This thesis focuses on the investigation and development of an integrated optical biosensor based on enhanced Raman techniques that will provide label-free detection of biomolecules. This is achieved by using hollow core photonic crystal fibers (HC-PCF), nanoparticles, or both. HC-PCF is a unique type of optical fiber, with continuous ‘channels’ of air (typically) running the entire length. The channels serve to confine electromagnetic waves in the core of the fiber, and tailor its transmission properties. Using HC-PCF as a biosensor requires development of a robust technique to fill hollow-core photonic crystal fibers. Though several groups have reported selective filling of HC-PCF’s core, the processes are cumbersome and limit the choice of liquid to avoid multimode behavior. In my Master’s thesis, I presented a simple technique to non-selectively fill all the HC-PCF channels with samples. The non-selective filling preserves the photonic bandgap property of the fiber, and yields an extremely strong interaction of light and the sample that produces considerable enhancement of the Raman signal from the analyte. Up to now, non-selective filling was accomplished through capillary action and it delivered a Raman signal enhancement of approximately 30-fold, which is not sensitive enough to detect biomolecules at the clinical level. Moreover, there were issues of reliability and reproducibility, due to evaporation, filling and coupling light into the fiber. The objective of this PhD research was to overcome these problems by developing a robust optical fiber platform based on Raman spectroscopy that can be used in a clinical setting. I initially focused on heparin, an important blood anti-coagulant that requires precise monitoring and control in patients undergoing cardiac surgery or dialysis. Since the Raman spectra of heparin-serum mixtures exhibits Raman peaks of heparin with poor signal-to-noise ratios, I concentrated on enhancing the heparin Raman signal and filtering out the spectral background of the serum to improve detection sensitivity. Reaching maximum enhancement of the Raman signal required a strong interaction of light and analyte, which can be achieved by using hollow core photonic crystal fiber as I had used in my Master’s research. Using a small piece of HC-PCF I was able to reach an enhancement in the heparin Raman signal of greater than 90-fold. With this degree of enhancement, I was able to successfully detect and monitor heparin in serum at clinical levels, something that had never been accomplished previously. After developing HC-PCF as a Raman signal enhancer, I focused on making the HC-PCF sensor robust, reliable and reusable. This was achieved by integrating the HC-PCF with a differential pressure system that allowed effective filling, draining and refilling of the samples in an HC-PCF, under identical optical conditions. To demonstrate the device’s detection capabilities, various concentrations of aqueous ethanol and isopropanol, followed by different concentrations of heparin and adenosine in serum, were successfully monitored. To further improve the sensitivity of the HC-PCF based Raman sensor, I incorporated surface enhanced Raman scattering (SERS), by introducing nanoparticles into the HC-PCF fibers. The research focused on determining the optimal volume and size of silver nanoparticles to achieve maximum enhancement of the Raman signal in the HC-PCF. The HC-PCF enhanced the Raman signal of Rhodamine 6G (R6G) approximately 90-fold. In addition, the optimal size and volume of AgNP enhanced the Raman signal of R6G approximately 40-fold, leading to a total enhancement of approximately 4,000 in HC-PCF. This was then used to demonstrate the application of a SERS based HC-PCF sensing platform in monitoring adenosine (a clinically important molecule), as well as malignant cells such as leukemia. Finally, I used hollow core crystal fibers to significantly enhance the efficiency of two-photon photochemistry. Although two-photon photochemical reactions are difficult to achieve with a small volume, I accomplished it by using a novel platform of HC-PCF to efficiently execute the two-photon induced photodecarbonylation reaction of cyclopropenone 1, and its conversion to the corresponding acetylene. The simple optical design configuration involved coupling an 800-nm tsunami laser to a short piece of HC-PCF filled with the sample. This allowed me to increase the efficiency of two-photon induced photochemistry by 80-fold, compared to a conventional spectrophotometer cuvette. Thus, this work leads to the use of HC-PCFs to more effectively study two-photon induced photochemistry processes, which was limited due to the difficulty of detecting photochemical events with a small excitation volume.

