This is a `sandwich thesis' comprising three distinct research streams I have pursued during the course of my master's degree. The first two streams have concluded, each resulting in a manuscript that is presented as a separate chapter of this thesis. The third research stream is ongoing, but preliminary results are presented in another chapter of this thesis. The first research stream presented in this thesis concerns the development of a technique to produce droplets with diameters as small as 5 microns with an extremely narrow size distribution in comparison to other methods. Other advantages of this technique, known as he snap-offf method, include its simplicity and ease of tuning droplet size. The results of this research are presented in chapter 3 in the form of a manuscript that is currently in press. The second research stream of this thesis explores the physics that drive droplet snap-off. A model was developed to predict the size of droplets, dependent on fluid properties, system geometry, and fluid flow rate. Experiments examined each of these parameters in turn, providing a cohesive understanding of the mechanism behind droplet snap-off. Multiple unanticipated predictions of the model were also verified experimentally. This research is presented in chapter 4 as a manuscript that will be submitted shortly. The final research stream of this thesis investigates forces in emulsions as they relate to a transition from glassy to crystalline dynamics. Specifically, 2D aggregates of droplets were compressed with micropipettes, providing both imaging of cluster evolution, as well as the force applied during compression. This research stream has demonstrated qualitative differences between droplet clusters that differ in composition so as to behave like crystals, glasses, or intermediate states. More quantitative analysis is required before this research stream is ready to be published. Preliminary results are presented in chapter 5. / Thesis / Master of Science (MSc)

The growing threat of antimicrobial resistance is among the largest concerns in the world today. One method under development to combat this issue is the encapsulation of microbes in microfluidic droplets for single-cell testing. This method may be able to circumvent the need for a traditional positive cell culture which consumes the majority of the testing time using current diagnostic methods. This dissertation presents a method by which to deterministically encapsulate microbes using an artificial intelligence object detection algorithm and a Droplet-On-Demand microfluidic device. To accomplish this, the Droplet-On-Demand microfluidic device was first developed using a unique 3D-printing manufacturing method. An annular Channel-in-Channel droplet generator was developed which produced droplets within the hydrophobic 3D-printed polymeric microfluidic device. Supporting microfluidic unit operations were also developed including pumps, a 3-way flow-thru valve, and a detection window used for visualizing microfluidic particles. Control software was developed using python which controlled pneumatically-actuated membranes within the microfluidic device, the imaging system, and the object detection algorithm. 20-μm and 2-μm test particles were used as non-biological test particles while red blood cells and fluorescent E.coli baceria were used as biological test particles. All test particles were identified and encapsulated and show the flexibility of the system overall and the ability to identify a variety of particles of interest in microfluidic systems. Growth tests were conducted using E.coli bacteria encapsulated within microfluidic droplets with a fluorescent metabolic indicator. The fluorescence of droplets containing actively growing encapsulated bacteria was quantified using a unique first-principles model paired with an image processing protocol to provide relative concentration data to quantify the growth of the E.coli over time. These growth results indicated that bacterial growth in droplets could be detected and quickly quantified in 4 hours and thus provide practical results to clinicians on the susceptibility of bacteria to an antibiotic. This Droplet-On-Demand technology has the capability of providing clinically applicable data from the most basic and fundamental biological source, an individual cell; and that can be done with low concentrations and on any cell that can be visually identified.

The combustion dynamics and stability are dependent on the quality of mixing and vaporization of the liquid fuel in the pre-mixer. The vaporization characteristics of different blends of biofuel droplets injected into the air stream in the pre-mixer are modeled in this current study. The focus of this work is on the blended alternate fuels which are lately being considered for commercial use. Two major alternate fuels analyzed are ethanol and Rapeseed Methyl Esters (RME). Ethanol is being used as a substitute for gasoline, while RME is an alternative for diesel. In the current work, the vaporization characteristics of a single droplet in a simple pre-mixer has been studied for pure ethanol and RME in a hot air jet at a temperature of 800 K. In addition, the behavior of the fuels when they are mixed with conventional fuels like gasoline and diesel is also studied. Temperature gradients and vaporization efficiency for different blends of bio-conventional fuel mixture are compared with one another. The model was validated using an experiment involving convection heating of acoustically levitated fuel droplets and IR-thermography to visualize and quantify the vaporization characteristics of different biofuel blends downstream of the pre-mixer. Results show that the 20 µm droplets of ethanol-gasoline 50-50 blend is completely evaporated in 1.1 msec, while 400 µm droplets vaporized only 65% in 80 msec. In gasoline-ethanol blends, pure gasoline is more volatile than pure ethanol. In spite of having higher vapor pressure, ethanol vaporizes slowly compared to gasoline, due to the fact that latent heat of vaporization is higher for ethanol. For gasoline-ethanol blended fuels, ethanol component vaporizes faster. This is because in blended fuels gasoline and ethanol attain the same temperature and ethanol vapor pressure is higher than that for gasoline. In the case of RME-diesel blends, initially diesel vaporizes faster up to 550K, and above this temperature, vapor pressure of RME becomes dominant resulting in faster vaporization of RME. Current work also looks into the effect of non-volatile impurities present in biofuels. Depending on source and extraction process, fuels carry impurities which impact vaporization process. In this work these effects on ethanol blended fuel have been studied for different concentration of impurities. The presence of non-volatile impurities reduces the vaporization rate by reducing the mass fraction of the volatile component at the surface. However, impurities also increase the surface temperature of the droplet. Finally, the effects of hot and cold spots in the prevaporizer have been investigated. Due to inefficient design, prevaporizer may have local zones where the temperature of air increases or decreases very sharply. Droplets going through these abnormal temperature zones would vaporize at a different rate than others. Current study looks into these droplets to understand the vaporization pattern.

There have been many changes in production agriculture over the last 20 years. The use of herbicide resistant crops has become common place in production agriculture. However, the release of crops resistant to auxin herbicides has brought more attention to the pesticide application process regardless of the type of pesticide applied. Moreover, controlling off-target movement of pesticides has become an integral part of the day to day farming tasks. The use of deposition aids when applied with water has been documented; however, the effect of deposition aids on pesticide application is not well understood. Based on these findings, selecting a deposition aid not only can be affected by the pesticide used but also the crop in question. Additionally, label restrictions on auxin herbicide application in auxin tolerant crops brings an additional problem to cotton growers. The use of insecticides in conjuction with herbicide applications has been commonplace for many growers across the cotton belt. However, smaller droplets have been utilized to increase coverage of these insecticides. Data presented in these findings suggest that larger droplets can still have good levels of efficacy and in some instances increase yield. The use of auxin tolerant crops allows for usage of addition POST herbicides to cotton; however, the effect of these tank mix applications on ctrop injury is not well understood. In both EnlistTM and Xtend® Flex cotton levels of injury were increased when glufosinate and S-metolachlor were applied in a tank mix. However, yield was not negatively impacted in either study.

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