At the cutting edge of the chemical and biological research, innovation takes place in a field referred to as Lab on Chip (LoC), a multi-disciplinary area that combines biology, chemistry, electronics, microfabrication, and fluid mechanics. Within this field, droplets have been used as microreactors to produce advanced materials like quantum dots, micro and nanoparticles, active pharmaceutical ingredients, etc. The size of these microreactors offers distinct advantages, which were not possible using batch technologies. For example, they allow for lower reagent waste, minimal energy consumption, increased safety, as well as better process control of reaction conditions like temperature regulation, residence times, and response times among others. One of the biggest drawbacks associated with this technology is its limited production volume that prevents it from reaching industrial applications. The standard production rates for a single droplet microfluidic device is in the range of 1-10mLh-1, whereas industrial applications usually demand production rates several orders of magnitude higher. Although substantial work has been recently undertaken in the development scaled-out solutions, which run in parallel several droplet generators. Complex fluid mechanics and limitations on the manufacturing capacity have constrained these works to explore only in-plane parallelization. This thesis investigates a three-dimensional parallelization by proposing a microfluidic system that is comprised of a stack of droplet generation layers working on the liquid-liquid ow regime. Its realization implied a study of the characteristics of conventional droplet generators and the development of a fabrication process for 3D networks of microchannels. Finally, the combination of these studies resulted in a functional 3D parallelization system with the highest production rate (i.e. 1 Lh-1) at the time of its publication. Additionally, this architecture can reach industrially relevant production rates as more devices can be integrated into the same chip and many chips can compose a manufacturing plant. The thesis also addresses the concerns about system reliability and quality control by proposing capacitive and radio frequency resonator sensors that can measure accurately increments as small as 2.4% in the water-in-oil volume fraction and identify errors during droplet production.

A novel hierarchical flexing and stretching strategy for rigid semiconducting substrates was devised. Architectures for comprehensively compliant semiconductors were created as a result. Si and GaN-on-Si have been segmented into both highly flexible and rigid segments. An advanced controlled cleavage technique has been integrated into the manufacturing process. The bending radius of the substrate has been decoupled from the substrate thickness thus allowing for higher mechanical stability, while achieving bending radii below 250 .m. Novel fabrication workflows have been created, one of which is completely compatible with CMOS fabrication techniques, while still being cost effective. Each of the rigid segments have been designed to carry in excess of its own weight. The reliability of the interconnecting springs was examined by rugged cyclic bending and twisting tests. Finite element simulations in COMSOL exhibited no stress for the rigid segments. For the first time a flexible and/or stretchable Si substrate has been integrated with pick and place tool technology. Additionally the platform serves as a More-than-Moore technology, by folding the monocrystalline substrate on top of itself, while routing power through the flexible segments. This More-than-Moore (MtM) technology has the advantages of System-in-Package (SiP) but does not have the additional costs. From this compliant approach a qubic 4D electronic platform was created. An aerially deployable electronic system was achieved by incorporating thermal paste into the qubic platform. Energy storage, sensing, and actuating were successfully tested on the system. Buried cavities for microfluidics were developed for on-chip chemical and biological processes. A platform was developed for µTF-SOFCs deposition. Cavities were interconnected subterraneously and columnar anodes were developed to enhance the fuel flow in the fuel cell electrode. The triple phase boundary (TPB) was enhanced by over an order of magnitude in comparison to standard processing techniques. A subsequent, microfluidic platform was developed for biological applications. The wettability of the platform gave good results for water, as well as for neurobasal media buffer. Tests indicate that neurons can grow directly on the platform.

