Optical modelling of cells for improved miniaturized chip-based cytometry
Leuven | More than two weeks ago
Flow cytometry on a chip for better and more affordable healthcare
Flow cytometry is a versatile technology for cell identification and separation of the different cell species from mixed cell samples such as blood. Applications include disease diagnosis, cancer treatment and drug development. Bench-top systems are widely used in clinical and research labs. In a cytometer, a laser beam is focused on the center of a microfluidic channel and while cells are passing through the laser beam, scattering and fluorescence signals from the cells are measured and used for cell discrimination. Cells may differ in membrane protein expression, size, nucleus shape and organelle distribution which all influence their optical signature. Based on the optical signal, target cells can be sorted out downstream by integrated cell sorting modules.
At imec, we have developed miniaturized cell sorting chips for low-cost and high-speed cell sorting. See e.g. https://vimeo.com/82078661.
While miniaturization brings significant advantages in size, cost and parallelization, it puts constraints on the collection of the optical signals. To design efficient integrated photonic structures for collecting the optical signals, accurate optical models of cells are necessary.
In the context of this thesis, the student will create 3D optical models of blood cells (monocytes, lymphocytes, granulocytes, etc) and compare these models to optical properties available in the literature. First, an extensive literature and database study will be performed and can be followed by experimental cell characterization to fill in knowledge gaps. Secondly, the cell model will be implemented in a suitable full device simulation space (Maxwell equations solver) for which the student is faced with the challenge to find and evaluate the most efficient approach in terms of simulation time and memory usage. During the study, the student will learn about nanophotonic simulations, image processing, and cell biology. The work will also include Matlab/Python scripting.
Type of project: Combination of internship and thesis, Thesis
Duration: 1 academic year
Required degree: Master of Science, Master of Engineering Science
Required background: Nanoscience & Nanotechnology, Physics, Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Gunay Yurtsever (Gunay.Yurtsever@imec.be) and Sarah Libbrecht (Sarah.Libbrecht@imec.be) and Niels Verellen (Niels.Verellen@imec.be)