Rapid and reliable diagnostics of a disease represents one of the main focuses of today’s academic and industrial research in the development of new sensor prototypes and improvement of existing technologies. With respect to demographic changes and inhomogeneous distribution of the clinical facilities worldwide, especially in rural regions, a new generation of miniaturized biosensors is highly demanded offering an easy deliverability, low costs and sample preparation and simple usage. This work focuses on the integration of nanosized electronic structures for high-specific sensing applications into adequate microfluidic structures for sample delivery and liquid manipulation.
Based on the conjunction of these two technologies, two novel sensor platforms were prototyped, both allowing label-free and optics-less electrochemical detection ranging from molecular species to eukaryotic micron-sized human cells.:Table of Figures
List of Tables
Abbreviations
List of Symbols
1 Introduction
1.1 Motivation
1.2 State of the art
1.3 Scope of this thesis
2 Fundamentals
2.1 Sensors at the nanoscale
2.2 Transistors technology
2.2.1 p-n junction
2.2.3 The MOSFET
2.2.4 The ISFET and BioFET
2.3 Impedance measurements for biodetection
2.3.1 Electrical impedance spectroscopy
2.3.2 Electrical impedance cytometry
2.4 Microfluidics
2.4.1 Definition
2.4.2 Droplet-based microfluidics
2.5 Biomarkers for sensing applications
2.5.1 Peripheral blood mononuclear cells (PBMCs)
2.5.2 Physical parameters
3. Material and methods
3.1 General
3.1.1 Materials and chemicals
3.1.2 Surface cleaning
3.2 Lithography
3.2.1 Electron beam lithography
3.2.2 Laser lithography
3.2.3 UV lithography
3.2.4 Soft lithography
3.3 Thermal deposition of metals
3.4 APTES functionalization
3.4.1 Fluorescent labeling of APTES
3.5 Measurement devices
3.5.1 SiNW FET measurements
3.5.2 Electrical Impedance cytometry measurements
3.6 Bacteria and cell cultivation
3.6.1 PBMC purification and treatment
3.6.2 Bacteria cultivation
4. Compact nanosensors probe microdroplets
4.1 Overview
4.2 Fabrication
4.2.1 SiNW FET fabrication
4.2.2 SiNW FET modification for top-gate sensing
4.3 Electrical characterization
4.4 Flow-focusing droplet generation
4.4.1 Flow-focusing geometry
4.4.2 Flow-focusing droplet characterization
4.4.3 Microfluidic integration
4.5 Deionized water droplet sensing
4.6 Phosphate-buffered saline (PBS) droplet sensing
4.6.1 Influence of the droplet’s ionic concentration
4.6.2 Plateau formation in dependence of the droplet’s settling time
4.6.3 Droplet analysis by their ratio
4.6.4 Dependence on pH value
4.6.5 Long time pH sensing experiment
4.6.6 Dependence on ionic concentration
4.7 Tracking of reaction kinetics in droplets
4.7.1 Principle and setup of the glucose oxidase (GOx) enzymatic test
4.7.2 GOx enzymatic assay
4.8 Stable baseline by conductive carrier phase
5. Impedance-based flow cytometer on a chip
5.1 Overview
5.2 Overview of the fabrication of the sensor device
5.3 COMSOL simulation of sensing area
5.3.1 Prototyping of the sensing geometry
5.3.2 Optimization of the sensing geometry
5.3.3 Evaluation of the working potential
5.3.4. Scaling of the sensing area
5.4 Fabrication of the nanoelectronic sensing structure
5.4.1 Nanofabrication and analysis
5.4.2 Evaluation of the proximity effect
5.5 Microcontacting of nanostructured sensing structures
5.6 Electrical characterization of the sensing structure
5.6.1 Characterization in alternating current
5.6.2 Characterization in direct current (DC)
5.7 Scaling effect of nanostructures in static sensing conditions
5.8 Multi-analyte detection on the sensor
5.9 Microfluidic focusing system
5.9.1 1D focusing using FITC-probed deionized water
5.9.2 2D Focusing using fluorescent microparticles
5.10 Microfluidic integration of the two technologies
5.11 Dynamic SiO2 particle detection
5.11.1 Single particle detection
5.11.2 Scatter plot representation
5.11.3 Effect of the sensing area in dynamic particle detection
5.11.4 Dynamic detection of SiO2 particles with different diameters
5.12 Detection of peripheral blood mononuclear cells (PBMCs)
5.12.1 Overview
5.12.2 PBMC classification detected by impedance cytometry
5.12.3 PBMC Long-time detection
5.13 Detection of acute myeloid leukemia by impedance cytometry
5.13.1 Manual analysis of the output response
5.13.2 Learning algorithm for automatic cell classification
5.14 Exploring the detection limit of the device
6. Summary and outlook
Scientific output
References
