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The development of a waterborne pathogen detection method that is rapid, multiplex, sensitive, and specific, would be of great assistance for water treatment facilities and would help protect water consumers from harmful pathogens. Here we have utilized surface enhanced Raman spectroscopy (SERS) in a sensitive multiplex pathogen detection method. Two strategies are proposed herein, one that utilizes SERS antibody labels and one that measures the intrinsic SERS signal of organisms. For the SERS label strategy, gold nanoparticles are conjugated with antibodies specific to Cryptosporidium parvum and Giardia lamblia and with organic dye molecules. The dye molecules, rhodamine B isothiocyanate (RBITC) and malachite green isothiocyanate (MGITC) were surface enhanced by the gold nanoparticles resulting in unique fingerprint SERS spectra. The SERS label method was successful in detecting G. lamblia and C. parvum simultaneously. The method was subsequently coupled with a filtration step to both concentrate and capture cysts on a flat surface for detection. Raman mapping across the filter membrane detected ~95% of the spiked cysts in the optimized system. In the second type of strategy, intrinsic virus SERS signals were detected with silver nanoparticles for enhancement. Principal component analysis performed on the spectra data set resulted in the successful differentiation of MS2 and PhiX174 species and also for the differentiation of viable virus samples and inactivated virus samples. / Ph. D.

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique that combines molecular specificity of vibrational fingerprints offered by Raman spectroscopy with single-molecule detection sensitivity from plasmonic hotspots of noble metal nanostructures. Label-free SERS has attracted tremendous interest in bioanalysis over the last two decades due to minimal sample preparation, non-invasive measurement without water background interference, and multiplexing capability from rich chemical information of narrow Raman bands. Nevertheless, significant challenges should be addressed to become a widely accepted technique in bio-related communities. In this dissertation, limitations from different aspects (performance, reliability, and analysis) are articulated with state-of-the-art, followed by how introduced works resolve them. For high SERS performance, SERS substrates consisting of vertically-stacked multiple metal-insulator-metal layers, named nanolaminate, were designed to simultaneously achieve high sensitivity and excellent uniformity, two previously deemed mutually exclusive properties. Two unique factors of nanolaminate SERS substrates were exploited for the improved reliability of label-free in situ classification using living cancer cells, including background refractive index (RI) insensitivity from 1.30 to 1.60, covering extracellular components, and 3D protruding nanostructures that can generate a tight nano-bio interface (e.g., hotspot-cell coupling). Discrete nanolamination by new nanofabrication additionally provides optical transparency, offering backside-excitation, thereby label-free glucose sensing on a skin-phantom model. Towards reliable quantitative SERS analysis, an electronic Raman scattering (ERS) calibration method was developed. ERS from metal is omnipresent in plasmonic constructs and experiences identical hotspot enhancements. Rigorous experimental results support that ERS can serve as internal standards for spatial and temporal calibration of SERS signals with significant potential for complex samples by overcoming intrinsic limitations of state-of-art Raman tags. ERS calibration was successfully applied to label-free living cell SERS datasets for classifying cancer subtypes and cellular drug responses. Furthermore, dual-recognition label-SERS with digital assay revealed improved accuracy in quantitative dopamine analysis. Artificial neural network-based advanced machine learning method was exploited to improve the interpretability of bioanalytical SERS for multiple living cell responses. Finally, this dissertation provides future perspectives with different aspects to design bio-interfaced SERS devices for clinical translation, followed by guidance for SERS to become a standard analytical method that can compete with or complement existing technologies. / Doctor of Philosophy / In photonics, metals were thought to be not very useful, except mirrors. However, at a length scale smaller than wavelength, it has been realized that metallic structures can provide unique ways of light manipulation. Maxwell's equations show that an interface between dielectric and metal can support surface plasmons, resulting in collective oscillations of electrons and light confinement. Surface-enhanced Raman spectroscopy (SERS) is a sensing technique that combines enhanced local fields arising from plasmon excitation with molecular fingerprint specificity of vibrational Raman spectroscopy. The million-fold enhancement of Raman signals at hotspots has driven an explosion of research, providing tons of publications over the last two decades with a broad spectrum of physical, chemical, and biological applications. Nevertheless, significant challenges should be addressed for SERS to become a widely accepted technique, especially in bio-related communities. In this dissertation, limitations from different aspects (performance, reliability, and analysis) are articulated with state-of-the-art, followed by how innovative strategies addressed them. Each chapter's unique approach consists of a combination of five aspects, including nanoplasmonics, nanofabrication, nano-bio interface, cancer biology, statistical machine learning. First, high-performance SERS substrates were designed to simultaneously achieve high sensitivity and excellent uniformity, two previously deemed mutually exclusive properties, by vertically stacking multiple metal-insulator-metal layers (i.e., nanolaminate). Their 3D protruding nanotopography and refractive-index-insensitive SERS response enabled label-free in situ classification of living cancer cells. Tweaked nanofabrication produced discrete nanolamination with optical transparency, enabling label-free glucose sensing on a skin phantom. Towards reliable quantitative SERS analysis, an electronic Raman scattering (ERS) calibration method was developed that can overcome the intrinsic limitations of Raman tags, and it was successfully applied to label-free living cell SERS datasets for classifying cancer subtypes and cellular drug responses. Furthermore, dual-recognition label-SERS with digital assay revealed improved accuracy in quantitative dopamine analysis. Advanced machine learning (artificial neural network) was exploited to improve the interpretability of SERS bioanalysis for multiple cellular drug responses. Finally, this dissertation provides future perspectives with different aspects, including SERS, biology, and statistics, for SERS to potentially become a standard analytical method that can compete with or complement existing technologies.

