Raman spectroscopy is an extremely versatile technique with molecular sensitivity and fingerprint specificity. However, the translation of this tool into a deployable technology has been stymied by irreproducibility in sample preparation and the lack of complex data analysis tools. In this dissertation, a droplet microfluidic platform was prototyped to address both sample-to-sample variation and to introduce a level of quantitation to surface enhanced Raman spectroscopy (SERS). Shifting the SERS workflow from a cell-to-cell mapping routine to the mapping of tens to hundreds of cells demanded the development of an automated processing tool to perform basic SERS analyses such as baseline correction, peak feature selection, and SERS map generation. The analysis tool was subsequently expanded for use with a multitude of diverse SERS applications. Specifically, a two-dimensional SERS assay for the detection of sialic acid residues on the cell membrane was translated into a live cell assay by utilizing a droplet microfluidic device. Combining single-cell encapsulation with a chamber array to hold and immobilize droplets allowed for the interrogation of hundreds of droplets. Our novel application of computer vision algorithms to SERS maps revealed that sialic sugars on cancer cell membranes are found in small clusters, or islands, and that these islands typically occupy less than 30% of the cell surface area. Employing an opportunistic mindset for the application of the data processing platform, a number of smaller projects were pursued. Biodegradable aliphatic-aromatic copolyesters with varying aromatic content were characterized using Raman spectroscopy and principal component analysis (PCA). The six different samples could successfully be distinguished from one another and the tool was able to identify spectral feature changes resulting from an increasing number of aryl esters. Uniquely, PCA was performed on the 3,125 spectra collected from each sample to investigate point-to-point heterogeneities. A third set of projects evaluated the ability of the data processing tool to calculate spectral ratios in an automated fashion and were exploited for use with nano-pH probes and Rayleigh hot-spot normalization. / Ph. D. / How can we understand the dynamic behavior of the cell membrane? Do certain polymeric structures in biodegradable plastic favor bacterial growth and subsequent degradation? To answer these and other intriguing scientific questions, techniques and technologies must be borrowed from a diverse array of fields and combined with fundamental understanding to create innovative solutions. In this dissertation, a two-dimensional surface enhanced Raman spectroscopy (SERS) assay was translated into a live cell assay by utilizing a droplet microfluidic device. Combining single-cell encapsulation with a chamber array to hold and immobilize droplets allowed for the interrogation of hundreds of droplets. Shifting the SERS workflow from a manual cell-to-cell mapping routine to the mapping of tens to hundreds of cells demanded the development of an automated processing tool to perform basic SERS analyses such as baseline correction, peak feature selection, and SERS map generation. Our novel application of computer vision algorithms to SERS maps was able to reveal that sialic sugars on cancer cell membranes are found in small clusters, or islands, and that these islands typically occupy less than 30% of the cell surface area. With an opportunistic mindset, several smaller projects that combine Raman and SERS with extensive data analysis were also pursued. Biodegradable plastics of varying content were studied with Raman spectroscopy. The aliphatic and aromatic polymeric units within these plastics both contain esters, but it is hypothesized that enzymatic hydrolysis occurs at the units asymmetrically. For each of six different samples, five maps were collected, processed using the analysis tool, and then analyzed using a multivariate analysis toolbox. Principal component analysis (PCA) was used to distinguish the polymers and to identify spectral feature changes resulting from an increasing v number of aryl esters. Uniquely, PCA was performed on the 3,125 spectra collected from each sample to investigate point-to-point heterogeneities. A third set of projects evaluated the ability of the data processing tool to calculate spectral ratios in an automated fashion and it was exploited for use with nano-pH probes and Rayleigh hot-spot normalization

