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Description
Stephen Ebbens1 Andrew Campbell1

1, University of Sheffield, Sheffield, , United Kingdom

In order to fully realize the potential of active colloids there is an increasing drive to exploit complex behaviour, such as collective motion and self-organisation. In the main, these phenomena have been studied theoretically to date, although with sufficient experimental attention to show the viability of observing collective phenomena such as clustering. Models and simulations have also shown that the specific details of the active colloids propulsion mechanism critically alter predicted ensemble behaviour. One particular example is the link between mechanism, hydrodynamic flow field and the resulting inter-particular interactions that can lead to re-orientation and translation. In this context, here we focus on describing the way in which experimental characterisation of catalytic Janus colloids motion can provide critical information about mechanism, which in turn will assist predicting and controlling their collective self-organising structures.

In particular, we highlight a recently developed method where the combination of video microscopy analysis of tracer particles with image analysis algorithms allows the flow field around active colloids to be experimentally determined. These experimental observations are compared with predictions from theory, providing new insights into propulsion mechanism. The flow data and mechanistic implications are discussed in the context of previous observations for catalytic Janus colloid behaviour, and in respect to informing the development of more accurate predictions for collective behaviour.

However, catalytically powered motile Janus colloids present a particularly complex scenario when considering collective effects due to the ability for interactions mediated by chemical fields to re-orientate and translate neighbouring colloids, in addition to hydrodynamics. Consequently, we also discuss how analysis of tracer particle motion can allow chemical field induced effects to be assessed in certain scenarios, and describe the potential to develop new empirical models for collective motion based on these experimental data sets.

Finally, we offer a perspective on eventual routes by which the collective behaviour of active colloids may be controlled and exploited in the future to enable new applications.

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