Self-organization of active matter: The role of interactions
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Abstract
Active matter has received considerable attention in recent years. Its constituents, active particles, have the ability to convert free energy into directed motion by which they drive themselves out of thermal equilibrium.
The field of active matter encompasses a multitude of biological systems on different length scales: from running, flying or swimming macroscopic animals down to motile bacteria and sperm cells. Moreover, synthetic microscopic active particles that either draw inspiration from biological microswimmers or propel via novel mechanisms have been devised. The combination of self-propelled motion and interactions between active particles gives rise to a wealth of fascinating self-organized collective behaviors, such as the formation of flocks of birds, collective cell migration and the motility-induced phase separation of active Janus colloids. In this thesis, we investigate several self-organized phenomena in systems of active particles via numerical simulations and analytical theory. A major goal of this work is to elucidate how the properties of interactions (e.g., their strength and range) affect the emergent collective behavior. We first deal with the motility-induced phase separation of active particles that interact via short-ranged repulsive potentials. In contrast to the conventional model of active Brownian particles, we take into account the self-propulsion mechanism via a chemical reaction in a thermodynamically consistent way. This influences the resulting phase behavior, especially for soft particles. In a second system, inspired by bacterial quorum sensing, we study active particles that discontinuously change their motility at a threshold concentration of self-generated chemical signals. This interaction leads to a separation of the system into regions of different motility. Via numerical simulations, we show that the densities and sizes of the phases sensitively depend on the concentration threshold, the interaction range and the self-propulsion speed. We compare our results to experiments of light-activated Janus colloids and develop a mean-field theory that yields quantitative agreement with the simulations. Finally, we investigate active colloidal clusters that self-assemble from passive building blocks. Using the approach speeds of particle pairs obtained from experiments as input, we develop a model that disentangles the interplay of reciprocal and nonreciprocal effective interactions giving rise to self-propulsion and quantitatively predicts the motion of larger clusters.