchainment and sequential carbon dioxide enchainment are also investigated.
The two side-reactions are shown to be thermodynamically disfavored,
rationalizing the high selectivity exhibited in experimental studies
using <b>1</b>. Furthermore, the DFT calculations show that
the rate-determining step is the nucleophilic attack of the coordinated
epoxide molecule by the zinc-bound carbonate group in line with previous
experimental findings (ΔΔ<i>G</i><sub>353</sub> = 23.5 kcal/mol; Δ<i>G</i><sup>‡</sup><sub>353</sub> = 25.7 kcal/mol). Both <i>in situ</i> spectroscopy
and DFT calculations indicate that just one polymer chain is initiated
per dizinc catalyst molecule. The catalyst adopts a “bowl”
shape conformation, whereby the acetate group coordinated on the concave
face is a spectator ligand while that coordinated on the convex face
is the initiating group. The spectator carboxylate group plays an
important role in the catalytic cycle, counter-balancing chain growth
on the opposite face. The DFT was used to predict the activities of
two new catalysts, good agreement between experimental turn-over-numbers
and DFT predictions were observed