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02/03/2026 10:17

Autonomous navigation through the labyrinth - TU researchers investigate independent decision-making of droplets

Bettina Bastian Science Communication Centre - Abteilung Kommunikation
Technische Universität Darmstadt

    Tiny droplets can navigate their way through unknown environments like living cells – without sensors, computers or external control. This finding by researchers led by TU Darmstadt has now been published in the renowned journal Proceedings of the National Academy of Sciences (PNAS).

    According to a recent study, microscopic synthetic droplets can navigate autonomously. The tiny amounts of liquid are able to detect obstacles from a distance and move reliably through complex mazes – without cameras, electronics or external control. The reason for this is a mechanism that the research team led by TU Darmstadt refers to as ‘chemical echolocation’.
    Here's how it works: instead of emitting sound waves like bats in dark caves, the droplets release small amounts of chemicals into their environment as they move. These chemicals spread throughout the environment and are reflected by nearby walls and dead ends. The returning ‘echo’ subtly pushes the droplet away from blocked paths and towards open paths, thus guiding its movement.

    Generating their own signals

    ‘The droplets do not follow a pre-programmed route, nor do they respond to a signal placed at the destination,’ explains Dr Aritra Mukhopadhyay, first author of the study and postdoctoral researcher at the Institute for Condensed Matter Physics (IPKM) in the Department of Physics at TU Darmstadt. ‘Instead, they continuously generate their own signals and respond to how these return from the environment.’
    To test the mechanism, the researchers combined theory, computer simulations and laboratory experiments. In simulations, chemical droplets were placed at the entrance to labyrinth-like environments with many dead ends. The droplets consistently chose the correct path at each intersection and efficiently reached the exit, even as the maze became larger and more complex. In contrast, conventional strategies based on following a chemical source placed at the exit became unreliable with increasing distance, as the guiding signal weakened with distance.
    The team then experimentally demonstrated ‘chemical echolocation’ using millimetre-sized droplets made from simple polymer mixtures. When placed in mazes filled with water, the droplets spontaneously began to move and, remarkably, navigated to the exit without any external cues. High-speed recordings showed that the droplets slowed down near intersections, perceived the chemical ‘echo’ from dead ends, and turned away from them in time. In repeated experiments, most droplets successfully solved the maze, and their navigation time only increased gradually as the length of the maze increased.

    Potential use in robotics

    ‘This ability to make automated independent navigation decisions illustrates how synthetic active matter systems can achieve functionality solely through physical mechanisms, without requiring the complex biochemical mechanisms of their biological counterparts,’ emphasises TU professor Benno Liebchen, last author of the study, which also involved researchers from Huazhong University of Science and Technology in China.

    The results point to a new path toward autonomous microscopic systems that could be used where conventional robotics reaches its limits. Since ‘chemical echolocation’ does not require integrated electronics, sensors or calculations, it could in principle be scaled down to significantly smaller dimensions. The mechanism could one day be used in environments where remote control is difficult: for example, navigating through narrow microfluidic channels, exploring confined environments or delivering small cargo items along complex routes.
    IPKM/mih


    Contact for scientific information:

    Prof. Dr. Benno Liebchen
    Working Area: Theory of Soft Matter
    benno.liebchen@pkm.tu-darmstadt.de
    +49 6151 16-24509


    Original publication:

    Aritra K. Mukhopadhyay, Ran Niu, Linhui Fu, Kai Feng, Christopher Fujta, Qiang Zhao, Jinping Qu und Benno Liebchen: „Automated decision-making by chemical echolocation in active droplets“. In: „Proceedings of the National Academy of Sciences“, Vol. 123, Nr. 5, DOI: 10.1073/pnas.2526773123


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    Criteria of this press release:
    Journalists, Scientists and scholars
    Information technology, Physics / astronomy
    transregional, national
    Research results
    English


     

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