The burgeoning field of active matter, which studies systems of self-propelled particles that consume energy to move, has long challenged scientists seeking to predict their collective behavior. From flocks of birds to bacterial colonies, these systems are governed by complex, non-equilibrium dynamics. A persistent question has been how individual particles—such as bacteria—distribute themselves within a crowded environment, a process fundamental to understanding everything from the formation of biofilms to the transport of microscopic payloads.
In a significant advance, a collaborative team of physicists and microbiologists has uncovered the fundamental laws that govern this distribution. Their research reveals that the arrangement of living bacteria is dictated by a nuanced interplay between the particles’ own motility and their attraction to specific liquid environments. The findings demonstrate a “like-attracts-like” phenomenon, providing a new framework for predicting the organization of these complex systems and offering insights that span biology, physics, and engineering.
Understanding Active Matter Systems
Active matter is a class of materials whose individual components convert stored or ambient energy into mechanical work, resulting in directed motion. Unlike passive particles that only jiggle randomly due to thermal energy (Brownian motion), active particles are inherently out of equilibrium. This category includes a vast range of agents, from microscopic swimmers like bacteria and synthetic nanomotors to macroscopic groups such as schools of fish and human crowds. The constant energy consumption and self-propulsion lead to emergent collective behaviors that are not seen in conventional materials, such as swarming, turbulent-like flows, and spontaneous pattern formation.
A primary goal in this field is to develop predictive models that can explain how these systems organize themselves. Understanding the distribution of particles is crucial because it underlies many large-scale phenomena. For example, the way bacteria aggregate is the first step in the creation of biofilms, which have major implications for medicine and industry. Similarly, controlling the distribution of self-propelled microrobots is essential for future applications in targeted drug delivery or materials self-assembly. The inherent non-equilibrium nature of these systems, however, means that traditional statistical mechanics often fall short, requiring new principles to be discovered.
An Interdisciplinary Breakthrough
To tackle this challenge, researchers from the Ulsan National Institute of Science and Technology (UNIST) and Stanford University combined expertise from physics and microbiology. The study, published in the journal Physical Review Letters, was led by Professor Joonwoo Jeong of the UNIST Department of Physics, Professor Robert J. Mitchell from the UNIST Department of Biological Sciences, and Professor Sho C. Takatori at Stanford University. This collaboration was instrumental in bridging the gap between the physical principles of particle motion and the complex biological behavior of living microorganisms.
By focusing on bacteria as a model system for self-propelled particles, the team was able to study a well-understood biological agent whose motility is quantifiable. Bacteria, such as E. coli, swim by rotating flagella, a form of self-propulsion that makes them a perfect example of active matter. The interdisciplinary approach allowed the researchers to not only observe the physical phenomena but also ground their findings in the known behaviors of living systems, adding a layer of complexity that is often missing from studies using purely synthetic particles.
A New Law of Distribution
The central discovery of the research is a new principle that clarifies how motile particles are spatially arranged. The team found that the distribution is not random but is instead governed by a balance between two key factors: the intrinsic motility of the particles and their affinity for the specific liquid environment they are in. Motility refers to the particle’s ability to move independently, a defining characteristic of active systems that separates them from passive particles. Affinity, in this context, describes the chemical or physical preference of the particles for one type of liquid environment over another, which can influence where they tend to linger.
This finding moves beyond earlier models that often focused primarily on particle-to-particle interactions or collisions with boundaries to explain collective structures. By showing that the particle-fluid interaction is a critical component, the research introduces a new dimension to the puzzle of active matter organization. It suggests that the environment itself plays a dynamic role in shaping the architecture of active systems, guiding the assembly of particles in predictable ways.
The ‘Like-Attracts-Like’ Principle
The most compelling outcome of this balance is a phenomenon the researchers described as being consistent with a “like-attracts-like” principle. This means that particles with similar properties tend to cluster together. In this case, bacteria with a certain motility level and environmental preference will preferentially gather in regions that are most favorable to them, leading to non-uniform distributions. This is a form of self-organization, where complex patterns emerge spontaneously from the simple rules governing individual particles.
This principle provides a powerful yet intuitive explanation for the complex patterns observed in bacterial suspensions and other active fluids. It helps explain why some areas within a fluid might become densely populated with bacteria while others remain sparse. This emergent behavior is a hallmark of active matter and is fundamental to understanding how microscopic agents can collaborate to produce large-scale structures without central coordination.
Implications for Microrobotics and Medicine
The discovery of these governing laws has significant practical implications. The ability to predict and control the distribution of self-propelled particles is a key goal for the engineering of microrobotic systems. By tuning the motility of synthetic microswimmers or altering the chemical landscape of the fluid they move through, engineers could guide them to assemble at specific locations. This could be used to deliver drugs to a precise target within the body or to build microscopic structures on-demand.
In medicine, a deeper understanding of bacterial distribution could offer new ways to combat biofilm formation. Biofilms are communities of bacteria that adhere to surfaces and are notoriously resistant to antibiotics. They are a major source of persistent infections. By understanding the physical principles that drive their initial formation—the aggregation of individual bacteria—researchers may be able to develop strategies to disrupt this process. Furthermore, the work has applications in reproductive medicine, where selecting sperm cells based on their motility is a critical step in certain fertility treatments. This research provides a foundational framework that could inform the design of more efficient selection devices.
