CAREER: Adaptability of soft deformable granular materials

NON-TECHNICAL SUMMARY: Most people think of granular materials as particles of sand, soil, or gravel. As such, most models for these materials assume that individual grains are rigid and perfectly smooth. This idealization rarely holds in real-world biotechnology applications because granular materials are made of soft particles that interact in complex ways. For example, biological cells can interact, deform, and stick to one another to form biological tissues. Understanding how this process occurs is critical for advancing applications in biotechnology, adaptive or responsive metamaterials, and programmable soft robotics. This project develops a novel experimental platform based on custom-built, inflatable particles whose size, shape, stiffness, and interactions can be individually and precisely controlled. The research will investigate how particle-level properties such as deformability and friction give rise to the collective behavior. The educational component of this project targets multiple levels of the STEM pipeline. A new physics course curriculum for non-science college majors will be developed using everyday scenarios to make physics concepts accessible and relevant. Undergraduate researchers will gain hands-on laboratory training while developing science demonstrations for K-12 students and the general public, creating a broad extent of scientific engagement across communities. TECHNICAL SUMMARY: This project investigates the mechanical behavior and adaptability of granular packings composed of soft, frictional, deformable particles with actively tunable degrees of freedom including size, shape, and stiffness. The interplay of friction and particle-level deformability produces nonlinear, history-dependent mechanical responses that lie beyond the reach of existing jamming and constraint-counting frameworks. Understanding how this process occurs is critical for advancing applications in biotechnology, adaptive or responsive metamaterials, and programmable soft robotics. Three research objectives are pursued: (1) characterizing the relationship between friction, deformability, applied pressure, and the onset of rigidity, (2) quantifying the sensitivity of bulk mechanical properties to preparation history and small structural perturbations, and (3) identifying decentralized local adaptation rules that use particle-level degrees of freedom to achieve predictable, programmable modification of bulk properties. Experiments use custom pneumatic particles with individual pressure control, optical imaging, and a novel overlap-based modulus measurement method, complemented by contact-network simulations. The educational objectives include developing a physics curriculum for algebra-based undergraduate courses serving non-STEM majors, featuring real-world case study worksheets connecting physics principles to everyday scenarios. In parallel, hands-on demonstrations inspired by the research will be developed by undergraduate researchers and deployed at public outreach events and extended workshops for K-12 students. 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. NSF Award ID: 2541744 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Nidhi Pashine | Institution: Syracuse University, SYRACUSE, NY | Award Amount: $358,377 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2541744 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2541744.html