Bacterial turbulence drives interfacial waves and shape dynamics in phase-separated droplets

Researchers have discovered that the activity of bacterial colonies can induce turbulence, which in turn generates waves at the interface of immiscible liquid droplets. This phenomenon, observed in two-phase liquid systems, reveals a mechanism by which biological energy at the microscale can influence fluid dynamics and the morphology of soft structures. The study opens new avenues for understanding how biological systems interact with their physical environment at the level of complex fluids. The team used droplets composed of two immiscible liquids, one aqueous and one oily, into which active bacteria were introduced. The collective motility of the bacteria in the aqueous phase generated turbulent flows. These flows not only agitated the liquid but also exerted forces on the interface between the two phases, leading to the formation of waves and dynamic changes in the droplet's shape. The magnitude and pattern of these waves depended on bacterial density and the viscoelastic properties of the fluids. This finding is relevant to fields such as biophysics and soft materials engineering. Understanding how biological activity can shape interfaces and generate dynamic patterns in fluid systems is crucial for designing new active materials, optimizing bioremediation processes, or even modeling the formation of complex biological structures. The results suggest that microorganism-induced turbulence could be a key factor in the self-organization of biological systems at mesoscopic scales.

New Algorithm Inspired by Slime Mold Optimizes Transport on Graphs

Researchers have developed a new algorithm to solve the distributed optimal transport problem on graphs, drawing inspiration from the behavior of the slime mold, *Physarum polycephalum*. This single-celled organism is known for its ability to find efficient paths between food sources, forming networks of tubes that minimize transport costs. The algorithm mimics this biological process, iteratively adjusting flows in a network to achieve an optimal configuration. Optimal transport seeks the most efficient way to move resources between multiple sources and destinations, minimizing a total cost. It is a fundamental challenge in logistics, communication networks, and other fields. Traditional methods often require centralized computation and can be inefficient for very large or dynamic graphs. The *Physarum*-based approach offers a distributed solution, where each node in the network makes local decisions that, collectively, lead to a globally optimal solution. The algorithm operates by simulating a flow of "nutrients" through the edges of the graph. The conductance of each edge is adjusted based on the flow passing through it, analogous to how *Physarum* slime mold thickens tubes that carry more nutrients. This iterative process converges towards a flow distribution that minimizes the total transport cost. Results show that this method can be competitive with existing algorithms, especially in scenarios where decentralization and adaptability are crucial. This breakthrough has significant implications for the design of robust and efficient networks, from urban planning and energy distribution to route optimization in transportation and communication networks. The ability to solve these types of problems in a distributed manner opens the door to more resilient and scalable systems that can dynamically adapt to changes in demand or network topology, without relying on centralized control.