Protein phosphorylation plays critical roles in diverse cellular functions, including cell cycle, growth, differentiation, and apoptosis. Deregulated phospho-signaling is often associated with many human diseases and cancers. Despite tremendous efforts to investigate the molecular mechanisms that control the functionality of phospho-signaling pathways, only limited progress has been made on describing the temporal and spatial profiles of cellular protein phosphorylation. The main challenges associated with the study of phospho-signaling processes in cells are related to the short time-scale of certain phosphorylation and dephosphorylation events, the low abundance of the phosphorylated protein forms as compared to their non-phosphorylated counterparts, the complicated and time-consuming sample preparation methods that are accompanying such type of work, and, last, the performance of the detection methods that are suitable for assessing protein phosphorylation. To tackle the challenges associated with the investigation of protein phosphorylation in cells, our objective was to develop a combined mass spectrometry (MS) and microfluidics strategy that enables fast sampling and sensitive detection of key signaling phosphoproteins in complex biological samples. MS is the most widely used analytical tool in the field of proteomics due to its high sensitivity, specificity, and throughput. Microfluidics has been proven as a suitable platform for handling small volumes of scarce samples, being also amenable to automation, integration, and multiplexing. To achieve our objective, this study was conducted in multiple steps: (1) We performed a comprehensive analysis of the factors that affect the performance of mass spectrometry detection (i.e., sensitivity, reproducibility, ability to accurately identify a large number of proteins from complex samples), when used in conjunction with technologies that are conducted in a non-standard fashion, on short time-scales; (2) We developed and evaluated a miniaturized strategy for rapid proteolytic digestion and phosphopeptide enrichment; (3) We demonstrated sensitive detection and quantification of phosphopeptides from complex biological samples using multiple reaction monitoring mass spectrometry (MRM-MS) and microfluidic sample processing; and (4) We developed a microfluidic platform for handling and processing cells that enables the investigation of biological processes that occur on short time-scales, and that can be integrated with the devices developed for the analysis of phospho-proteins. SKBR3 cells were used as a model system for developing and demonstrating the microfluidic chips. The detection and quantification of phospho-proteins involved in MAPK (mitogen activated protein kinase) signaling pathways was achieved at the low nM level. Overall, this study demonstrates proof-of-concept applicability of a microfluidics-MS strategy for monitoring phosphorylation processes in signaling networks. / PHD / Cellular protein phosphorylation plays critical roles in cellular functions, and deregulated phosphorylation is often associated with many human diseases and cancers. Despite tremendous efforts to investigate the molecular mechanisms that control cellular protein phosphorylation events, limited progress has been made on describing the temporal and spatial profiles. The main challenges are related to the short time-scale of certain phosphorylation and dephosphorylation events, the low abundance of the phosphorylated protein forms as compared to their non-phosphorylated counterparts, the complicated and time-consuming sample preparation methods that are accompanying such type of work, and, last, the performance of the detection methods that are suitable for assessing protein phosphorylation. To address the issues involved in the investigation of protein phosphorylation in cells, we developed a novel strategy using mass spectrometry (MS) and microfluidics. This study was conducted in multiple steps: (1) We performed a comprehensive analysis of the factors that affect the performance of mass spectrometry detection; (2) We developed and evaluated a miniaturized strategy for rapid proteolytic digestion and phosphopeptide enrichment; (3) We demonstrated sensitive detection and quantification of phosphopeptides from complex biological samples; and (4) We developed a microfluidic platform for handling and processing cells that enables the investigation of biological processes that occur on short time-scales, and that can be integrated with the devices developed for the analysis of phospho-proteins.

This work is a “sandwich” thesis, containing the work of 4 manuscripts studying droplet motion preceded by background chapters. We start with an introduction that focuses on general concepts in capillarity and fluid dynamics, and how we can build scaling models from first principles. Following the introduction, there is a methodology chapter which provides some notes on the experimental methods used in the manuscripts. In the first manuscript (chapter 3) we look into how a moving a droplet leads to dissipation in an underlying underlying soft substrate. We develop a system of sub-micron elastomeric substrates as well as micropipette based technique to study the forces on micrometric droplets in motion. We find that dissipation scales with the thickness of the underlying film. In chapter 4, we follow up the work on dissipation in soft substrates with a study on the role of uncrosslinked chains in the same substrates, as well as providing more details on substrate fabrication. Next, in chapter 5 we study how geometry can be used to drive motion in droplets. We suspend droplets between two fibers held at an angle and find droplets move towards the apex of the fibers. We develop a simple scaling model for the motion and we are able to modify the fibers to develop a droplet pump that allows for long range microdroplet transport. In the final manuscript (chapter 6) we study how external forces can be used to drive droplet motion. In particular, we study how magnetic fields can drive rearrangements in an aggregate of ferrofluid droplets. We describe phase changes in such a system with a simple scaling model. In these works we develop an understanding of how to drive motion in droplets, with an impact on both fundamental physics and applications in industry. / Thesis / Doctor of Philosophy (PhD) / From cactus needles using their needles to collect water droplets, to microfluidic devices used for health sensing, the motion of droplets is ubiquitous in both nature and industrial applications. In this work, we use experiments and simple models to understand the motion of microscopic droplets across a variety of systems. We first look at how energy is lost in these systems, in particular dissipation in droplets moving across a soft substrate. We then look at how we can use geometry and capillarity to drive motion in droplets by moving droplets with fiber pairs. Finally we use ferrofluids to study the effect of external driving forces on clusters of droplets.