The increasing market demand for fresh produce promotes a keen interest in developing a rapid, sensitive and reliable method for monitoring plant health and determining the shelf-life of postharvest produce. The objective of this study is to explore the capability of Surface-enhanced Raman spectroscopy (SERS) in these applications. SERS integrates Raman spectroscopy which measures molecular vibrations and nanotechnology which enhances the weak Raman signals. Herein, we developed two SERS methods based on a surface detection approach using nanoparticles solution and a headspace detection approach using gold nanoparticles (AuNPs) fibers, to detect biochemical changes during postharvest storage of arugula leaves. Compared with surface detection, the headspace detection revealed significant spectral changes during the storage, particularly in the shifts around 500, 950 and 1030 cm-1. These changes analyzed using principal component analysis (PCA) to establish a prediction model for shelf-life determination. Through analyzing reference standard compounds, we identified the dimethyl disulfide (DMDS), 1-propanethiol and methanethiol (MT) were most likely to account for the signature spectra of headspace arugula at the late storage period due to the activities of spoilage bacteria. The headspace detection method was also applied to monitor the stress responses of living basil to abiotic stresses (pesticide/salinity). However, the volatile analysis of the basil plants response to abiotic stresses (pesticide/salinity) showed indistinctive results. In conclusion, the headspace detection based on SERS provides a new strategy for quality monitoring of fresh produce in the food industry.

In the first part of the Thesis, a new type of active system for SERS and SERRS of hydrophobic molecules, namely a 3-dimensional (3D) nanosponge aggregate with incorporated hydrophobic molecules has been developed, and tested by fullerene C60 and hydrophobic free- base tetraphenylporfine (H2TPP). The SERS and SERRS (surface enhanced /resonance/ Raman scattering) limits of detection (LODs) of C60 at four excitation wavelengths spanning the visible spectral region were found to be by one order of magnitude lower than in the reference system, which mimics the previously reported ways of utilization of Ag nanosponges as substrates for SERS and SERRS. The superiority of the newly developed sample is attributed to the efficient localization of the hydrophobic molecules into hot spots in 2D fractal aggregates of Ag nanoparticles (NPs). Diprotonation of H2TPP during the procedure using HCl as the preaggregation agent has been eliminated by employment of NaCl. On the other hand, investigation of the mechanism of H2TPP protonation during the former preparation procedure opened a possibility to employ Ag nanosponge aggregate as nanoreactor. In the second part of the Thesis, 2D assemblies of AgNPs were found to be better substrates for SERS of single layer graphene (SLG) than the 3D ones. In particular, the 2D...

In der vorliegenden Dissertation werden verschiedene plasmonisch aktive Kern/Schale- Nanopartikel synthetisiert, experimentell und theoretisch charakterisiert und in analytischen Anwendungen der oberflächenverstärkten Raman-Spektroskopie (engl. surface-enhanced Raman scattering, SERS) eingesetzt. Es werden die optischen Eigenschaften von Gold/Silber-Nanoschalen mit durchstimmbaren Plasmonbanden behandelt. Motivation dafür ist die Frage nach optimalen SERS-Markern für die rote Laseranregung (λ = 632.8 nm). In SERS-Anwendungen gibt es die Möglichkeit mehrere Marker-Moleküle auf die Oberfläche der Nanopartikel aufzubringen, um so eine erhöhte Multiplexing-Kapazität zu generieren. Diese Option der gemischten Monolagen wird in der vorliegenden Arbeit untersucht. Es werden SERS-Marker-Konzepte für die rote Laseranregung basierend auf einzelnen Nanopartikeln gezeigt. Außerdem wird dargestellt, inwieweit sich durch die Anordnung von Nanopartikeln in allen drei Raumdimensionen neue SERS-Marker- Konzepte mit sehr guten plasmonischen Eigenschaften realisieren lassen. In den oben beschriebenen Kapiteln übernehmen Nanopartikel die Rolle des SERS-Substrats für den selektiven Nachweis eines bestimmten Zielmoleküls (z.B. Antigens). Neben diesen Anwendungen können Nanopartikel jedoch auch noch als SERS-Substrat für die markierungsfreie Detektion von Analytmolekülen eingesetzt werden. In dieser Dissertation wird die Herstellung, Charakterisierung und der Einsatz eines integrierten SERS-Substrats für die kombinierte Festphasensynthese und Analytik mittels plamonisch aktiver Gold/Glas-Kern/Schale-Nanopartikel auf Harz-Mikrokugeln behandelt.

