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Active Mechanics of Cohesive Biological Aggregates : -The Case of Fire-Ant Swarms-
A majority of soft living materials owe their complex mechanical behavior to an underlying network structure. Despite this inherent complexity, the physical structure of these materials can often be conceptualized as dynamic physical networks, where nodes and connections are governed by simple rules. An advantage of such a network representation resides in its well-defined mathematical structure, enabling the use of the powerful machinery of statistical mechanics. This statistical approach, or transient network theory (TNT), provides a bridge to connect (simple) “network rules” to emerging (complex) “continuum response”. In dynamic polymer networks, topological bond rearrangement combined with chain elasticity is sufficient to explain the emerging elasticity, rheology, and time-dependent fracture of the material. Applying this approach to living materials is tempting but is challenging because of the diversity of mechanisms involved (cell signaling, reaction, diffusion, growth, …) and issues with direct observations and measurements.
This presentation will discuss our recent work on a biological yet simplified mechanical network (the raft) that solenopsis invicta (better known as fire ants) make with their own body to escape flooding. Like cellular systems, these networks are highly dynamic and active. As such, they are not only capable of adapting their viscoelastic response to load to avoid premature failure, but also display collective morphogenesis with the stochastic emergence of long protrusions from the raft’s edge. Employing experimental characterization and our dynamic network model, we unveil a set of local rules that reproduces the emergence of these instabilities in the absence of external factors. Results suggest that collective morphogenesis in fire ant swarms emerge from a reduced set of rules at the network level. To conclude, we discuss the potential of the concept of dynamics network to better understanding active and living materials, and discuss potential applications to the development of decentralized, autonomous active matter and synthetic swarms.