Acknowledgements / Rasche und zuverlässige biologische Krankheitsdiagnostik repräsentiert eines der Hauptfokusse heutiger akademischer und industrieller Forschung in der Entwicklung neuer Sensor-Prototypen und Verbesserung existierender Technologien. In bezug auf weltweite demographische Änderungen und hohe Distanzen zu Kliniken, besonders in ländlichen Gegenden, werden zusätzliche Anfordungen an neue miniaturisierte Biosensor-Generationen gestellt, wie zum Beispiel ihre Transportfähigkeit, geringe Kosten und Probenpräparation, sowie
einfache Handhabung. Diese Dissertation beschäftigt sich mit der Integration nanoskalierter Strukturen zur Detektion chemischer und biologischer Spezies und mikrofluidischen Kanälen zu deren Transport und zur Manipulation der Ströme. Basierend auf der Verbindung dieser beiden Technologien wurden zwei Sensor-Plattformen entwickelt, die eine markierungsfreie und nicht-optische elektrische Detektion von Molekülen bis zu eukaryotischen menschlichen Zellen erlauben.:Table of Figures
List of Tables
Abbreviations
List of Symbols
1 Introduction
1.1 Motivation
1.2 State of the art
1.3 Scope of this thesis
2 Fundamentals
2.1 Sensors at the nanoscale
2.2 Transistors technology
2.2.1 p-n junction
2.2.3 The MOSFET
2.2.4 The ISFET and BioFET
2.3 Impedance measurements for biodetection
2.3.1 Electrical impedance spectroscopy
2.3.2 Electrical impedance cytometry
2.4 Microfluidics
2.4.1 Definition
2.4.2 Droplet-based microfluidics
2.5 Biomarkers for sensing applications
2.5.1 Peripheral blood mononuclear cells (PBMCs)
2.5.2 Physical parameters
3. Material and methods
3.1 General
3.1.1 Materials and chemicals
3.1.2 Surface cleaning
3.2 Lithography
3.2.1 Electron beam lithography
3.2.2 Laser lithography
3.2.3 UV lithography
3.2.4 Soft lithography
3.3 Thermal deposition of metals
3.4 APTES functionalization
3.4.1 Fluorescent labeling of APTES
3.5 Measurement devices
3.5.1 SiNW FET measurements
3.5.2 Electrical Impedance cytometry measurements
3.6 Bacteria and cell cultivation
3.6.1 PBMC purification and treatment
3.6.2 Bacteria cultivation
4. Compact nanosensors probe microdroplets
4.1 Overview
4.2 Fabrication
4.2.1 SiNW FET fabrication
4.2.2 SiNW FET modification for top-gate sensing
4.3 Electrical characterization
4.4 Flow-focusing droplet generation
4.4.1 Flow-focusing geometry
4.4.2 Flow-focusing droplet characterization
4.4.3 Microfluidic integration
4.5 Deionized water droplet sensing
4.6 Phosphate-buffered saline (PBS) droplet sensing
4.6.1 Influence of the droplet’s ionic concentration
4.6.2 Plateau formation in dependence of the droplet’s settling time
4.6.3 Droplet analysis by their ratio
4.6.4 Dependence on pH value
4.6.5 Long time pH sensing experiment
4.6.6 Dependence on ionic concentration
4.7 Tracking of reaction kinetics in droplets
4.7.1 Principle and setup of the glucose oxidase (GOx) enzymatic test
4.7.2 GOx enzymatic assay
4.8 Stable baseline by conductive carrier phase
5. Impedance-based flow cytometer on a chip
5.1 Overview
5.2 Overview of the fabrication of the sensor device
5.3 COMSOL simulation of sensing area
5.3.1 Prototyping of the sensing geometry
5.3.2 Optimization of the sensing geometry
5.3.3 Evaluation of the working potential
5.3.4. Scaling of the sensing area
5.4 Fabrication of the nanoelectronic sensing structure
5.4.1 Nanofabrication and analysis
5.4.2 Evaluation of the proximity effect
5.5 Microcontacting of nanostructured sensing structures
5.6 Electrical characterization of the sensing structure
5.6.1 Characterization in alternating current
5.6.2 Characterization in direct current (DC)
5.7 Scaling effect of nanostructures in static sensing conditions
5.8 Multi-analyte detection on the sensor
5.9 Microfluidic focusing system
5.9.1 1D focusing using FITC-probed deionized water
5.9.2 2D Focusing using fluorescent microparticles
5.10 Microfluidic integration of the two technologies
5.11 Dynamic SiO2 particle detection
5.11.1 Single particle detection
5.11.2 Scatter plot representation
5.11.3 Effect of the sensing area in dynamic particle detection
5.11.4 Dynamic detection of SiO2 particles with different diameters
5.12 Detection of peripheral blood mononuclear cells (PBMCs)
5.12.1 Overview
5.12.2 PBMC classification detected by impedance cytometry
5.12.3 PBMC Long-time detection
5.13 Detection of acute myeloid leukemia by impedance cytometry
5.13.1 Manual analysis of the output response
5.13.2 Learning algorithm for automatic cell classification
5.14 Exploring the detection limit of the device
6. Summary and outlook
Scientific output
References
Acknowledgements
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:72324 |
| Date | 02 October 2020 |
| Creators | Schütt, Julian |
| Contributors | Cuniberti, Gianaurelio, Meroçi, A., Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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