<p>This thesis highlights the use and significance of surface enhanced Raman spectroscopy (SERS) for forensic applications. Two unique SERS substrates are developed for successful (1) forensic toxicological drug detection in human patient plasma and (2) trace explosive detection.  </p>

No description available.

Metallic nanostructures supporting surface plasmon modes can concentrate optical fields, and enhance luminescence processes from the metal surface at plasmonic hotspots. Such nanoplasmonic metal luminescence contributes to the spectral background in surface-enhanced Raman spectroscopy (SERS) measurements and is helpful in bioimaging, nano-thermometry, and chemical reaction monitoring applications. Despite increasing interest in nanoplasmonic metal luminescence, little attention has been paid to investigating its dependence on voltage modulation. Also, the hyphenated electrochemical surface-enhanced Raman spectroscopy (EC-SERS) technique typically ignores voltage-dependent spectral background information associated with nanoplasmonic metal luminescence due to limited mechanistic understanding and poor measurement reproducibility. In this thesis, we combine the experimental observations and theoretical study on dynamic Faradaic & non-Faradaic modulated nanoplasmonic metallic luminescence and molecular vibrational Raman from hotspots at the electrode-electrolyte interfaces using multiple novel nano-optoelectrodes. Our work represents a critical step toward the general application of nanoplasmonic metal luminescence signals in optical voltage biosensing, hybrid optical-electrical signal transduction, and interfacial electrochemical monitoring. / Master of Science / Understanding the non-Faradaic and Faradaic process pathway is crucial for unraveling reaction mechanisms, developing efficient catalysts, designing bionsensing methodology, energy conversion and cellular stimulator (1-7). Advances in spectroscopic techniques( 8, 9) and computational models (3, 10) have facilitated the investigation of the non-Faradic and Faradaic processes. Unlike bulk reactions, interfacial electrochemical reactions occur in nanometer-thin layers (3, 11), necessitating highly sensitive detection methods. A significant challenge is background interference from bulk electrolytes and electrodes, often obscuring weak signals from the interfacial region – traditional spectroelectrochemistry struggles to match the high temporal resolution requirement due to noise (12, 13). Surface plasmons have become a promising solution for enhancing the sensitivity of spectroelectrochemical techniques (14, 15). Surface plasmons are collective oscillations of electrons at the metal-dielectric interface, which can focus and intensify optical fields at the nanoscale (16), boosting diverse nonlinear emission signals, including fluorescence, Raman scattering, and harmonic generation (17-23). By utilizing surface plasmons, spectroelectrochemistry techniques have shown promise in detecting interfacial activities with high sensitivity. In this thesis, we introduce a pioneering dual-channel in situ EC-SERS methodology, which harnesses the synergy between plasmon-enhanced vibrational Raman scattering (PE-VRS) and plasmon-enhanced electronic Raman scattering (PE-ERS) interfacial signals to monitor and analyze the Faradaic and non-Faradaic process at the electrode-electrolyte interfaces.

