Colloid and Polymer Science, August 2020 (article)
We present a novel approach for characterizing the properties and performance of active matter in dilute suspension as well as in crowded environments. We use Super-Heterodyne Laser-Doppler-Velocimetry (SH-LDV) to study large ensembles of catalytically active Janus particles moving under UV illumination. SH-LDV facilitates a model-free determination of the swimming speed and direction, with excellent ensemble averaging. In addition, we obtain information on the distribution of the catalytic activity. Moreover, SH-LDV operates away from walls and permits a facile correction for multiple scattering contributions. It thus allows for studies of concentrated suspensions of swimmers or of systems where swimmers propel actively in an environment crowded by passive particles. We demonstrate the versatility and the scope of the method with a few selected examples. We anticipate that SH-LDV complements established methods and paves the way for systematic measurements at previously inaccessible boundary conditions.
Nature Communications, 11(2210), May 2020 (article)
Symmetry breaking and the emergence of self-organized patterns is the hallmark of com-
plexity. Here, we demonstrate that a sessile drop, containing titania powder particles with
negligible self-propulsion, exhibits a transition to collective motion leading to self-organized
ﬂow patterns. This phenomenology emerges through a novel mechanism involving the
interplay between the chemical activity of the photocatalytic particles, which induces Mar-
angoni stresses at the liquid–liquid interface, and the geometrical conﬁnement provided by
the drop. The response of the interface to the chemical activity of the particles is the source
of a signiﬁcantly ampliﬁed hydrodynamic ﬂow within the drop, which moves the particles.
Furthermore, in ensembles of such active drops long-ranged ordering of the ﬂow patterns
within the drops is observed. We show that the ordering is dictated by a chemical com-
munication between drops, i.e., an alignment of the ﬂow patterns is induced by the gradients
of the chemicals emanating from the active particles, rather than by hydrodynamic
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems