One of the grand challenges in materials science and engineering is the ability to design active and adaptive materials that dynamically change configuration and functionality in response to specific triggers and changes in the surrounding environment. Architected matter with shape morphing capabilities and on-demand programmability of mechanical properties (i.e., soft robotic materials) will have a wealth of applications in deployable systems, dynamic optics, soft robotics, and medicine. Hydrogels, a class of stimuli-responsive materials, are promising constituents for designing such soft robotic materials. Hydrogels can change their volume by several fold in response to various environmental cues. Furthermore, most hydrogels are transparent and stretchable, as well as cost-efficient and environmentally friendly. However, most hydrogels are soft and brittle and the stresses that they can generate and tolerate are rather limited. To improve their actuation force and mechanical integrity, they have to be integrated in hybrid systems with stiffer materials and structures. The project will explore how to combine hydrogel units with elastomeric cellular scaffolds carefully designed to amplify the output of the active components. Upon activation, low-stress deformations of hydrogel muscles positioned in the scaffolds will induce large reconfigurations in the scaffold morphology and enable work.
proposed project introduces and investigates a new class of active, reconfigurable, and shape-morphing soft robotic materials with programmed mechanical properties based on elastomeric cellular structures actuated by hydrogel muscles. The objective is to establish robust and computationally efficient methods to capture their highly non-linear response, to synthesize hydrogels that generate large deformations in response to external stimuli, to identify cellular architectures that amplify and direct the hydrogels' response, to develop 3D printing strategies that enables fabrication of computationally identified material designs, and to solve the inverse problem of identifying realizable layouts that form soft robotic matter with the desired behavior. Guided by these studies, the research team will then explore opportunities for application of the active soft robotic materials in the design of smart and adaptive structures, including manipulators, reconfigurable structures and adaptive optics. The research is expected to enable material design capabilities that shift the current paradigm for soft robotic materials by creating an efficient work-flow that given a target application identifies the optimal cellular microstructure and hydrogel composition.
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.
