26 research outputs found
AdaPT Adaptable Particle Tracking for spherical microparticles in lab on chip systems
Due to its rising importance in science and technology in recent years, particle tracking in videos presents itself as a tool for successfully acquiring new knowledge in the field of life sciences and physics. Accordingly, different particle tracking methods for various scenarios have been developed. In this article, we present a particle tracking application implemented in Python for, in particular, spherical magnetic particles, including superparamagnetic beads and Janus particles. In the following, we distinguish between two sub steps in particle tracking, namely the localization of particles in single images and the linking of the extracted particle positions of the subsequent frames into trajectories. We provide an intensity based localization technique to detect particles and two linking algorithms, which apply either frame by frame linking or linear assignment problem solving. Beyond that, we offer helpful tools to preprocess images automatically as well as estimate parameters required for the localization algorithm by utilizing machine learning. As an extra, we have implemented a technique to estimate the current spatial orientation of Janus particles within the plane. Our framework is readily extendable and easy to use as we offer a graphical user interface and a command line tool. Various output options, such as data frames and videos, ensure further analysis that can be automate
Transport Efficiency of Biofunctionalized Magnetic Particles Tailored by Surfactant Concentration
Controlled transport of surface functionalized magnetic beads in a liquid
medium is a central requirement for the handling of captured biomolecular
targets in microfluidic lab-on-chip biosensors. Here, the influence of the
physiological liquid medium on the transport characteristics of functionalized
magnetic particles and on the functionality of the coupled protein is studied.
These aspects are theoretically modeled and experimentally investigated for
prototype superparamagnetic beads, surface functionalized with green
fluorescent protein immersed in buffer solution with different concentrations
of a surfactant. The model reports on the tunability of the steady-state
particle substrate separation distance to prevent their surface sticking via
the choice of surfactant concentration. Experimental and theoretical average
velocities are discussed for a ratchet like particle motion induced by a
dynamic external field superposed on a static locally varying magnetic field
landscape. The developed model and experiment may serve as a basis for
quantitative forecasts on the functionality of magnetic particle transport
based lab-on-chip devices