Microfluidics are devices with channels or reservoirs that have dimensions in the range of micrometers. They have an increasing role in biological analysis processes due to their ability to use very small sample volumes. Many microfluidic processes rely heavily on precise temperature measurement and control. Advances in 3D printing have led to high resolution digital light processing stereolithography (DLP-SLA) printers capable of using bio-compatible materials, available at BYU. This custom 3D printer has a resolution of 7.6 µm in the XY plane and 10 µm in the Z axis. Combined with a custom-made resin, we can produce microfluidic features as small as 18 µm x 20 µm. These advances allow for more complex internal geometries with multiple overlapping channels. As the internal geometry becomes more complex, traditional microfluidic temperature measurement tools are limited in their application. This dissertation considers the use of temperature sensitive quantum dots (QDs), nano-scale semiconductor crystals that fluoresce, as an internal temperature measurement tool. This work presents two types of QDs, CdTe and CdSe/ZnS, and their performance as a temperature sensor by relating either photoluminescence peak intensity to temperature or a feed-forward neural network combining multiple features of the fluorescent spectra to temperature. Additionally, 3D printing's ability to create arbitrary 3D structures with an arbitrary 3D orientation, as opposed to traditional microfluidic fabrication methods, enables new three-dimensional heater geometries to be created that provide better internal heat distributions. We present new heater geometries only feasible through 3D printing that can isothermally heat a precisely defined volume. One such design is for a device that can control the temperature of a 5 µL internal chamber to within 0.2°C. This last design is aimed at a new microfluidic device for high resolution DNA melt curve analysis for the detection of single nucleotide polymorphisms. This set of tools we developed will enable the expansion of 3D printed microfluidics beyond the current planar limitations and fluid flow processes into temperature sensitive analyses.

No / This study employs artificial neural networks (ANNs) to create a model to identify relationships between variables affecting drug nanoprecipitation using microfluidic reactors. The input variables examined were saturation levels of prednisolone, solvent and antisolvent flowrates, microreactor inlet angles and internal diameters, while particle size was the single output. ANNs software was used to analyse a set of data obtained by random selection of the variables. The developed model was then assessed using a separate set of validation data and provided good agreement with the observed results. The antisolvent flow rate was found to have the dominant role on determining final particle size.

No / In this work, the possibility of bottom-up creation of a relatively stable aqueous hydrocortisone nanosuspension using microfluidic reactors was examined. The first part of the work involved a study of the parameters of the microfluidic precipitation process that affect the size of generated drug particles. These parameters included flow rates of drug solution and antisolvent, microfluidic channel diameters, microreactors inlet angles and drug concentrations. The experimental results revealed that hydrocortisone nano-sized dispersions in the range of 80¿450nm were obtained and the mean particle size could be changed by modifying the experimental parameters and design of microreactors. The second part of the work studied the possibility of preparing a hydrocortisone nanosuspension using microfluidic reactors. The nano-sized particles generated from a microreactor were rapidly introduced into an aqueous solution of stabilizers stirred at high speed with a propeller mixer. A tangential flow filtration system was then used to concentrate the prepared nanosuspension. The nanosuspension produced was then characterized using photon correlation spectroscopy (PCS), Zeta potential measurement, transmission electron microscopy (TEM), differential scanning calorimetry (DSC) and X-ray analysis. Results showed that a narrowsized nanosuspension composed of amorphous spherical particles with a mean particle size of 500±64 nm, a polydispersity index of 0.21±0.026 and a zeta potential of ¿18±2.84mVwas obtained. Physical stability studies showed that the hydrocortisone nanosuspension remained homogeneous with slight increase in mean particle size and polydispersity index over a 3-month period.

