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  • Featured in Physics
  • Open Access

Closed-Loop Control of Active Nematic Flows

Katsu Nishiyama*, John Berezney*, Michael M. Norton*, Akshit Aggarwal, Saptorshi Ghosh, Zahra Zarei, Michael F. Hagan, and Seth Fraden†

Zvonimir Dogic

  • *These authors contributed equally to this work.
  • †Contact author: fraden@brandeis.edu
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Phys. Rev. X 15, 041053 – Published 19 December, 2025

DOI: https://doi.org/10.1103/4hrx-6rdq

Abstract

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

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Physics Subject Headings (PhySH)

Focus

Reining In a Chaotic Fluid

Published 19 December, 2025

Fluid flows mimicking biological flows can be controlled in the lab using a feedback system, which could be useful in robotics and other technologies.

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Popular Summary

Active fluids—materials made of energy-consuming components such as protein filaments and molecular motors—are notoriously unstable. They often switch unpredictably between different flow states, respond strongly to small temperature changes, and drift over time as their biological components age. In this study, we demonstrate a way to control this chaotic behavior using feedback. By embedding a light-responsive active fluid in a proportional-integral (PI) control loop, we create a system that automatically adjusts the intensity of applied light in real time. This approach allows us to keep the fluid flowing at a target speed despite internal fluctuations and external disturbances.

Our system combines microscopy, data analysis, and optical control into a single feedback platform. We continuously record images of the fluid as it moves, and we use machine learning algorithms to calculate how fast and in what direction the material is flowing. The measured average flow speed is compared to a preset value, and the difference between them is used by the PI controller to decide how much to change the light intensity. Light acts as a trigger for the molecular motors, forming clusters that push and pull on the surrounding filaments to drive motion. As a result, the feedback loop automatically strengthens or weakens the light input to stabilize the overall flow, even when we intentionally apply large temperature changes.

By adjusting the control settings, we observe complex dynamics, including oscillations that arise from the competition between the controller’s timing and the material’s internal response rates. Using these insights, we can design more sophisticated feedback schemes to shape how active fluids move and organize, paving the way for creating new dynamic patterns and self-regulating materials.

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Phys. Rev. X 15, 041053– Published 19 December, 2025
  • Received 13 March 2025
  • Accepted 9 October 2025
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