Predicting Polyethylene Molecular Weight and Composition Distributions Obtained Using a Multi-Site Catalyst in a Gas-Phase Lab-Scale Reactor,Macromolecular Theory and Simulations

当前位置： X-MOL 学术 › Macromol. Theor. Simul. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Predicting Polyethylene Molecular Weight and Composition Distributions Obtained Using a Multi-Site Catalyst in a Gas-Phase Lab-Scale Reactor
Macromolecular Theory and Simulations ( IF 1.8 ) Pub Date : 2021-01-26 , DOI: 10.1002/mats.202000079
Jennifer P. Aiello ₁ , Yan Jiang ₂ , Joseph A. Moebus ₂ , Brian R. Greenhalgh ₂ , Kimberley B. McAuley ₁

Affiliation

A dynamic model is developed to predict detailed chain-length and comonomer incorporation behavior during gas-phase ethylene/hexene copolymerization using a supported hafnocene catalyst. The multi-site catalyst results in a copolymer with a broad orthogonal composition distribution (BOCD) where the high molecular-weight tail has high hexene incorporation. The model relies on gel permeation chromatography measurements obtained using multiple detectors (GPC-4D), so that the composition of the copolymer is determined for different chain-length fractions. Chain-length distributions are discretized into bins so that comparisons can be made between GPC-4D data and model predictions. Parameter estimation is aided by an estimability-ranking procedure and a mean-squared-error selection criterion to determine that 22 of 36 model parameters can be estimated using product characterization and reactor operating data from 10 semi-batch reactor runs. An additional 4 runs are used for model validation, confirming the predictive power of the model. The proposed model can aid the selection of reactor operating conditions to achieve targeted copolymer properties.

中文翻译：

预测在气相实验室规模反应器中使用多站点催化剂获得的聚乙烯分子量和组成分布

建立了动力学模型，以预测使用负载的f茂催化剂在气相乙烯/己烯共聚过程中的详细链长和共聚单体掺入行为。多中心催化剂产生具有宽正交组成分布（BOCD）的共聚物，其中高分子量尾部具有高己烯掺入。该模型依赖于使用多个检测器（GPC-4D）获得的凝胶渗透色谱法测量值，因此可针对不同链长级分确定共聚物的组成。链长分布离散化为仓，以便可以在GPC-4D数据和模型预测之间进行比较。参数估计由可估计性排序程序和均方误差选择标准确定，可以确定使用36个模型参数中的22个可以使用产品特征和来自10个半间歇反应堆运行的反应堆操作数据进行估计。另外的4次运行用于模型验证，确认了模型的预测能力。所提出的模型可以帮助选择反应器的操作条件以实现目标共聚物的性能。

更新日期：2021-01-26

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11