(Nanowerk News) Active Brownian motion describes particles that can propel themselves forward, while still experiencing random Brownian motion as they are jostled by neighboring particles.
Through a new analysis published in EPR E (“Brownian particles are active in a biased periodic potential”), Meng Su at Northwestern Polytechnical University in China, together with Benjamin Lindner at Humboldt University of Berlin, Germany, have found that this movement can be accurately described using four different mathematical patterns.
Active Brownian particles can be found in a wide variety of scenarios in nature: from sub-cellular structures pulled by biomolecular motors, to the movement of entire herds, which can act collaboratively to find food or avoid predators more easily. Recently, researchers developed artificial particles that behave very much like their natural counterparts – presenting exciting new opportunities in medical robotics, and many other cutting-edge areas of research. Ultimately, Su and Lindner’s discoveries may yield exciting new insights into how these systems behave.
The motion of Active Brownian particles is known to depend on the friction they experience, as well as external bias forces, which bend their path in a certain direction. Using computer simulations of active Brownian systems, supported by simple calculations, Su and Lindner found that variations in these two parameters can force the system into one of four possible states.
When a balance is struck between the biased active driving force, and the friction experienced by a particle, it will enter a ‘locked’ state – limiting its motion to a small region. When the driving force instead dominates friction, the particle will move continuously in mostly straight lines: entering a ‘driving’ state. Alternatively, the particle can switch back and forth between the locked and running state, or between two different running states. When the system is subjected to random disturbances, the average speed of the particles will change depending on the intensity of the noise – but their motion stays in one of these four states.