Pattern Formation in Active Nonreciprocal Mechanical Metamaterials

Objective

Living matter, from cells to complex organisms are animate: they perform extraordinary mechanical tasks like locomotion, adaptation to environments, and self-repair. By contrast, even advanced synthetic materials remain far from achieving such autonomous functionalities. A promising route to synthetic animate materials is nonreciprocal mechanical metamaterials: active mechanical systems composed of distributed sensors and actuators whose active feedback breaks the symmetry of couplings between their unit blocks. To realize animate functionalities, these materials should in principle be able to form and control environment-dependent nonlinear patterns. Yet most studies to date remain confined to linear regimes and isolated settings. As a result, the fundamental understanding of patterns in nonreciprocal mechanical metamaterials is still poorly understood. This project addresses this gap by developing the theoretical foundations for pattern formation, selection, and control in nonlinear nonreciprocal metamaterials. Specifically, I will (i) identify the physical laws governing pattern formation under the effects of nonlinearity, damping, and driving, (ii) investigate the role of geometric constraints like finite size and boundaries, and (iii) translate these insights into computational multiphysics models of active mechanical metamaterials, in which patterns induce animate behaviors. This proposal represents an innovative approach made possible by the complementary expertise of a leading lab in active mechanical metamaterials (host) and my own background in nonlinear dynamics. The results from this study will open new avenues by establishing the guiding principles for pattern-based animate and autonomous functionalities in active solids. This fellowship will equip me with transformational expertise in nonlinear active solids, multiphysics simulations and interdisciplinary collaboration, constituting a major step towards establishing my independent academic career.