Micro-swimmers can be biological, such as plankton, or engineered particles, such as nanomotors. Plankton contributes to global ecosystems by producing oxygen, which forms the basis of the ocean food web.
Free-Riding in the Current
Navid Mousavi has created new methods for modeling and studying the navigation of micro-swimmers by combining active matter physics with machine learning principles. The thesis finds optimal behaviors for plankton to survive in their turbulent habitat.
“In the model, plankton use local information for navigation, reflecting the real-world conditions that these small swimmers encounter. Unlike previous models where navigation was based on global information,” says Navid Mousavi.
The research also showed that micro-swimmers can utilize the flow to move faster than they can on their own, which is an important insight for both biological and artificial applications.
Another exciting result of the study is the discovery of optimal behavior to avoid high turbulent strain. Surprisingly, it is observed that micro-swimmers tend to swim against the current to keep their position in low-strain regions.
“This behavior seems to be crucial for survival and allows plankton to avoid predators and stay in nutrient-rich zones,” says Navid Mousavi.
Knowledge for Medicine Development
All the strategies found were shown to work effectively in several different scenarios, meaning they can be applied to real-life situations.
The results of the study provide important knowledge that has several applications. An example is in medicine, where it could help develop smart micro-swimmers that can deliver drugs directly to specific areas of the body, making treatments more effective. Environmentally, these tiny swimmers could help clean up microplastics from our oceans and contribute to a healthier planet.
“In the future, we will need to validate the model in experiments, both with natural plankton and artificial micro-swimmers,” says Navid Mousavi.
The researchers also plan to investigate more complex models that deals with energy efficiency and the collective behavior of multiple swimmers.
