Molecular weight distribution controlled long chain branching

Research on the modelling, optimization and control of emulsion polymerization (latex) reactors and processes has been expanding rapidly as the chemistry and physics of these systems become better understood, and as the demand for new and improved latex products increases. The objectives are usually to optimize production rates and/or to control product quality variables such as polymer particle size distribution (PSD), particle morphology, copolymer composition, molecular weights (MW s), long chain branching (LCB), crosslinking frequency and gel content. 

Iedema, P.D. and Hoefsloot, H.C.J. (2001) Synthesis of branched polymer architectures from molecular weight and branching distributions for radical polymerisation with long-chain branching, accounting for topology-controlled random scission. Macromol. Theor. Simul., 10, 855. 

In 1975 Mitsui Petrochemicals introduced metallocene-made LLDPE Tafiner , with controlled comonomer placement, but rather low MW. In 1991, Dow Plastics produced developmental quantities of ethylene copolymers with up to 25 mole % of butene, hexene or octene, Affinity resins. The use of a metallocene catalyst with a single cyclopentadiene ring, resulted in a certain degree of randomization of the polymerization process. The catalyst produced PP with narrow molecular weight distribution, and a long chain branching, similar to LDPE. 

Until recent years, there existed major barriers to the development of quantitative relationships between the molecular structure of molten polymers and their rheological behavior. First, reaction systems capable of producing polymers on an industrial scale yielded materials with complex and imprecisely controlled structures. Second, the molecular weight distributions of linear polymers tended to be broad and somewhat irreproducible. And, finally, the branching structure of long-chain branched polymers, particularly low-density polyethylene, involves multidimensional distributions that can neither be predicted nor characterized with precision. 

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