2D-Nature of Active Brownian Motion at Interfaces published in New J. Phys.

Two-dimensional nature of the active Brownian motion of catalytic microswimmers at solid and liquid interfaces

Two-dimensional nature of the active Brownian motion of catalytic microswimmers at solid and liquid interfaces
Kilian Dietrich, Damian Renggli, Michele Zanini, Giovanni Volpe, Ivo Buttinoni & Lucio Isa
New Journal of Physics 19, 065008 (2017)
DOI: 10.1088/1367-2630/aa7126

Colloidal particles equipped with platinum patches can establish chemical gradients in H2O2-enriched solutions and undergo self-propulsion due to local diffusiophoretic migration. In bulk (3D), this class of active particles swim in the direction of the surface heterogeneities introduced by the patches and consequently reorient with the characteristic rotational diffusion time of the colloids. In this article, we present experimental and numerical evidence that planar 2D confinements defy this simple picture. Instead, the motion of active particles both on solid substrates and at flat liquid–liquid interfaces is captured by a 2D active Brownian motion model, in which rotational and translational motion are constrained in the xy-plane. This leads to an active motion that does not follow the direction of the surface heterogeneities and to timescales of reorientation that do not match the free rotational diffusion times. Furthermore, 2D-confinement at fluid–fluid interfaces gives rise to a unique distribution of swimming velocities: the patchy colloids uptake two main orientations leading to two particle populations with velocities that differ up to one order of magnitude. Our results shed new light on the behavior of active colloids in 2D, which is of interest for modeling and applications where confinements are present.

Simon Nilsson defended his Master Thesis. Congrats!

Simon Nilsson defended his Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 14 June 2017.

Thesis title: Collective Dynamics in a Complex Environment

Thesis advisor: Giovanni Volpe

Collective behaviour is a phenomenon that often occurs in systems of many interacting individuals. Common macroscopic examples of collective behaviour are flocks of birds, swarms of insects and crowds of people. On the microscopic scale, it is often observed in so-called active systems, constituted by self-propelled particles, also known as active particles. Motile bacteria or synthetic microswim- mers are among the most commonly studied active particles.

The potential applications of collective behaviour and understanding thereof encompass multiple disciplines, ranging from robotics and medicine to algorithms, like ant colony optimization. However, the apparent complexity makes under- standing an intimidating task. Despite this, simple models have proven successful in capturing the defining characteristics of such systems.

This thesis examines a well-known model of active matter and expands it to incorporate necessary components to explore the effects a complex environment has on this pre-existing model. Additionally, a new model is proposed and explored in purely active systems as well as in complex environments. Simulations show that a phase transition between a gaseous state and the formation of metastable clusters occurs as the level of orientational noise decreases. Furthermore, they show that this model describes the formation of metastable channels in a crowded environment of passive particles.