This thesis reports the fabrication of three dimensionally independent on-chip microchannels using a CMOS-compatible single mask deep reactive ion etching (DRIE) process for cooling 3D ICs. Three dimensionally independent microchannels are fabricated by utilizing the RIE lag effect. This allows complex microchannel configurations to be fabricated using a single mask and single silicon etch step. Furthermore, the microchannels are sealed in one step by low temperature oxide deposition. The micro-fin channels heat transfer characteristics are similar to previously published channel designs by being capable of removing 185 W/cm2 before the junction temperatures active elements exceed 85°C. To examine the heat transfer characteristics of this proposed on-chip cooler, different channel geometries were simulated using computational fluid dynamics. The channel designs were simulated using 20°C water at different flow rates to achieve a laminar flow regime with Reynolds numbers ranging from 200 to 500. The steady state simulations were performed using a heat flux of 100 W/cm2. Simulation results were verified using fabricated test chips. A micro-fin geometry showed to have the highest heat transfer capability and lowest simulated substrate temperatures. While operating with a Reynolds number of 400, a Nusselt number per input energy (Nu/Q) of 0.24 W-1 was achieved. The micro-fin geometry is also capable of cooling a substrate with a heat flux of 100W/cm2 to 45ºC with a Reynolds number of 525. These channels also have a lower thermal resistance compared to external heat sinks because there is no heat spreader or thermal interface material layer. / Master of Science

The Volume-of-Fluid method, an Eulerian multiphase flow model that adds a volume fraction transport equation to the CFD governing equations, is widely used for any fluid-fluid interface tracking problem. There are important aspects of multiphase flow that impact aircraft flight, especially flight in extreme environments. These extreme environments can range from wet, icy conditions to sandstorms, and volcanic debris. The problems posed by these harsh environments are only exacerbated by aircraft that tend to travel at higher Mach-numbers. The specific aims of the proposed research include application of the Volume-of-fluid method to the following aspects of aircraft flight: shock-droplet interactions, and molten CMAS infiltrating a thermal barrier coating. Passive scalars are used in novel ways to elucidate droplet breakup physics. From this, a mechanism for how instabilities form on the air-droplet interface is discovered. It is also found that non-cavitating droplet breakup becomes much less dependent on Mach number at higher Mach numbers. A cavitation model designed for underwater explosions is adapted to the shock-droplet problem, and results show that cavitation phenomena is greatly dependent on Mach number, but the adapted model overpredicts cavitation effects. 2D and 3D CFD models are developed for the CMAS infiltration problem, and those are compared to analytical models from literature, and a new proposed analytical model called the feathery pipe network model. Results show that feathery pipe network model is both computationally inexpensive, and allows parameterization of useful properties.

No description available.

Antimicrobial resistance in bacteria is a global health challenge with a projected fallout of 10 million deaths annually and cumulative costs of over 1 trillion dollars by 2050. The currently available tools exploited in the detection of bacteria or their DNA can be expensive, time inefficient, or lack multiplex capabilities among others. The research work highlighted in this dissertation advances techniques employed in the phenotypic or genotypic detection of bacteria and their DNA. In this dissertation, I present polymethyl methacrylate-pressure sensitive adhesive microfluidic platforms developed using a time-efficient, inexpensive fabrication technique. Microfluidic devices were then equipped with functionalized monoliths and utilized for sequence-specific capture and detection of picomolar concentrations of bacterial plasmid DNA harvested from cultured bacteria. I then showed multiplex detection of multiple bacteria gene targets in these devices with an improved monolith column. Finally, I demonstrated a genotypic approach to studying single bacteria growth in water-in-oil droplets with nanomolar concentrations of a fluorescence reporter, and detection via laser-induced fluorescence after convenient room temperature 2-h incubation conditions. The systems and methods described herein show potential to advance tools needed to address the surging problems and effects of drug-resistant bacteria.