My research is in the field of organic chemistry, specifically polymer science. The goal for this project was to develop a preexisting model to predict kinetic information for other polymer systems. The original model was used to predict kinetic information for RAFT polymer systems, but we wanted to make it more versatile and apply it to other types of polymerizatons. Many models that exist in polymer science are limited to being accurate for one type of polymerization and lack experimental evidence. Our work hopes to create a general model that is versatile and is proven with experimental evidence. MatLab software was used to analyze gas chromatography data and various calculated experimental parameters. The model then predicts the ratio of propagation to deactivation (k*) and the number of activation and deactivation cycles (decap). This data is useful when looking at the mechanism of polymerization at different dispersities and can serve as a powerful prediction tool to optimize reactions. We found that our model was able to accurately predict kinetic information for ATRP, RAFT, PET-RAFT, blended, and cationic polymerization systems. This project has taught me how to use MatLab software, how modeling works, and the value of predictive work. Before this project I exclusively work in the laboratory making various polymers and testing their properties, it was interesting to see what chemistry research can look like outside of the laboratory.
Authors: Colleen Morley and Madison Kearons
Advisor: Dominik Konkolewicz, Department of Chemistry and Biochemistry
Presentor: Colleen Morley
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