2019 AIChE Annual Meeting

(692a) Heteropolymer Design and Synthesis through Practical Prediction of Controlled Radical Polymerizations

Authors

Smith, A. A. A. - Presenter, Stanford University
Hall, A., UC Berkeley
Wu, V., UC Berkeley
Xu, T., University of California, Berkeley
Appel, E. A., Stanford University
The opportunities for elaborate polymer designs have been expanded, following the advent of controlled radical polymerizations, such as RAFT and ATRP. Yet experimental design of copolymerizations seldom take advantage of reactivity ratios, despite there being an in-depth knowledge of the reaction kinetics involved that would allow prediction of monomer distribution and design of polymer structure. Furthermore, even more elaborate polymer designs are possible by increasing the number of unique monomers in the polymerization. Heteropolymers harbor an infinite number of possible variations in composition and molecular weight, yet this class of materials is largely unexplored. The difficulties in designing and understanding polymerizations with gradients in composition, or statistical distribution of monomers, likely contribute significantly to scarcity of heteropolymer exploration studies.

To make these considerations more approachable, we have developed ‘Compositional Drift’, a program using a Monte Carlo method to predict monomer consumption and heteropolymer monomer sequence in controlled radical polymerizations, based on monomer reactivity ratios [1]. ‘Compositional Drift’ is developed for experimentalists, and does not require experience with simulation software. This presentation will demonstrate ‘Compositional Drift’, and discuss its application and use in understanding non-covalent polymer-protein complexes [2]. Lastly, a simple and accurate method for determining reactivity ratios, based on the Meyer-Lowry model, will be given. This is designed to be used in conjunction with ‘Compositional Drift’, further enabling reactivity ratio considerations in polymer design.

[1] Smith, A. A. A. et al. (2019). "Practical Prediction of Heteropolymer Composition and Drift." ACS Macro Letters 8(1): 36-40.

[2] B. Panganiban. et al. (2018) Random heteropolymers preserve protein function in foreign environments. Science, 359, 1239–1243