Droplets are ubiquitous microscopic systems - ranging in size from several nanometers to ~100 micrometers – that undergo abundant environmental interactions. Researchers have shown that droplets can impact both earth climate and air quality through physical and chemical processes. Droplets released from the human respiratory system, either suspended in air or deposited on surfaces, can carry pathogens (e.g., influenza viruses, the SARS-CoV-2 virus), and are thus important for disease transmission. The need to understand the role of droplets in environmental processes requires appropriate tools for droplet characterization. We used Raman and surface-enhanced Raman spectroscopy (SERS) based imaging as such tools due to their capacity for simultaneous collection of abundant molecular information inside droplets and their potential to collect detailed images of droplet component distributions. We imaged pH and chemical moiety distributions inside droplets over a wide range of: 1) droplet compositions; 2) surrounding environmental conditions (relative humidity, temperature); and 3) droplet morphologies. This dissertation describes measurement of droplet pH in droplets containing mixtures of phosphate buffer (PB), one of the most commonly used biological solvents, and ammonium sulfate (AS), arguably the most abundant chemical species in atmospheric droplets, at room temperature. We observed a pH gradient inside PB droplets while a homogeneous pH distribution was found inside AS droplets, thus showing a significant pH effect due to droplet composition. We attributed the contrasting pH distribution in the two droplet systems to different ionic interactions at the air-water interface. In addition, we obtained AS droplet images at 223K to investigate ice nucleation upon freezing. We observed variable nucleation behavior in AS droplets as a function of concentration, a finding with implications for atmospheric cloud nucleation. We also investigated virus deposition during sessile droplet evaporation using gold nanoparticles. SERS imaging enabled development of correlations between virus viability and droplet deposition pattern and related them in terms of the coffee-ring effect. Suppression of the coffee-ring effect can reduce virus infectivity on surfaces during droplet evaporation. These works collectively exhibit the potential of Raman and SERS imaging for droplet characterization. / Doctor of Philosophy / Droplets are ubiquitous in the environment. Small droplets can form clouds and fogs, and are often micro- to nano-scale in size. Droplets can either grow or shrink in the environment when they absorb or lose water. Similarly, reactions may happen when droplets contain various species. Droplets in human breath exhalate may contain pathogens, such as the SARS-CoV-2 virus that is the cause of the COVID-19 pandemic. If the virus stays viable in droplets, no matter where the droplets are located, the virus will remain infectious and may be transmitted to others through contact. The studies in this dissertation were conducted to determine the distributions of soluble and insoluble components inside droplets and to elucidate how the observed distributions correlate with important droplet properties and environmental processes. We used two methods to observe droplets: Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS). Molecules are constantly vibrating, these vibrations result in characteristic Raman signals that can be monitored. Both Raman and SERS provide such measurements, except that SERS has greater sensitivity due to the signal enhancement provided by gold or silver nanoparticles. In this dissertation, we obtained images of droplets with variable compositions at both room temperature and -50 °C. We also examined virus survival inside droplets during droplet drying. Using the collected images, we related the component distribution inside a droplet to its acidity, and evaluated virus survival in terms of droplet drying patterns. The images demonstrate that Raman and SERS imaging are promising tools for the study of droplets.

