Project Grant 2239801

This $239,999 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will support research into understanding how mechanical systems can learn intelligent behaviors through local self-organization processes similar to neural networks. Over a five-year period from January 2023 through December 2027, the University of Chicago will investigate the non-equilibrium requirements for materials to physically learn new functionalities through Hebbian and anti-Hebbian learning principles. The awardee will develop the underlying theory of non-equilibrium memory in adaptive materials and explore how natural chemo-mechanical feedback circuits can implement such memory. Undergraduate and graduate students will be trained through this interdisciplinary work expanding the understanding of what non-linear, non-equilibrium disordered mechanical systems can achieve through learning behaviors.