Mathematical Modeling of Chain Shuttling Polymerization
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Chain shuttling polymerization with dual catalysts has introduced a new class of polyolefin called olefin block copolymers (OBCs). The Dow Chemical Company developed this new material in 2006 with a chain shuttling agent used to exchange living and dormant chains between two single-site catalysts reversibly. One catalyst may produce a soft/amorphous ethylene/-olefin block due to its high reactivity ratio towards α-olefin insertion, while the other catalyst makes a hard/semi-crystalline ethylene/-olefin block due to its low -olefin reactivity ratio. The soft block provides elastomeric properties, whereas the hard block works as a physical crosslink to connect the elastomeric blocks. Characterization of these novel materials is challenging because there are no analytical methods that can measure the distribution of blocks in OBCs. A mathematical model that can describe the detailed microstructure of these products is, therefore, an important step towards understanding how different polymerization conditions and kinetic parameters affect their microstructure. The main objective of this thesis is to develop such detailed models for semi-batch and continuous stirred tank reactors (CSTR). Starting from the polymerization mechanism generally accepted for chain shuttling polymerization, we developed two different mathematical models to predict OBC microstructures made under different conditions. The first and simpler model uses population balances and the method of moments to predict chain length and composition averages for the overall (whole) OBC and for populations with different number of blocks. The second, and more complex model, uses dynamic Monte Carlo techniques to predict complete distributions of chain length and chemical composition. The simulations described in this thesis show that OBCs have complex, multiblock structures, that depend strongly on several polymerization kinetic parameters, reactor conditions, and reactor modes of operation. As these conditions change, number average chain lengths, chemical compositions, average number of blocks, and block distribution among the OBC populations are also affected, and possibly the application properties of these advanced polyolefins. The models proposed herein allow us to quantify the trends of this microstructural changes, and hopefully can help researchers design OBCs with better controlled molecular architectures.
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Ibrahim Maafa (2016). Mathematical Modeling of Chain Shuttling Polymerization. UWSpace. http://hdl.handle.net/10012/11131