Human-made biomaterials have the potential to unlock biological mysteries and transform human health. For a biomaterial to be useful, it must mimic the properties of living tissues and present cues to cells that generate a desired response (for example: to support loads, to grow, to produce a certain protein, to transform in some way, etc). A wide-range of materials are used in these applications and, in our shared work at HMC, we focus on soft tissue-models called hydrogels. Hydrogels are water-saturated polymer networks that are formed by mixing initially separate precursor-containing liquids to form solid materials (just like mixing resins when using epoxy). By precisely controlling the composition and volume of each precursor fluid, it is possible to engineer hydrogels whose bulk, macroscopic properties mimic those of living tissues. The problem, however, is that biological tissues do not have fixed, uniform properties throughout; instead, their properties vary as a function of space. Therefore, current hydrogel fabrication methods do not adequately capture the complexity of living tissues.
To address this problem, our group has been working to develop a microfluidic solution for efficiently combining hydrogel precursors that would produce hydrogels with properties that could be controlled with microscale resolution. One approach would be to manually fabricate a range of microfluidic devices and evaluate how well they combine precursors to form hydrogels, but this process would be a time-expensive approach. Instead, we deploy computational models (using ANSYS Fluent on the National Science Foundation’s XSEDE) to generate and evaluate microfluidic channel designs that can efficiently mix precursor streams. Each design must consider a complex, and competing, set of considerations including material properties, mixing efficiency and time scales, polymerization rates, pressure costs, cell viability, and manufacturability, among others. The goal of these computational models is to generate a suite of microfluidic designs that are optimized for specific applications. Future work includes fabricating and empirically validating optimized microfluidic geometries.
Research will take place during the Spring 2022 semester for academic credit and extends work initiated by prior Mudders with the possibility for collaboration with students external to HMC. Check out our recent work: https://ui.adsabs.harvard.edu/abs/2020APS..DFDU10004P/abstract
Essay Prompt (~1 page total, due 24 hours prior to your scheduled interview): Why are you interested in working on this project? What skills do you hope to learn through this work? What skills do you bring to the group that support the project’s success?
As a member of this group, you would work on projects that collectively build knowledge at the intersection of fluid mechanics, bioengineering, and materials engineering. Together, our work seeks to build tools and materials for evaluating biological function in benchtop models to uncover biological function.