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Digital microfluidics (DMF) has recently emerged as a popular technology for a wide range of applications. In DMF, nL-mL droplets containing samples and reagents are controlled(i.e., moved, merged, mixed, and dispensed from reservoirs) by applying a series of electrical potentials to an array of electrodes coated with a hydrophobic insulator. DMF is distinct from microchannel-based fluidics as it allows for precise control over multiple reagent phases (liquid and solid) in heterogeneous systems with no need for complex networks of microvalves. In this thesis, digital microfluidics has been applied to address key challenges in the fields of chemistry, biology and medicine. For applications in chemistry, the first two-plate digital microfluidic platform for synchronized chemical synthesis is reported. The new method, which was applied to synthesizing peptide macrocycles, is fast and amenable to automation, and is convenient for parallel scale fluid handling in a straightforward manner. For applications in biology, I present the first DMF-based method for extraction of proteins (via precipitation) in serum and cell lysate. The performance of the new method was comparable to that of conventional techniques, with the advantages of automation and reduced analysis time. The results suggest great potential for digital microfluidics for proteomic biomarker discovery. Furthermore, I integrated DMF with microchannels for in-line biological sample processing and separations. Finally, for applications in medicine, I developed the first microfluidic method for sample clean-up and extraction of estrogen from one-microliter droplets of breast tissue homogenates, blood, and serum. The new method is fast and automated, and features >1000x reduction in sample use relative to conventional techniques. This method has significant potential for applications in endocrinology and breast cancer risk reduction. In addition, I describe a new microfluidic system incorporating a digital microfluidic platform for on-chip blood spotting and processing, and a microchannel emitter for direct analysis by mass spectrometry. The new method is fast, robust, precise, and is capable of quantifying analytes associated with common congenital disorders such as homocystinuria, phenylketonuria, and tyrosinemia.

Digital microfluidics (DMF) has recently emerged as a popular technology for a wide range of applications. In DMF, nL-mL droplets containing samples and reagents are controlled(i.e., moved, merged, mixed, and dispensed from reservoirs) by applying a series of electrical potentials to an array of electrodes coated with a hydrophobic insulator. DMF is distinct from microchannel-based fluidics as it allows for precise control over multiple reagent phases (liquid and solid) in heterogeneous systems with no need for complex networks of microvalves. In this thesis, digital microfluidics has been applied to address key challenges in the fields of chemistry, biology and medicine. For applications in chemistry, the first two-plate digital microfluidic platform for synchronized chemical synthesis is reported. The new method, which was applied to synthesizing peptide macrocycles, is fast and amenable to automation, and is convenient for parallel scale fluid handling in a straightforward manner. For applications in biology, I present the first DMF-based method for extraction of proteins (via precipitation) in serum and cell lysate. The performance of the new method was comparable to that of conventional techniques, with the advantages of automation and reduced analysis time. The results suggest great potential for digital microfluidics for proteomic biomarker discovery. Furthermore, I integrated DMF with microchannels for in-line biological sample processing and separations. Finally, for applications in medicine, I developed the first microfluidic method for sample clean-up and extraction of estrogen from one-microliter droplets of breast tissue homogenates, blood, and serum. The new method is fast and automated, and features >1000x reduction in sample use relative to conventional techniques. This method has significant potential for applications in endocrinology and breast cancer risk reduction. In addition, I describe a new microfluidic system incorporating a digital microfluidic platform for on-chip blood spotting and processing, and a microchannel emitter for direct analysis by mass spectrometry. The new method is fast, robust, precise, and is capable of quantifying analytes associated with common congenital disorders such as homocystinuria, phenylketonuria, and tyrosinemia.

<p dir="ltr">The necessity for on-farm, point-of-need (PON) nucleic acid amplification tests (NAATs) arises from the prolonged turnaround times and high costs associated with traditional laboratory equipment. This thesis aims to address these challenges by developing devices and a user-interface application designed for the efficient, accurate, and rapid detection of <i>Bacteroidales</i> as an indicator of fecal contamination on fresh produce farms.</p><p dir="ltr">In pursuit of this, I collaborated with lab members to engineer a Field-Applicable Rapid Microbial Loop-mediated isothermal Amplification Platform, FARM-LAMP. This device is portable (164 x 135 x 193 mm), energy-efficient (operating under 20 W), achieves the target 65°C with ± 0.2°C fluctuations, and is compatible with paper-based biosensors for loop-mediated isothermal amplification (LAMP). Subsequently, I led the fabrication of the microfluidic Field-Applicable Sampling Tool, FAST, designed to deliver high-throughput (10 samples per device), equal flow-splitting of fluids to paper-based biosensors, eliminating the need for a laboratory or extensive training. FARM-LAMP achieved 100% concordance with standard lab-based tests when deployed on a commercial lettuce farm and FAST achieved an average accuracy of 89% in equal flow-splitting and 70% in volume hydration.</p><p dir="ltr">A crucial aspect of device development is ensuring that results are easily interpretable by users. To this end, I developed a Python-based image analysis codebase to quantify sample positivity for fecal contamination, ranging from 0% (no contamination) to nearly 100% (definite contamination) and the concentration of field samples. It utilizes calculus-based mathematics, such as first and second derivative analysis, and incorporates image analysis techniques, including hue, saturation, and value (HSV) binning to a sigmoid function, along with contrast limited adaptive histogram equalization (CLAHE). Additionally, I developed a preliminary graphical user interface in Python that defines a prediction model for the concentration of <i>Bacteroidales</i> based on local weather patterns.</p><p dir="ltr">This thesis encompasses hardware development for on-field quantification and the creation of a preliminary user-interface application to assess fecal contamination risk on fresh produce farms. Integrating these devices with a user-interface application allows for rapid interpretation of results on-farm, aiding in the effective development of strategies to ensure safety in fresh produce operations.</p>