(196d) From Process to Product - Enhancing the Understanding of ?-Olefin-Polymerizations

A fundamental task within polymer chemistry is getting a deeper insight of polymerization processes, especially those of industrial relevance. Only by understanding the fundamentals, such as the reaction networks, thermodynamics and the structure-property relationship, simulation-based process optimization and product design will be possible. This gains more and more relevance, as with increasing production scale on single reactors experimental based optimization becomes less of an option for costs and safety reasons.

In this context, the high-pressure polymerizations of α-olefins are a striking example for many reasons. Performing high-pressure experiments – both in mini-plants and industrially – is extremely expensive, thus the need for reliable models with a predictive ability is extraordinarily high. At the same time, the polymer has a very complex and inhomogeneous microstructure, consisting of randomly introduced short- and long-chain branches. Process conditions determine this microstructure, which has an enormous impact on processability and product properties. Thus, it is of high interest to understand the connection between process, microstructure and product properties.

We will introduce a three-step modeling approach, which is able to predict – to a certain extent – polymer properties, characterized by rheology, from process conditions. Numerical modeling of the kinetics on deterministic base is the first step; in a second step a hybrid Monte-Carlo algorithm is describing the microstructure and finally in the last step the entangled polymer dynamics of the branched material can be calculated via the branch-on-branch algorithm [1].

This modelling approach opens up a wide research area: the fundamentals can be investigated more thoroughly and globally and at the same time reliable simulation-based product design becomes more realistic.

Another important aspect within this context is investigating the thermo-physical properties of the system, as this enables for a proper thermodynamic evaluation of the process. However, in the high-pressure and high-temperature area reliable data on properties such as the heat capacity is very rare. In particular, excess effects due to mixtures of polymer and solvents have not been investigated. Thus, we apply transitiometry – a high-temperature, high-pressure calorimeter of high sensitivity – to investigate heat capacities at these extreme conditions.

By this, we do can significantly enhance the understanding of α-olefin-polymerizations and make another significant step towards simulation-based process optimization as well as process design.

[1] D. Read et al., Science. 2011, 333(6051), 1871.