Process Modeling for Polyolefin Elastomer Polymerization with an Efficient Method for Kinetic Parameter Estimation

ABSTRACT A steady‐state process model was developed for the solution polymerization of polyolefin elastomers (POE) using a metallocene catalyst system. The proposed model incorporates a comprehensive kinetic scheme and physical property estimations based on the PC‐SAFT EOS, enabling accurate prediction of polymer properties. To address the limitations in traditional parameter fitting, an efficient estimation method based on the Nelder–Mead simplex algorithm was introduced. This optimization method allows direct fitting of pre‐exponential factors and activation energies for each reaction step using plant data, improving the accuracy and speed of kinetic modeling. Model predictions under various operating conditions, including reaction temperature, residence time, and feed molar ratio, showed agreement with industrial data. This approach not only provides a reliable tool for simulating POE production but also offers a general methodology applicable to other catalytic systems with scarce kinetic data.

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Publication Details

Journal
Macromolecular Reaction Engineering
Published
2026-01-20
DOI
https://doi.org/10.1002/mren.70006
Primary Topic
Thermal and Kinetic Analysis
Type
article
Field-Weighted Citation Impact
0.00

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Process Modeling for Polyolefin Elastomer Polymerization with an Efficient Method for Kinetic Parameter Estimation

Shanbao Lai, Muze Hong, Qianqian Qiang, Jiajun Wang et al.
Macromolecular Reaction Engineering
Thermal and Kinetic Analysis
article

Process Modeling for Polyolefin Elastomer Polymerization with an Efficient Method for Kinetic Parameter Estimation

Shanbao Lai, Muze Hong, Qianqian Qiang, Jiajun Wang, Zhitao Li
article en

Abstract

ABSTRACT A steady‐state process model was developed for the solution polymerization of polyolefin elastomers (POE) using a metallocene catalyst system. The proposed model incorporates a comprehensive kinetic scheme and physical property estimations based on the PC‐SAFT EOS, enabling accurate prediction of polymer properties. To address the limitations in traditional parameter fitting, an efficient estimation method based on the Nelder–Mead simplex algorithm was introduced. This optimization method allows direct fitting of pre‐exponential factors and activation energies for each reaction step using plant data, improving the accuracy and speed of kinetic modeling. Model predictions under various operating conditions, including reaction temperature, residence time, and feed molar ratio, showed agreement with industrial data. This approach not only provides a reliable tool for simulating POE production but also offers a general methodology applicable to other catalytic systems with scarce kinetic data.

Macromolecular Reaction Engineering
State Key Laboratory of Chemical Engineering (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
Thermal and Kinetic Analysis
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