The advent of soft robotics, wearable electronics, and personalized medicine has sparked a demand for synthetic materials that mimic the mechanical responses of living tissues. Living tissues are unique as they are soft at touch, yet resistant to deformation. This strain-adaptive stiffening represents one of Nature's defense mechanisms that prevents accidental tissue rupture and imbues a characteristic feeling of firmness. Various molecular and macroscopic constructs have been explored to reproduce the tissue mechanics; however, they fail to integrate softness and firmness on a molecular scale. This project aims at the development of a materials design platform that harnesses architectural codes for programming the grand variation of mechanical responses, ranging from that of ultra-soft brain tissue to super-firm skin. Through closed-loop collaboration of soft matter theoreticians, synthetic chemists, and experimental physicists, this design-by-architecture approach will inspire new directions in synthetic chemistry and soft-matter physics towards creation of novel molecular architectures with encoded structure-property correlations. In line with the mission of the Materials Genome Initiative, this approach will constitute the foundation for a materials design search engine that will guide and accelerate the synthesis of tissue replicas with targeted mechanical properties. The novel classes of materials will catalyze fundamental shifts in many technologies, including - but not limited to - soft robotics, active camouflage systems, and biomedical devices.
Conventional gels and elastomers cannot replicate tissue's strain-adaptive stiffening. Transition from the super-soft to super-firm mechanical response upon deformation requires a hierarchical organization of different structural motifs that trigger a cascade of deformation mechanisms at different stress levels. As such, the project will address three fundamental and increasingly complex challenges. First, theoretical modeling will establish universal correlations between network architecture and mechanical properties such as stiffness and firmness, and will form quantitative guidelines for encoding precise mechanical "phenotypes" in designed polymeric systems. Second, introduction of self-assembling moieties into network architectural code will empower polymer assemblies with strain-adaptive stiffening. Third, incorporation of dynamic crosslinks will impart programmable viscoelastic response and extend the platform to strain-rate responsive mechanical phenotypes. Fulfillment of the project goals will yield a molecular code - collectively enabling the programmable and efficient development of next-generation of tissue-like synthetic materials with both strain- and strain rate-adaptive mechanical properties.
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.
