Grainger College of Engineering, All Events

Living systems exhibit a remarkable capacity to self-organize, sustaining dynamics such as self-replication and information processing far from thermal equilibrium. What determines this capacity, and why is it inevitably lost? 

In this talk, I will present a broad view of our lab’s efforts to understand the limits of what I have termed the non-equilibrium capacity (NEC) of living systems—the ability to generate, sustain, and restart the dynamics that define life. I will begin with experiments that probe this capacity by pushing cells toward extreme conditions. By slowing or suspending cellular processes, we uncover key limits on how slowly life can proceed while remaining viable, and identify conditions under which cells can lose—and in some cases later recover—the ability to self-replicate and process information. 

I will then turn to computational approaches based on generalized cellular automata, in which cells interact through simple rule-based “secrete-and-sense” mechanisms to self-organize from disordered initial states into spatial patterns, including static configurations, traveling waves, and spiral waves. Within this framework, we find that predictability is not fully accessible from the initial configuration, but is instead dynamically constructed over time. This construction is mediated by emergent topological collective modes—defect-like structures whose creation, motion, and annihilation govern the evolution of these spatial patterns and determine their long-time outcomes. 

Together, these experimental and computational studies suggest that the non-equilibrium capacity of living systems is not directly accessible from a static snapshot, but is instead dynamically revealed through their time evolution.