Polymer chemists still look to proteins with envy. The unparalleled control of monomer distribution and dispersity of proteins is well beyond the reach of modern polymer chemistry. However, simple measures of control is possible, as the theoretical understanding needed to exert control of gradient to gradient-block copolymers is well developed, though experimentally it is rarely utilized, likely due to the complexity of design and analysis involved. While comprehensive software packages for predicting polymerizations have been developed, their complexity renders them difficult to approach when doing exploratory experimental work. Compositional drift in batch polymerizations due different reactivity of monomers is a well-known phenomenon. This drift can lead to the formation of a gradient in composition when the polymers are synthesized using controlled polymerization methodologies, such as RAFT. By knowing the apparent reactivity ratios of the polymerization, the drift can be controlled by adjusting polymerization conditions to create gradient copolymers towards a desired design. The same methodology can also be applied to predict composition in non-drifting polymerizations. Despite the low complexity of doing so, neither are seldom done, likely due to the perceived difficulty. We seek to remedy this through ‘Compositional Drift’; an easy-to-use program enabling the prediction of drift in polymer composition based on the use of the Mayo-Lewis model and Monte-Carlo methodology. This tool has guided experimental design and allowed an understanding of polymer compositions in complicated heteropolymers. We wish to supply this tool to the community, showcasing two recent examples of use in the literature.<sup>1,2</sup>

Practical prediction of monomer composition and drift in controlled radical polymerizations

256th National Meeting (2018)

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