Ethylene polymerization catalyzed by bridging Ni/Zn heterobimetallics

Hsin Chun Chiu, Arijit Koley, Peter L. Dunn, Ryan J. Hue, Ian A. Tonks

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

The effect of proximal Zn halides on Ni-catalyzed ethylene polymerization is reported in this work. A series of (NON)NiLX (NON = 2,6-bis-((2,6-diisopropylphenyl)imino)methyl phenoxide; LX = methallyl or L = py, X = tolyl, 2-4) ethylene polymerization precatalysts have been synthesized, as well as a heterobimetallic Ni/Zn complex, (NON)Ni(C4H7)ZnBr2 (5). Each precatalyst could be activated (or promoted) by ZnX2 (X = Cl, Br, Et) to polymerize ethylene. In situ recruitment of ZnX2 by the free imine binding pocket of the NON complexes results in the generation of heterobimetallic active species that produce lower Mn polyethylene than monometallic controls. Room temperature ZnX2-promoted polymerizations with these catalysts resulted in bimodal Mn distributions that result from different catalyst speciation: "dangling" imine-ligated ZnX2 species yield higher Mn polymer while N,O-chelated ZnX2 species yield lower Mn polymer. Running polymerizations at higher temperature yields in only lower Mn polymer resulting from exclusive formation of the thermodynamically favored N,O chelated Ni/Zn heterobimetallic. DFT calculations indicate that this bridging bimetallic complex undergoes β-H elimination more facilely than monometallic Ni analogues, resulting in lower molecular weight polymers.

Original languageEnglish (US)
Pages (from-to)5513-5517
Number of pages5
JournalDalton Transactions
Volume46
Issue number17
DOIs
StatePublished - 2017

Bibliographical note

Funding Information:
Financial support was provided by the University of Minnesota (start up funds) and the ACS Petroleum Research Fund (ACS-PRF 54225-DNI3). The Bruker-AXS D8 Venture diffractometer was purchased through a grant from NSF/MRI (1224900) and the University of Minnesota. Equipment purchases for the NMR facility were supported through a grant from the NIH (S10OD011952) with matching funds from the University of Minnesota. Computational resources were provided by the Minnesota Supercomputing Instituted (MSI) at the University of Minnesota. The authors declare no competing financial interests. Ms Xuelan Wen and Prof. Jason D. Goodpaster (UMN) are thanked for computational assistance.

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