Preparation and 3D Tracking of Catalytic Swimming Devices

Abstract

We report a method to prepare catalytically active Janus colloids that "swim" in fluids and describe how to determine their 3D motion using fluorescence microscopy. One commonly deployed method for catalytically active colloids to produce enhanced motion is via an asymmetrical distribution of catalyst. Here this is achieved by spin coating a dispersed layer of fluorescent polymeric colloids onto a flat planar substrate, and then using directional platinum vapor deposition to half coat the exposed colloid surface, making a two faced "Janus" structure. The Janus colloids are then re-suspended from the planar substrate into an aqueous solution containing hydrogen peroxide. Hydrogen peroxide serves as a fuel for the platinum catalyst, which is decomposed into water and oxygen, but only on one side of the colloid. The asymmetry results in gradients that produce enhanced motion, or "swimming". A fluorescence microscope, together with a video camera is used to record the motion of individual colloids. The center of the fluorescent emission is found using image analysis to provide an x and y coordinate for each frame of the video. While keeping the microscope focal position fixed, the fluorescence emission from the colloid produces a characteristic concentric ring pattern which is subject to image analysis to determine the particles relative z position. In this way 3D trajectories for the swimming colloid are obtained, allowing swimming velocity to be accurately measured, and physical phenomena such as gravitaxis, which may bias the colloids motion to be detected.

Tracking Janus microswimmers in 3D with machine learning

“…Therefore, a simple approach using the particle's grayscale moment of inertia, which varied as a function of its vertical position, was developed. Similar to the strategy in 20 , an LUT of the microswimmers' evolving moment of inertia was extracted from a series of particle Z-stacks, to which a cubic polynomial was fitted (see Electronic Supplementary Information (ESI) of 25 ). However, the over-reliance on a singular image property averaged over a few particles is undesirable, and motivates a more robust approach to the 3D tracking of non-fluorescent Janus microswimmers with conventional wide-field microscopy techniques.…”

“…Similar to the strategy in ref. 20, an LUT of the microswimmers' evolving moment of inertia was extracted from a series of particle Z -stacks, to which a cubic polynomial was fitted (see ref. 25 of ESI‡).…”

“…To overcome these issues, Campbell et al used the method previously proposed by Spiedel et al for passive particles to track the vertical position of fluorescent gravitactic Janus microswimmers from 2D microscopy images using the outermost radius of the concentric rings of the fluorescent particles as they swim out of focus. 19,20 Unlike confocal microscopy, this method does not require a rigorous model and knowledge of the optical properties of the microscope. A single Janus particle was fixated in gellan gum, from which the ''bright ring radius'' of the fluorescent particle was extracted at different heights, to which a calibration curve was fitted using a cubic polynomial.…”

Tracking Janus microswimmers in 3D with Machine Learning

“…Therefore, a simple approach using the particle's grayscale moment of inertia, which varied as a function of its vertical position, was developed. Similar to the strategy in (20), an LUT of the microswimmers' evolving moment of inertia was extracted from a series of particle Z-stacks, to which a cubic polynomial was fitted (see Supporting Information of ( 26)). However, the over-reliance on a singular image property averaged over a few particles is undesirable, and motivates a more robust approach to the 3D tracking of non-fluorescent Janus microswimmers with conventional wide-field microscopy techniques.…”