Cette thèse porte sur l’étude de la variabilité de la croissance de bactéries en gouttes micro-fluidiques. Dans un premier temps, la puce micro-fluidique utilisée au cours de la thèse est présentée. Elle permet d’encapsuler des bactéries individuelles dans 1500 gouttes d’un nano litre, et de suivre leur croissance en parallèle grâce à la mesure de leur fluorescence par microscopie. La relation entre fluorescence mesurée et nombre de bactérie est discutée, et plusieurs questions techniques, comme la variabilité de taille des gouttes, l’hétérogénéité de fluorescence des bactéries, sont mesurées et leurs conséquences sur les mesures de croissance quantifiées. Dans un second temps, nous développons un modèle probabiliste qui permet, à partir de la variabilité des temps de divisions des bactéries, de prédire la variabilité de croissance entre les gouttes. Pour ce faire, nous adaptons le modèle classique de Bellman-Harris. La distribution aléatoire du nombre initial de bactérie par gouttes, ainsi que les temps de divisions différents des premières générations de bactéries sont ajoutées au modèle pour l’adapter à notre système expérimental. Les contributions de ces différentes sources de variabilité à la variabilité inter-gouttes de croissance des populations de bactéries sont quantifiées, et le modèle permet bien d’expliquer la variabilité de la croissance entre les gouttes. Dans un troisième temps, nous proposons un schéma d’inférence pour résoudre le problème inverse, qui est de retrouver, à partir des courbes de croissance, la variabilité des temps de division des bactéries individuelles. Le modèle précédent ne peut être utilisé à cause des sources externes de variabilité, nous proposons donc un schéma d’inférence basé sur le suivi dans le temps de chacune des trajectoires des gouttes. Grâce à des simulations reproduisant les conditions expérimentales, nous prouvons que l’inférence est possible. Elle ne peut être appliquée à nos expériences en raison de la précision insuffisante de notre mesure de fluorescence. Enfin, la même puce micro-fluidique est utilisée pour quantifier l’action d’antibiotiques sur des bactéries, notamment la réponse SOS qui est induite lorsque l’ADN de la bactérie est endommagé. La technologie d’encapsulation en goutte est utilisée pour mesurer l’hétérogénéité de réponse des bactéries et la relier à leur capacité à survivre au stress dû à l’antibiotique, et à reformer une colonie. / This thesis presents some results about the variability of the growth of bacteria in microfluidics droplets. In the first chapter, the microfluidic chip used throughout the PhD is presented. It allows to encapsulate bacteria in an array of 1.500 nano-liter sized droplets, and to follow their growth in each droplet in parallel through fluorescence microscopy. The link between the measured fluorescence and the number of bacteria in a droplet is discussed, and other technical questions are addressed, such as the variability in droplet size and the cell-to-cell fluorescence variability. Next, we develop a stochastic model to account for the observed variability of population size in the droplet during the exponential phase of growth. A well-known stochastic model, the Bellman-Harris model, is adapted to take into account the external sources of randomness due to our experimental system (initial distribution of bacteria per droplet, different division time of the first generations). They are taken into account, along with the effects of the cell-to-cell variability of division times in our model, which is successful to predict the variability observed in the microfluidics experiments. Then we tackle the inverse problem, which is to recover the cell-to-cell variability from the observation of the growth in droplets. We propose an inference scheme based on following each droplet in time. The deviation from pure exponential growth is linked back to the cell-to-cell variability, and this inference scheme is proven to be successful on simulations that mimic the experimental constrains. However, we cannot completely apply it to our experiments because of a lack of accuracy in our fluorescence measurements. Finally, we demonstrate how our chip can represent a gain of space and time to quantify the effect of antibiotics on a bacterial strain compared to classical susceptibility measurement methods. We also show how it can be used to study the variability of the SOS response of bacteria, which is a bacterial stress response induced when the DNA of the cell is damaged, and relate it to the ability to survive an antibiotic treatment.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18979号 / 工博第4021号 / 新制||工||1619(附属図書館) / 31930 / 京都大学大学院工学研究科マイクロエンジニアリング専攻 / (主査)教授 鈴木 基史, 教授 木村 健二, 教授 蓮尾 昌裕 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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Indiana University-Purdue University Indianapolis (IUPUI) / A new method for capturing 3D video from a single imager and lens is introduced in this research. The benefit of this method is that it does not have the calibration and alignment issues associated with binocular 3D video cameras, and allows for a less expensive overall system. The digital imaging technique Depth from Defocus (DfD) has been successfully used in still camera imaging to develop a depth map associated with the image. However, DfD has not been applied in real-time video so far since the focus mechanisms are too slow to produce real-time results. This new research result shows that a Microfluidic lens is capable of the required focal length changes at 2x video frame rate, due to the electrostatic control of the focus. During the processing, two focus settings per output frame are captured using this lens combined with a broadcast video camera prototype. We show that the DfD technique using Bayesian Markov Random Field optimization can produce a valid depth map.

This project encompasses the design of a pretreatment protocol for blood serum and adaption of that protocol to a microfluidic environment in order to optimize key sample characteristics, namely pH, conductivity, and viscosity, to enable on-chip electrokinetic separations. The two major parts of this project include (1) designing a pretreatment protocol to optimize key parameters of the sample solution within a target range and (2) designing /fabricating a microchip that will effectively combine the sample solution with the appropriate buffers to replicate the same bench-scale protocol on the micro-scale. Biomarker detection in complex samples such as blood necessitates appropriate sample “pretreatment” in order for specific markers to be isolated through subsequent separations. This project, though using conventional mixing techniques and buffer solutions, is one of the first to observe the effects of the combination of micro-mixing and sample pretreatment in order to create an all-in-one “pretreatment chip”. Using previous literature related to capillary electrophoresis, a bench-scale pretreatment protocol was developed to tune these parameters to an optimal range. A PDMS device was fabricated and used to combine raw sample with specific buffer solutions. Off-chip electrodes were used to induce electrokinetic micro-mixing in the mixing chamber, where homogeneous analyte mixing was achieved in less than one second using an 800V DC pulse wave. Ultimately, we wish to incorporate this device with pre-fabricated electrokinetic devices to optimize certain bioseparations.