Optofluidic sensing utilizes the advantages of both microfluidic and optical science to achieve tunable and reconfigurable high-performance sensing purpose, which has established itself as a new and dynamic research field for exciting developments at the interface of photonics, microfluidics, and the life sciences. With the trend of developing miniaturized electronic devices and integrating multi-functional units on lab-on-a-chip instruments, more and more desires request for novel and powerful approaches to integrating optical elements and fluids on the same chip-scale system in recent years. By taking advantage of the electrowetting phenomenon, the wettability of liquid droplet on micro/nano-structured surfaces and the Leidenfrost effect, this doctoral research focuses on developing high-performance optofluidic sensing systems, including optical beam adaptive steering, whispering gallery mode (WGM) optical sensing, and surface-enhanced Raman spectroscopy (SERS) sensing. A watermill-like beam steering system is developed that can adaptively guide concentrating optical beam to targeted receivers. The system comprises a liquid droplet actuation mechanism based on electrowetting-on-dielectric, a superlattice-structured rotation hub, and an enhanced optical reflecting membrane. The specular reflector can be adaptively tuned within the lateral orientation of 360°, and the steering speed can reach ~353.5°/s. This work demonstrates the feasibility of driving a macro-size solid structure with liquid microdroplets, opening a new avenue for developing reconfigurable components such as optical switches in next-generation sensor network. Furthermore, the WGM sensing system is demonstrated to be stimulated along the meridian plane of a liquid microdroplet, instead of equatorial plane, resting on a properly designed nanostructured chip surface. The unavoidable deformation along the meridian rim of the sessile microdroplet can be controlled and regulated by tailoring the nanopillar structures and their associated hydrophobicity. The nanostructured superhydrophobic chip surface and its impact on the microdroplet morphology are modeled by Surface Evolver (SE), which is subsequently validated by the Cassie-Wenzel theory of wetting. The influence of the microdroplet morphology on the optical characteristics of WGMs is further numerically studied using the Finite-Difference Time-Domain method (FDTD) and it is found that meridian WGMs with intrinsic quality factor Q exceeding 104 can exist. Importantly, such meridian WGMs can be efficiently excited by a waveguiding structure embedded in the planar chip, which could significantly reduce the overall system complexity by eliminating conventional mechanical coupling parts. Our simulation results also demonstrate that this optofluidic resonator can achieve a sensitivity as high as 530 nm/RIU. This on-chip coupling scheme could pave the way for developing lab-on-a-chip resonators for high-resolution sensing of trace analytes in various applications ranging from chemical detections, biological reaction processes to environmental protection. Lastly, this research reports a new type of high-performance SERS substrate with nanolaminated plasmonic nanostructures patterned on a hierarchical micro/nanostructured surface, which demonstrates SERS enhancement factor as high as 1.8 x 107. Different from the current SERS substrates which heavily relies on durability-poor surface structure modifications and various chemical coatings on the platform surfaces which can deteriorate the SERS enhancement factor (EF) as the coating materials may block hot spots, the Leidenfrost effect-inspired evaporation approach is proposed to minimize the analyte deposition area and maximize the analyte concentration on the SERS sensing substrate. By intentionally regulating the temperature of the SERS substrate during evaporation process, the Rhodamine 6G (R6G) molecules inside a droplet with an initial concentration of 10-9 M is deposited within an area of 450 μm2, and can be successfully detected with a practical detection time of 0.1 s and a low excitation power of 1.3 mW. / Doctor of Philosophy / Over the past two decades, optofluidics has emerged and established itself as a new and exciting research field for novel sensing technique development at the intersection of photonics, microfluidics and the life sciences. The strong desire for developing miniaturized lab-on-a-chip devices and instruments has led to novel and powerful approaches to integrating optical elements and fluids on the same chip-scale systems. By taking advantage of the electrowetting phenomenon, the wettability of liquid droplet on micro/nano-structured surfaces and the Leidenfrost effect, this doctoral program focuses on developing high-performance optofluidic sensing systems, including optical beam adaptive steering, whispering gallery mode (WGM) optical sensing, and surface-enhanced Raman spectroscopy (SERS) sensing. During this doctoral program, a rotary electrowetting-on-dielectric (EWOD) beam steering system was first fabricated and developed with a wide lateral steering range of 360° and a fast steering speed of 353.5°/s, which can be applied in telecommunication systems or lidar systems. Next, the meridian WGM optical sensing system was optically simulated using finite difference time domain (FDTD) method and was numerically validated to achieve a high quality-factor Q exceeding 104 and a high refractive index sensitivity of 530 nm/RIU, which can be applied to the broad areas of liquid identification or single molecule detection. Lastly, a SERS sensing platform based on a hierarchical micro/nano-structured surface was accomplished to exhibit a decent SERS enhancement factor (EF) of 1.81 x 107. The contact angle of water droplet on the SERS substrate is 134° with contact angle hysteresis of ~32°. Therefore, by carefully controlling the SERS surface temperature, we employed Leidenfrost evaporation to concentrate the analytes within an extremely small region, enabling the high-resolution detection of analytes with an ultra-low concentration of ~10-9 M.

