The effect of micro and macro mixing in continuous polymer reactor systems on long chain branching frequency and structure

本课题旨在建立一种预测高分子分子长链分支结构和频率的数学模拟方法。聚合材料通常在搅拌槽式反应器容器中制造，然后通过熔化和成型加工成最终产品。这些产品的例子包括管道，瓶子，电脑机箱，薄膜和粘合剂。聚合物材料的加工性能取决于聚合物的流变性，而流变性又取决于聚合物链的分子特性（如组成、分子量分布、长链分支类型、频率和长度）。这些分子性质是由初始反应容器中的条件决定的。获得理想的流变特性需要大量昂贵的反复试验。为了减少这种情况，我们必须发展聚合物分子特性和流变性能之间的关系。拟议的研究侧重于发展这种关系，并基于并扩展了先前基于物理脉冲方法开发的数学模拟方法的工作。这产生了一个数学模型，应用于橡胶工业使用的商业聚合过程，成功地预测了阴离子聚合中产生的聚合物链的全分子量分布。目前提出的工作包括开发一种在分子水平上能够预测长链分支频率和结构受混合（包括扩散效应）影响的模拟方法。这将是结合聚合物链扩散速率影响的物理脉冲方法。为了实现开发一种准确、定量预测的方法的目标，我们将合成和分析许多具有不同长链分支结构和频率的聚烯烃。

This research project aims at developing a mathematical simulation method for predicting long chain branching structure and frequency in polymer molecules.  Polymeric materials are typically made in stirred tank reactor vessels and then processed into final products by melting and shaping. Examples of these products include pipes, bottles, computer cases, films and adhesives. The processing properties of the polymeric materials depend on the rheology of the polymers which, in turn, depends on the molecular properties of the polymer chains (e.g. composition, molecular weight distribution, long chain branching type, frequency and length).  These molecular properties are determined by conditions in the initial reaction vessel.  Obtaining desired rheological properties requires much expensive trial and error experimentation. To reduce this we must develop relationships between polymer molecular properties and rheological properties.  The proposed research focuses on developing such relationships and is based on, and extends, previous work that developed mathematical simulation methods based on the method of Physical Pulses.  This produced a mathematical model that was applied to a commercial polymerization process used by the rubber industry, successfully predicting the full molecular weight distributions for polymer chains produced in an anionic polymerization.The current proposed work comprises developing a simulation method capable of predicting long chain branching frequency and structure as affected by mixing (including diffusion effects) at the molecular level.  This will be the Method of Physical Pulses Incorporating the Effects of Polymer Chain Diffusion Rates.  In order to satisfy the goal of developing a method that gives accurate, quantitative predictions we will synthesize and analyze many polyolefins with varying long chain branching structure and frequency.