Rational design of polymerization systems: Perspectives from computational chemistry and reaction engineering

Conference Dates

May 20-25, 2018


The stochastic nature of polymerization processes often leads to a mixture of chain populations with drastically different molecular architecture. Things can be further complicated by reactor type and geometry, species involved, operating conditions, etc. Thus, scientists and engineers frequently rely on models to aid new and existing product development, scale-up, implementation and troubleshooting. Ultimately, detailed and accurate models enable the formulation of optimal reaction conditions to achieve desired polymer architecture and properties. This presentation will focus on examples from free radical and metallocene-type polymerization systems and provide insights into the rational design of materials.

Figure 1– Multiple transition states for polyethylene propagation

The realization that any polymerization model is only as reliable as the kinetic, mass and energy balance parameters that it employs leads to the continuous improvement of the analytical techniques and instrumentation necessary to determine them. Even the simplest ideal kinetic models require accurate rate parameters to guide system development. Alas, obtaining those from experiments is not always practical and, in some cases, impossible. Computational chemistry provides an appealing alternative. Moreover, with the advances in high-performance computing, the investigation of larger species has become more tractable. These advances are of particular importance to industry where quick results are often needed to enable decision making. In the first part of this presentation, we will demonstrate a computational protocol for accurate rate parameter estimation in both gas and condensed phase. Special emphasis will be placed on the concept of multiple reaction pathways associated with the chemical transformations along the reaction coordinate (Figure 1).

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