Computational Modeling of Polymerization and Degradation of Complex Polymer SystemsPublic
Oil paintings are complex works of art, even on the molecular level. Drying oils cure into a solid film through autoxidation and polymerization reactions and then degrade, leading to changes in material properties and film stability. This chemistry can be captured in a computational model and used by researchers in the coatings industry and art conservation to study polymer films through non-invasive means. However, there are numerous challenges in simulating how the complex polymers like those in painted works cure and degrade, mainly regarding the balance of tractability and accuracy of different computational models. In this dissertation, the context and chemistry of oil paint curing is described first. The next portion is a broader application of polymer modeling to polyolefin pyrolysis, which underscores the importance of selecting the right computational methods for the information and properties that are desired. A comparison of global and kinetic models is given, highlighting the level of detail acquired by explicitly considering reaction types rather than global fitting, which empirically matches experimental data but misses the effects attributed to tacticity and the chemical bonds in polypropylene and polyethylene pyrolysis. Following the utility of kinetic models, a broad lumping approach is applied to reaction types to fit a monomer-based kinetic model of ethyl linoleate, a representative molecule of larger drying oils found in paint, to experimental FTIR measurements. Advantages of this method are in automatically generating particular monomeric fragments as ethyl linoleate oligomerizes. The sensitivity of the model to kinetic rate parameters also highlights the overall influence of reaction types and the importance of subdividing reaction families based on local reactivity. This body of work culminates in a framework that is applied to ethyl linoleate autoxidation with stochastic simulation to capture both the formation of polymers and track the evolution of experimental measures of interest. Concluding remarks and a perspective on the future of computational modeling of complex polymer systems close the dissertation.
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