Spatiotemporal characterization of emergent behavior of self-propelled oil droplet

Abstract: To further understand the complex behavior of swimming microorganisms, the spontaneous motion of nonliving matter provides essential insights. While substantial research has focused on quantitatively analyzing complex behavioral patterns, characterizing these dynamics aiming for inclusive comparison to the behavior of living systems remains challenging. In this study, we experimentally and numerically investigated the 'life-like' behavior of an oil droplet in an aqueous surfactant solution by identifying behavioral modes of spontaneous motion patterns in response to varying physical parameters, such as volume and oil concentration. Leveraging data-driven nonparametric dynamical systems analysis, we discovered the low dimensionality and nonlinearity of the underlying dynamical system governing oil droplet motion. Notably, our simulations demonstrate that the two-dimensional Langevin equations effectively reproduce the overall behavior experimentally observed while retaining the rational correspondence with physical parameter interpretations. These findings not only elucidate the fundamental dynamics governing the spontaneous motion of oil droplet systems but also suggest potential pathways for developing more descriptive models that bridge the gap between nonliving and living behaviors.