Gold nanoclusters possess both theoretical and practical importance in the development of ultrasensitive biosensors based on surface-enhanced Raman spectroscopy (SERS). Manipulation of gold nanoclusters in a predictable and reproducible manner for the application of refined biochemical analysis still remains challenging. In this study, high-purity gold nanoclusters are isolated via a simple method based on density gradient centrifugation. Three distinct bands including monomers, small aggregates (2-4 nanospheres), and large aggregates (>5 nanospheres) can be separated via density gradient centrifugation. The isolated gold nanoclusters greatly enhance the Raman intensity of the trapped dye molecules such that single nanocluster detection is feasible. To develop a gold nanoparticle-based biosensor for influenza virus, effort was also made to modify recognition moieties such as aptamers to gold nanoparticles via distinct approaches. The increase of hydraulic diameter and the shift of optical absorbance spectrum indicate the success of surface modification to gold nanoparticles. / Master of Science

Pathogenic microbial contamination of the environment poses a significant threat to human health. Accordingly, microbial surveillance is needed to ensure safe drinking water and air quality. Current analytical methods for microbes are generally either culture-based, gene amplification-based, or sequencing-based. However, these approaches require centralized facilities, well-trained personnel, and specialized instruments that result in high costs and long turnaround times. Surface-enhanced Raman spectroscopy (SERS)-based techniques have been proposed to overcome these limitations. In this dissertation, we discuss work conducted to develop novel SERS-based methods to enable both sensitive microbial quantification and analysis of the interactions of pathogens, their hosts, and the surrounding environment. We first developed a labeled SERS-based lateral flow test for virus quantification. Optimization of the lateral flow design and digital signal analysis enabled high sensitivity towards SARS-CoV-2. To elicit a comprehensive understanding of pathogen infection, label-free living-cell SERS sensors were engineered by incubating host cells with nanoparticles. SERS spectral changes in host cellular components and metabolites during infection were used for viral quantification and offered inherent insights into the temporal and spatial molecular-level mechanisms of infection. These biosensors were validated using bacteriophage Phi6 and then developed for infectious H1N1 influenza. To understand microbial survival in the environment, living-cell SERS methods were applied under various conditions. Results showed cell inactivation and antibiotic treatment induced significant cellular and metabolic responses in the living whole-cell sensors, implying their potential applicability to various environmental conditions. Our research achieves rapid and on-site pathogen quantification and infection mechanism identification. / Doctor of Philosophy / Pathogenic microbes, such as the SARS-CoV-2 virus, can spread through air and water and are potentially harmful to human health. Monitoring the concentrations of these microbes in the environment is crucial to track their presence and provide an early warning of their spread. Unfortunately, current microbial detection methods are often expensive and take a long time since they typically require professional facilities and expert elicitation. Our research relies on a technique called surface-enhanced Raman spectroscopy (SERS) to address these challenges. SERS enables identification and quantification of microbes by analyzing specific features (i.e., peak position, peak intensity) in the spectra. We first applied this technique by modifying a commercial SARS-CoV-2 antigen test kit with a label molecule that provides SERS signals. We achieve accurate and sensitive quantification, even in the presence of high levels of environmental interference. To better understand how these harmful microbes interact with our bodies, we developed sensors that can measure SERS signal changes in host cells before and after infection. These sensors were tested using the bacteriophage virus Phi6 that infects bacteria and infectious H1N1 influenza virus. Furthermore, we applied these sensors to study how bacteria respond to different environmental conditions, providing valuable insights into their survival and behavior under various conditions. In summary, our research introduces methods that are more accessible to identify and quantify harmful microbes that can be potentially used by the general public. The methods provide us with molecular level understanding of pathogen interactions with humans and the environment.