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Mechanistic Detail Revealed via Comprehensive Kinetic Modeling of [rac-C2H4(1-indenyl)2ZrMe2]-Catalyzed 1-Hexene Polymerization

Thorough kinetic characterization of single-site olefin polymerization catalysis requires comprehensive, quantitative kinetic modeling of a rich multiresponse data set that includes monomer consumption, molecular weight distributions (MWDs), end group analysis, etc. at various conditions. Herein we...

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Bibliographic Details
Published in:Journal of the American Chemical Society 2010-01, Vol.132 (2), p.558-566
Main Authors: Novstrup, Krista A, Travia, Nicholas E, Medvedev, Grigori A, Stanciu, Corneliu, Switzer, Jeffrey M, Thomson, Kendall T, Delgass, W. Nicholas, Abu-Omar, Mahdi M, Caruthers, James M
Format: Article
Language:English
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Summary:Thorough kinetic characterization of single-site olefin polymerization catalysis requires comprehensive, quantitative kinetic modeling of a rich multiresponse data set that includes monomer consumption, molecular weight distributions (MWDs), end group analysis, etc. at various conditions. Herein we report the results obtained via a comprehensive, quantitative kinetic modeling of all chemical species in the batch polymerization of 1-hexene by rac-C2H4(1-Ind)2ZrMe2 activated with B(C6F5)3. While extensive studies have been published on this catalyst system, the previously acknowledged kinetic mechanism is unable to predict the MWD. We now show it is possible to predict the entire multiresponse data set (including the MWDs) using a kinetic model featuring a catalytic event that renders 43% of the catalyst inactive for the duration of the polymerization. This finding has significant implications regarding the behavior of the catalyst and the polymer produced and is potentially relevant to other single-site polymerization catalysts, where it would have been undetected as a result of incomplete kinetic modeling. In addition, comprehensive kinetic modeling of multiresponse data yields robust values of rate constants (uncertainties of less than 16% for this catalyst) for future use in developing predictive structure−activity relationships.
ISSN:0002-7863
1520-5126
DOI:10.1021/ja906332r