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Federico Bedini


Rel. Danilo Demarchi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2019

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Lab-on-chip (LoC) devices embody several key features, including the use of small sample volume, control over fluid dynamics, easy integration of cell manipulation techniques (cell sorting, cell isolation) and higher throughput than conventional analytical methods (e.g. patch clamp) [1-2]. Impedance flow cytometry (IFC) has been widely adopted for high-throughput cell detection and manipulation, sorting and counting. IFC works by measuring the impedance between a set of electrodes as single cells pass through a microchannel [3]. IFC, however, allows only for short-term single-cell analysis. Microelectrode arrays (MEAs) are often used to perform long-term analysis of cell populations. Coupled with electrical impedance spectroscopy (EIS), adhesion, morphology, proliferation and temporal evolution of cells can be analysed [4]. In this work, a novel LoC device is proposed, which integrates in-channel IFC and in-chamber MEAs in the same microfluidic platform. The microfluidic chip is fabricated on standard Si wafers through a CMOS-compatible photolithographic process, allowing for future microelectronics integration. Several versions of the chip are realized on the same Si wafer, diced and singularly tested to evaluate the effect of the geometrical parameters and channel configuration on the detection sensitivity. The first design includes IFC electrodes of different sizes at the bottom of a 10x10 μm2 microchannel, and a culture chamber comprising of 9 microwells with interdigitated electrodes. Different IDE parameters (width from 10 μm to 100 μm, gap from 5 μm to 20 μm) are also realized to assess optimum geometries for high sensitivity and SNR. The IFC and MEA electrodes are characterised using a multichannel impedance analyser. The performance of the microfluidic device is tested in a fluidic system with microbeads of different sizes (4-6-8 μm). Integration of IFC and MEAs in the same platform enables automated, high-throughput single-cell sorting and manipulation and long-term network analysis, allowing for more comprehensive studies of cell cultures.

Relators: Danilo Demarchi
Academic year: 2018/19
Publication type: Electronic
Number of Pages: 130
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering)
Classe di laurea: New organization > Master science > LM-29 - ELECTRONIC ENGINEERING
Ente in cotutela: TU Delft - section bioelectronics (PAESI BASSI)
Aziende collaboratrici: Technische Universiteit Delft
URI: http://webthesis.biblio.polito.it/id/eprint/10981
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