Particle Growth during the Polymerization of Olefins on Supported Catalysts. Part 2: Current Experimental Understanding and Modeling Progresses on Particle Fragmentation, Growth, and Morphology Development
The morphology of the growing polymer particles is important in olefin polymerisation on supported catalysts. It has a significant impact on the rate of mass and energy transport, and consequently on the polymerisation rate, comonomer incorporation, and the molecular weight distribution. The ability...
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Veröffentlicht in: | Macromolecular reaction engineering 2018-02, Vol.12 (1), p.n/a |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The morphology of the growing polymer particles is important in olefin polymerisation on supported catalysts. It has a significant impact on the rate of mass and energy transport, and consequently on the polymerisation rate, comonomer incorporation, and the molecular weight distribution. The ability to quantify the evolution of morphology during the polymerisation process à priori would therefore be quite useful. The morphology itself is a direct product of the fragmentation step and concurrent/subsequent expansion of the particle, both caused by the build‐up and dissipation of hydraulic forces due to the accumulation of polymer in the particle. It is influenced by the initial morphology of the support, as well as the reaction conditions and local polymer properties. The single particle models developed to describe the morphology evolution in a growing particle are reviewed here. The main assumptions, abilities, and limitations of the models are evaluated and the issues which face developing a completely predictive model are finally discussed. Despite some very interesting attempts at morphology modelling in recent years, significant progress still needs to be made in order to develop a fully predictive model of the sort.
The single particle models developed to describe the morphology evolution in a growing particle during the course of olefin polymerization on supported catalysts are reviewed here. The main assumptions, abilities, and limitations of the models are evaluated and the issues which face developing a completely predictive model are finally discussed. |
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ISSN: | 1862-832X 1862-8338 |
DOI: | 10.1002/mren.201700027 |