Molecular cages are emerging as a unique class of compounds with potential applications in catalysis, battery technology, and filtrations and separations. These single molecules have three-dimensional shapes, variable sizes, and empty space in their interiors. The most efficient way to build molecular cages and other shape-persistent architectures is the synthetic process known as dynamic covalent chemistry (DCC). Using DCC means that chemists can build structures with simple precursors which "self-assemble" into the desired geometry over the course of a single chemical reaction rather than building structures step-by-step over many reactions. However, a major challenge when using DCC is the difficulty in predicting what precursor is best to obtain the desired architecture. Currently, the Moore group of the University of Illinois at Urbana-Champain is working toward a set of guidelines for DCC which will help chemists design better precursors and synthetic strategies for building three-dimensional architectures. This project supports the education and professional development for future researchers and educators, preparing for a workforce for the science and engineering fields. In addition, the Moore Group members participate in public outreach and educational activities (e.g., Encouraging Tomorrow's Chemists events for local middle schools) to communicate and promote a strong literacy in science for the next generation.
With the support from the NSF Macromolecular, Supramolecular and Nanochemistry Program, the Moore group is using alkyne metathesis as a model DCC reaction to study the relationship between exchange rate and product distribution, especially in cases where kinetic traps are known to form. DCC describes reversible reactions where molecular components can exchange freely until a thermodynamic minimum is achieved, and kinetic traps arise when exchange rates are too slow and/or the building blocks have a high valance. The team aims to build a computational model that describes the relationship between exchange rates, valancy, and product distribution. The computational model is designed to provide chemists with a better understanding of which DCC reactions or reaction conditions are necessary to access predicted structures. Additionally, the model predicts when kinetic traps are likely to arise in a given reaction and the maximum product yield that can be expected. The computational model is supplemented with experimentally obtained kinetic data for both simple and complex alkyne metathesis reactions. Once the fundamentals are established, they will be used as a guide for accessing more complex shape-persistent molecular architectures of nanoscale dimension.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
