(192f) Refinement of Techniques in Molecular Modeling of Multicompartment Nanoreactors
- Conference: AIChE Annual Meeting
- Year: 2017
- Proceeding: 2017 Annual Meeting
- Group: Computational Molecular Science and Engineering Forum
Monday, October 30, 2017 - 3:15pm-4:45pm
Chemical reaction schemes often require multiple mutually orthogonal catalysts that preclude the use of one-pot systems. Single compartment micelle nanoreactors offer the benefits of chemical reaction separability of desired products. It follows that a system which immobilizes catalysts within separate compartments of a micelle for multistep reactions is highly desirable in order to gain the benefits of reaction separability and enhanced selectivity. An estimate of the thermodynamic interaction between blocks of copolymers is required to assess the ability of micelles to form distinct compartments. Our analysis utilizes the Flory-Huggins theory of polymer miscibility, which introduces a miscibility parameter ð as a measure of the favorability of the interaction between polymers in blends. In our current work, we compare the miscibility of binary polymer systems, using a series of computational methods to calculate the ð parameter for each pair of molecules as they might be found in a micelle. In order to explore the effect of molecular size on ð parameter, we extended the number of monomeric units from one to three. By refining our parameters and methods, our results have converged to the experimental observations of miscibility for these candidates. More specifically, we will investigate the relationship between number of lowest energy samples, number of cluster samples, reference temperature and accuracy of calculated ð values. An increase in the number of lowest energy samples has been shown to increase precision for averaged ð values, especially for trimeric systems. Similarly, we can improve the accuracy of the obtained ðÂ values by increasing the number of molecular cluster samples probed to estimate the coordination between a given pair of molecules. Finally, we will explore whether the choice of reference temperature greatly affects the final results, or if post-calculation Boltzmann averaging performed at the desired temperature is sufficient. Our primary goal is to investigate the existence of a quantitative model between molecular size and the parameters we have established here. Through further research, we will show that computational modeling can confidently and consistently predict miscibility behavior.