Self-Healing Polymers in Complex Water Matrices: Towards Smart Materials for the Environment

Responsible environmental stewardship requires reducing the environmental burden of synthetic polymers, which are accumulating in natural water bodies. At the same time, modern life relies heavily on synthetic polymers to perform increasingly complex functions across many industries, including textiles, transportation, medical, water treatment, and electronics industries.

Self-healing polymers are materials that can recover from physical or chemical damage autonomously. These polymers offer an untapped opportunity to mitigate the environmental burden of plastics by reducing waste, while also exceeding the capabilities of current synthetic polymers. However, most self-healing materials are designed to operate in inert, moisture-free environments, and their performance in real-world, complex environments is poorly understood.

This research project will examine how common ions in natural waters impact the self-healing process. The fundamental knowledge that is gained will be used to engineer new polymers that can self-heal under a wide range of conditions. Concepts in polymer materials science and smart materials will be incorporated into the undergraduate and graduate environmental engineering curriculum at Rice University.

This educational aim will fortify interdisciplinary skills development at the intersection of materials science and environmental engineering. Existing programs at Rice University will be leveraged to recruit and mentor undergraduate students from underrepresented groups and contribute to the development of a diverse STEM workforce.

The overarching goal of this project is to understand the key factors that determine the performance of self-healing polymers in complex water matrices. The most widely used mechanisms for self-healing rely on the capacity of polymeric chains at a damage interface to diffuse, reorganize, and re-form bonds with one another. This project will investigate the primary variables that impact this intrinsic capacity to re-form secondary bonds.

The specific objectives are to 1) determine the impact of water quality parameters – hardness, salinity, and total organic carbon – on intrinsic self-healing mechanisms, 2) derive mechanistic understanding of how water constituents alter self-healing behavior, and 3) establish synthetically controllable parameters that maximize self-healing performance (i.e., 100% recovery) in complex environments. Model polymers that self-heal via hydrogen bonding and ionic interactions will be synthesized, and bulk mechanical testing and microscopic profiling in the presence of complex water matrices will be applied to quantify self-healing as a function of different water constituents.

Dynamic mechanical analysis, quartz crystal microbalance with dissipation experiments, and spectroscopic chemical analysis will be used to gain mechanistic understanding of changes in self-healing behavior. Sidechain length and crosslinking density for each model polymer will be varied to identify conditions that maximize self-healing in complex environments.

The successful completion of this project will help establish design principles for smart and responsive polymeric materials that address pressing environmental challenges.

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.