Many environmental compartments are acknowledged transmission routes for infectious diseases, antibiotic resistance, and anthropogenic pollution. The need for environmental sensing has consistently been stressed as a means to minimize public health threats caused by such contaminants. Many analytical detection techniques have been developed and applied for environmental sensing. However, these techniques are often reliant upon centralized facilities and require intensive resources. For these reasons their use can be challenging under resource-constrained conditions characterized by poor water, sanitation, and hygiene (WASH) services. In this dissertation, we developed biotechnology- and/or nanotechnology-advanced analytical tools for environmental sensing that have potential for future application in regions with poor WASH services. First, loop-mediated isothermal amplification (LAMP) and nanopore sequencing were applied to develop assays for the detection of SARS-CoV-2, the causative agent of COVID-19, in wastewater samples. Second, surface-enhanced Raman spectroscopy (SERS) was applied for environmental detection of a range of analytes. Gold nanoparticle (AuNP)-based SERS substrates were fabricated by droplet evaporation-induced aggregation on a hydrophobic substrate. These SERS substrates were then applied for the detection of antibiotic resistance genes (ARGs) and other environmental contaminants (e.g., dye or hydrophobic organic contaminants). In a separate study, Au nanostructured SERS substrates were fabricated and applied for pH sensing in a range of environmental media. Finally, the environmental impact of an AuNP-based colorimetric detection assay was assessed via life cycle assessment. / Doctor of Philosophy / Environmental sensing is an important means to intervene against public health threats of infectious diseases and environmental contaminants. However, currently available analytical tools for environmental samples often require intensive resources that are not available in low- and middle-income countries. In this dissertation, we developed biotechnology and/or nanotechnology advanced analytical tools for environmental sensing that have potential future application applied under resource-constrained conditions. First, we applied loop-mediated isothermal amplification (LAMP) and nanopore sequencing to develop detection assays for SARS-CoV-2, the causative agent of COVID-19, in wastewater samples. Second, we applied surface-enhanced Raman spectroscopy (SERS) to develop assays for environmental analytes. We fabricated SERS substrates by evaporation-induced aggregation of gold nanoparticles (AuNPs) on a hydrophobic substrate and applied these for the detection of antibiotic resistance genes (ARGs) and other environmental contaminants. In addition, Au nanostructured SERS substrates were fabricated and applied for pH sensing in a range of environmental media. Finally, we used life cycle assessment to quantitatively evaluate the environmental impacts of an AuNP-based sensing applications.

Non-invasive and continuous spatiotemporal pathogen monitoring at biological interfaces (e.g., human tissue) holds promise for transformative applications in personalized healthcare (e.g., wound infection monitoring) and environmental surveillance (e.g., airborne virus surveillance). Despite notable progress, current receptor-based biosensors encounter inherent limitations, including inadequate long-term performance, restricted spatial resolutions and length scales, and challenges in obtaining multianalyte information. Surface-enhanced Raman spectroscopy (SERS) has emerged as a robust analytical method, merging the molecular specificity of Raman spectroscopy's vibrational fingerprinting with the enhanced detection sensitivity from strong light-matter interaction in plasmonic nanostructures. As a receptor-free and noninvasive detection tool capable of capturing multianalyte chemical information, SERS holds the potential to actualize bio-interfaced spatiotemporal pathogen monitoring. Nonetheless, several challenges must be addressed before practical adoption, including the development of plasmonic bio-interfaces, sensitive capture of multianalyte information from pathogens, regeneration of nanogap hotspots for long-term sensing, and extraction of meaningful information from spatiotemporal SERS datasets. This dissertation tackles these fundamental challenges. Plasmonic bio-interfaces were created using innovative nanoimprint lithography-based scalable nanofabrication methods for reliable bio-interfaced spatiotemporal measurements. These plasmonic bio-interfaces feature sensitive, dense, and uniformly distributed plasmonic transducers (e.g., plasmonic nano dome arrays, optically-coupled plasmonic nanodome and nanohole arrays, self-assembled nanoparticle micro patches) on ultra-flexible and porous platforms (e.g., biomimetic polymeric meshes, textiles). Using these plasmonic bio-interfaces, advancements were made in SERS signal transduction, machine-learning-enabled data analysis, and sensor regeneration. Large-area multianalyte spatiotemporal monitoring of bacterial biofilm components and pH was demonstrated in in-vitro biofilm models, crucial for wound biofilm diagnostics. Additionally, novel approaches for sensitive virus detection were introduced, including monitoring spectral changes during viral infection in living biofilms and direct detection of decomposed viral components. Spatiotemporal SERS datasets were analyzed using unsupervised machine-learning methods to extract biologically relevant spatiotemporal information and supervised machine-learning tools to classify and predict biological outcomes. Finally, a sensor regeneration method based on plasmon-induced nanocavitation was developed to enable long-term continuous detection in protein-rich backgrounds. Through continuous implementation of spatiotemporal SERS signal transduction, machine-learning-enabled data analysis, and sensor regeneration in a closed loop, our solution has the potential to enable spatiotemporal pathogen monitoring at the bio-interface. / Doctor of Philosophy / Continuous monitoring of pathogens within our bodies and surrounding environments is indispensable for various applications in personalized healthcare (e.g., monitoring wound infections) and environmental surveillance (e.g., airborne virus tracking). To accomplish this, we require sensors capable of seamlessly interfacing with biological systems, such as human tissue, and consistently providing pathogen-related information (e.g., spatial location and pathogen type) over prolonged periods. Our research relies on Surface-enhanced Raman spectroscopy (SERS) to address this challenge. SERS enables noninvasive sensing by providing unique fingerprints of molecules near the sensor's surface. SERS holds the potential to enable bio-interfaced spatiotemporal pathogen monitoring, but several challenges must be tackled before practical adoption. In this dissertation, we address various fundamental challenges in SERS, including constructing SERS devices that can seamlessly interface with biological systems while maintaining performance, sensitively capturing pathogen-related information, extracting meaningful insights from SERS datasets, and continuously regenerating the sensor surface to ensure long-term performance. We developed SERS devices capable of seamlessly interfacing with biological systems using innovative scalable nanofabrication methods. These devices contain sensitive, dense, and uniformly distributed SERS sensors on flexible and porous platforms, such as polymeric scaffolds and textiles. Leveraging these SERS devices, we made advancements in pathogen sensing, data analysis, and sensor regeneration. We demonstrated large-area spatiotemporal monitoring of biofilm components and pH in lab-grown biofilm models, critical for wound biofilm diagnostics. Additionally, we introduced novel approaches for sensitive virus detection, including monitoring changes in SERS signals during viral infection in living biofilms and directly detecting decomposed viral components. The SERS datasets were analyzed using machine learning models to extract biologically relevant spatial and temporal information, such as the spatial location of pathogen components and the temporal stage of pathogen growth, and to predict biological outcomes. Finally, we developed a sensor regeneration method to enable long-term continuous detection in complex backgrounds, such as blood. By continuously performing spatiotemporal pathogen sensing, data analysis, and sensor regeneration in a closed loop, our solution has the potential to realize bio-interfaced spatiotemporal pathogen monitoring.

