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Updated: Apr 21, 2026
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Ethylene Polymerizations Using Parallel Pressure Reactors and a Kinetic Analysis of Chain Transfer Polymerization
Published on: November 27, 2015
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Computational and synthetic studies with tetravinylethylenes
Erik J Lindeboom1, Anthony C Willis, Michael N Paddon-Row
1Research School of Chemistry, The Australian National University , Canberra ACT 0200, Australia.
The Journal of Organic Chemistry
|November 11, 2014
Summary
Computational studies reveal new details about tetravinylethylene compounds. High-level calculations predict structures and reaction outcomes for this understudied chemical class.
Area of Science:
- Organic Chemistry
- Computational Chemistry
Background:
- Tetravinylethylene compounds are an understudied class of hydrocarbons.
- Limited experimental and computational data exist for their structures and reactivity.
Purpose of the Study:
- To provide fresh insights into the neglected tetravinylethylene class of compounds.
- To computationally predict and explain the structures and reaction outcomes of the parent hydrocarbon.
Main Methods:
- High-level composite ab initio molecular orbital (MO) G4(MP2) computational studies.
- Exploratory reaction analysis.
Main Results:
- Detailed predictions of tetravinylethylene structures.
- Explanation of the outcomes of exploratory reactions.
- Validation of computational methods for this compound class.
Conclusions:
- Computational methods, specifically G4(MP2), are effective for studying tetravinylethylene.
- This work lays the groundwork for further experimental and computational investigations.
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