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Mapping the Structure–Property Space of Bimodal Polyethylenes Using Response Surface Methods. Part 1: Digital Data Investigation

A new method is proposed to study the multidimensional structure–property space of bimodal ethylene/1‐olefin copolymers using fundamental polymerization models and response surface methods. The fundamental polymerization models describe how the polymer microstructure depends on polymerization condit...

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Bibliographic Details
Published in:Macromolecular reaction engineering 2018-08, Vol.12 (4), p.n/a
Main Authors: DesLauriers, Paul J., Fodor, Jeff S., Soares, João B. P., Mehdiabadi, Saeid
Format: Article
Language:English
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Summary:A new method is proposed to study the multidimensional structure–property space of bimodal ethylene/1‐olefin copolymers using fundamental polymerization models and response surface methods. The fundamental polymerization models describe how the polymer microstructure depends on polymerization conditions, in particular how the short chain branching frequency varies across the molecular weight distribution. Statistical design of experiment techniques combined with response surface methods generates the minimum number of digital experiments needed to estimate the parameters for a forward model. The polymer microstructural data are combined with empirical equations to calculate polymer density and the primary structural parameter to quantify the presence of tie molecules in the polymer. This procedure links polymerization conditions to polymer microstructure and properties using the forward model. More importantly, the forward model can be reversed to determine which polymerization conditions are needed to make polymers with a given set of properties. A new method is proposed to link polymerization conditions to the structure‐property space of bimodal ethylene/1‐olefin copolymers. More importantly, this method may be reversed to determine which polymerization conditions are needed to make polymers with a given set of properties.
ISSN:1862-832X
1862-8338
DOI:10.1002/mren.201700066