Raman spectroscopy, together with multivariate statistical analyses, has proven to be a near real-time analytical technique capable of phenotyping cells, tissues and organs. This dissertation will show exclusively the application of the Raman spectroscopy phenotypic profiling method to; (i) microbial toxicity, (ii) ex-vivo organ perfusion, and (iii) subcellular location targeting. Real-time analytical methods for monitoring living biological systems will enable study of the physiological changes associated with growth, genetic manipulations, and adverse environmental conditions. Most existing analytical methods (NMR exempt), though highly accurate, must be performed off-line and most require destruction of the studied sample. These attributes make these methodologies less desirable to the study of physiological changes of cells, tissues, and organs. In this work, Raman spectroscopy has been identified and shown to be a good candidate for real-time analysis mainly because it can be performed: (i) in near real-time, (ii) non-destructively and with minimal sample preparation, (iii) through a glass barrier (i.e., can be performed in situ), and (iv) with minimal spectral interference from water. Here, Raman spectroscopy was used in combination with multivariate statistics to analyze the differing toxic effects of 4-C chain alcohols on E. coli. Good correlations were established between Raman spectra and off-line analytical techniques used to measure: (i) saturated, unsaturated, and cyclopropane fatty acids; (ii) amino acid composition of total protein; and (iii) cell membrane fluidity. Also, Raman 'fingerprint' analysis was used to discriminate among different phenotypic responses of cells. In addition, this methodology was applied to analyze perfusates of organs maintained by the VasoWave® organ perfusion system. Raman fingerprints can be used to assess organ health, and it is believed this data can be used to inform decisions such as whether or not to transplant an organ. Finally, molecular biology techniques were used to design and produce specific protein targets harboring a silver binding domain fusion, which upon release migrate to specific subcellular locations. By employing the related technique of surface-enhanced Raman scattering (SERS), which produces a highly amplified Raman signal in the presence of metallic nanoparticle substrates (e.g., silver nanoparticles), different regions of the E. coli cell structure were studied. The target regions studied by the technique included: (i) outer cell membrane, (ii) periplasm, and the (iii) cytoplasm. / Ph. D.