Fire Ant Rafts Offer Principles and Rules for Synthetic Programmable Morphing Matter

We examine fire-ant rafts as a model system of biological active matter composed of cohesive agents that interact through simple local rules to produce emergent collective dynamics. A hallmark of these rafts is treadmilling, a process enabled by the continuous cycling of ants through a multi-phase system, comprising in a minimal representation a solid-like network phase and a dilute motile phase that can migrate outside the network. Treadmilling requires the breaking of detailed balance in the fluxes between the phases, a signature of out-of-equilibrium systems. By combining experimental data with discrete agent-based simulations and a new continuum model, we show that simple rules governing the actions of single ants, based only on the positions, velocities and local forces an ant perceives and defining its next actions within a phase and triggering conditions for transition between phases, suffice to replicate the complex behavior of treadmilling and shape morphing of the raft as emergent phenomena. We also show that two principles hold empirically in the network phase: homeostasis of area density, a constraint that couples ant activity level to shape morphing in a very simple way; and the invariance of the network topology over relevant timescales, which supports global geometrical stability in the face of chaotic ant motions. Refined by evolution over very long times, the principles and rules governing fire ant rafts suggest design possibilities for achieving stable shape morphing in decentralized systems of synthetic programmable matter.

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Publication Details

Journal
Bioinspiration & Biomimetics
Published
2026-03-03
DOI
https://doi.org/10.1088/1748-3190/ae4ce3
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
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article

Fire Ant Rafts Offer Principles and Rules for Synthetic Programmable Morphing Matter

Franck J. Vernerey, Brian Cox
Bioinspiration & Biomimetics
Micro and Nano Robotics
article

Fire Ant Rafts Offer Principles and Rules for Synthetic Programmable Morphing Matter

Franck J. Vernerey, Brian Cox
article en

Abstract

We examine fire-ant rafts as a model system of biological active matter composed of cohesive agents that interact through simple local rules to produce emergent collective dynamics. A hallmark of these rafts is treadmilling, a process enabled by the continuous cycling of ants through a multi-phase system, comprising in a minimal representation a solid-like network phase and a dilute motile phase that can migrate outside the network. Treadmilling requires the breaking of detailed balance in the fluxes between the phases, a signature of out-of-equilibrium systems. By combining experimental data with discrete agent-based simulations and a new continuum model, we show that simple rules governing the actions of single ants, based only on the positions, velocities and local forces an ant perceives and defining its next actions within a phase and triggering conditions for transition between phases, suffice to replicate the complex behavior of treadmilling and shape morphing of the raft as emergent phenomena. We also show that two principles hold empirically in the network phase: homeostasis of area density, a constraint that couples ant activity level to shape morphing in a very simple way; and the invariance of the network topology over relevant timescales, which supports global geometrical stability in the face of chaotic ant motions. Refined by evolution over very long times, the principles and rules governing fire ant rafts suggest design possibilities for achieving stable shape morphing in decentralized systems of synthetic programmable matter.

Bioinspiration & Biomimetics
University of Colorado Boulder (US), Sherman Oaks Hospital (US), University of Colorado System (US)
Openalex Percentile: Top 37%
Micro and Nano Robotics
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Fire Ant Rafts Offer Principles and Rules for Synthetic Programmable Morphing Matter — Franck J. Vernerey, Brian Cox · Bioinspiration & Biomimetics (2026) | TGRS Research Map | TGRS