Interest in microchip capillary electrophoresis (CE) is growing due to the rapid analysis times provided and small sample input requirements. However, higher-concentration samples are typically needed because of the small (~pL) detection volumes in these devices. I have made membrane-based protein preconcentration systems in capillary and microchip designs to increase the detectability of low-concentration biological samples. A photopolymerized ion-permeable membrane interfaced with a microchannel in poly(methyl methacrylate) (PMMA) formed the preconcentrator. When a voltage was applied between the sample reservoir and the ionically conductive membrane in a capillary-based system, R-phycoerythrin was concentrated more than 1,000 fold, as determined by laser-induced fluorescence measurement. An integrated system that combines analyte preconcentration with microchip CE has also been developed using two different fabrication methods: polymerization and solvent bonding. In both approaches, microchannels within the PMMA substrates were interfaced with an ion-permeable hydrogel. When an electrical potential was applied along the channel, greater than 10,000-fold preconcentration was achieved for R-phycoerythrin. Concentrated protein samples were also injected and separated in these integrated microdevices. Membrane-based protein preconcentration devices can significantly increase the concentration range of biological samples that can be analyzed by microchip CE.

2-Bromoisobutyryl bromide was immobilized on poly(methyl methacrylate) (PMMA) substrates activated using an oxygen plasma. Atom-transfer radical polymerization was then performed to graft poly(ethylene glycol) (PEG) on the PMMA surface. PMMA micro capillary electrophoresis (µCE) devices made with the covalently modified surfaces exhibited substantially reduced electroosmotic flow and nonspecific adsorption of proteins. Both column efficiency and migration time reproducibility were one order of magnitude better with derivatized PMMA µCE devices compared to untreated versions. Fast, reproducible, and efficient separations of proteins and peptides were demonstrated using the PEG-grafted PMMA µCE chips. All analyses were completed in less than 60 seconds, and separation efficiencies as high as 53000 plates for a 3.5-cm long separation channel were obtained. A surface reactive acrylic polymer, poly(glycidyl methacrylate-co-methyl methacrylate) (PGMAMMA), was synthesized and evaluated for suitability as a substrate for fabrication of microfluidic devices for chemical analysis. This polymer has good thermal and optical properties, and is mechanically robust. A key advantage of this polymeric material is that the surface can be easily modified to control inertness and electroosmotic flow using a variety of chemical procedures. In this work, the procedures for aminolysis and photografting of linear polyacrylamide on microchannel surfaces in PGMAMMA substrates were developed, and the performance of the resultant µCE devices was demonstrated for the separation of amino acids, peptides, and proteins. Separation efficiencies as high as 46000 plates for a 3.5-cm long separation channel were obtained. Finally, a novel approach was developed to integrate a buffer ion permeable membrane in a PGMAMMA micro electric field gradient focusing (µEFGF) device. Using the µEFGF device, green fluorescent protein (GFP) was concentrated 4000-fold. Separation of GFP and R-phycoerythrin (R-PE), and selective elution of GFP from a protein mixture containing GFP, FITC-labeled casein, and FITC-labeled hemoglobin were also demonstrated. It was found that the volume and concentration of buffer and presence of carboxylic acid impurities in the membrane, which control the conductivity and ion transport properties of the membrane, strongly affected the behavior of the µEFGF device.

In this dissertation, microfluidic systems that integrate antibody-based sample preparation methods with electrophoretic separation are developed to analyze multiple biomarkers in a point-of-care setting. To form an affinity column, both monolith materials and wall-coated channels were explored. I successfully demonstrated that monolith columns can be prepared in microfluidic devices via photopolymerization. The selectivity of monolith columns was improved by immobilizing antibodies on the surface. These affinity columns can selectively enrich target analytes and reduce the signal of contaminant proteins up to 25,000 fold after immunoaffinity extraction. These results clearly demonstrate that microchip affinity monoliths can selectively concentrate and purify target analytes through specific antibody-antigen interactions. These monolith columns operated well for simple systems such as buffered solution, but suffered from clogging with real biological samples such as human serum. Therefore, I developed new affinity columns using a wall coating protocol. To form the affinity columns, a thin film of a reactive polymer was UV polymerized in a microchannel. Antibodies were attached by reaction between the polymer epoxy groups and antibody amine groups. All steps, including loading, washing, and elution for affinity extraction, as well as capillary electrophoresis analysis, were achieved simply via applying voltages to reservoirs on the microdevice. By adding reservoirs containing alpha-fetoprotein (AFP) standard into the same device, a quantitative method, either standard addition or calibration curve, can also be performed on-chip. These polymer microdevices have been applied in determining AFP levels in spiked serum samples, and the results are comparable with the values measured using a commercial enzyme linked immunosorbent assay kit. These microchips have also been adapted for detection of multiple biomarkers by immobilizing different antibodies on the affinity column. Four kinds of antibodies were attached to microchip columns, and the amounts of immobilized antibodies were characterized. The fluorescence signals of all four protein antigens were in the same range after rinsing, indicating that the derivatization reaction had little bias toward any of the four antibodies. With spiked human blood serum samples, four proteins in the ng/mL range were simultaneously quantified using both calibration curves and standard addition. In general, the calibration curve and standard addition results were close to the known spiked concentrations. These results indicate that my integrated microdevices can selectively retain and analyze targeted compounds in clinical samples. Moreover, my platform is generalizable and applicable for the simultaneous quantification of multiple biomarkers in complex matrices.