CAREER: Connecting Microscopic Rearrangements to Macroscopic Flow in Dynamic Covalent Networks

About This Grant

Non-Technical Summary High-performance materials ranging from composites for structural and defense capabilities to biomaterials for biotechnology and agricultural applications rely on long-chain macromolecules ‘stitched’ together into networks. The resulting polymer networks show high mechanical strength but are typically challenging to process in energy and cost-efficient ways that prevents manufacturing and use. The incorporation of chemical linkages that can rearrange on the molecular level known as ‘dynamic bonds’ presents a strategy to impart processability when bond exchange is activated while preserving mechanical strength when suppressed. However, understanding of how microscopic chemistry translates to observed bulk behavior remains poorly understood. This CAREER work combines chemistry and characterization tools to enable dynamic networks with co-optimized processability and mechanical stability. This will be achieved by understanding how local molecular events define deformation behavior that is key to processing and manufacturing without compromising mechanical strength. The new materials and understanding developed in this project will broadly benefit the US by advancing national health, prosperity, and welfare by enabling to methods to make and deploy advanced materials. This research will further be combined with K-12 outreach and student training to prepare the next generation STEM workforce. Technical Summary This project will establish how mixtures of dynamic covalent bonds and topological entanglements can be harnessed to co-optimize viscosity and elasticity. New characterization methods and synthetic tools will be developed to understand the physics of network relaxation and the fundamental insight gained will subsequently be used to control chemical and physical interactions. Coupled rheological and spectroscopic measurements will be used to reveal the ways in which segmental motion and configurational constraints affect local bond exchange events. These measurements will inform the design of dynamic covalent bond pathways to decouple viscous relaxation and elastic mechanics. Finally, the effect of topological motifs including entanglements and defects on emergent viscoelasticity will be explored. The goal of this work is to provide measurements to definitively link microscopic exchange events, mesoscopic chain topology, and macroscopic properties. Importantly, such data could inform future AI/ML frameworks for the design of materials for advanced manufacturing, composites, and biomedicine. Additionally, this research will be integrated with a school mentorship program for fostering polymer science and building connections to motivate and support the STEM workforce. 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.