Addressing reliability challenges in solid-state nanopore sensors for robust point-of-care diagnosticsDong, Ming Nanoporenucleic acid detectionpathogen identificationmolecular diagnosticsElectrical EngineeringPHDRapid and accurate nucleic acid detection is vital for controlling disease outbreaks and monitoring environmental safety. These methods facilitate the early identification of pathogens and genetic markers critical for public health and ecological balance. Nanopore technology, leveraging nanoscale pores in materials like silicon nitride and quartz glass, represents a significant advancement in molecular diagnostics. It provides a unique platform for analyzing nucleic acids and proteins at the single-molecule level, enabling the precise detection and quantification of biological molecules. The development and detailed characterization of these nanopores are crucial for enhancing their application across diverse scientific and clinical fields. This dissertation mainly focuses on exploring the possibility of developing an integrated LAMP readout system using solid-state nanopores for rapid, label-free nucleic acid self-testing. First, we investigated the dynamics of nanopore formation during controlled dielectric breakdown (CBD), with a focus on how redox-induced bubble generation at the electrolyte-membrane interface alters electric field distribution and impacts nanopore formation. This study reveals how these bubbles affect the number and distribution of nanopores, offering new insights into the stochastic nature of nanopore fabrication and suggesting ways to enhance sensor consistency and reliability. Additionally, we studied the effects of laser-assisted dielectric breakdown (LaCBD) on nanopore formation, particularly noting the formation of laser-induced debris and its asymmetric distribution, which affects molecular transport. Our research also underscores the importance of comprehensive baseline assessments for nanopore sensors, recommending the integration of baseline current measurements with traditional noise assessments to improve accuracy. Then, we developed a Rolling Circle Amplification (RCA)-coupled glass nanopore counting method for detecting mild Traumatic Brain Injury (mTBI)-related microRNAs (miRNAs) in saliva. This approach uses large glass nanopores to digitally count specific mTBI-associated miRNAs such as let-7a, miR-30e, and miR-21 with high specificity and sensitivity. Validated for accurate quantification of these potential mTBI biomarkers, our results demonstrate that this method offers a practical, non-invasive solution for mTBI diagnosis at the point-of-care. Taking the rapid and sensitive Loop-Mediated Isothermal Amplification (LAMP) assays, we expand it with nanopore sensing for assay readout for pathogen diagnostics. We first introduced a high-fidelity machine learning-assisted method to identify false positives in LAMP, employing nanopore-based sizing and counting. This technique, designed to improve the specificity and reliability of LAMP assays often affected by contamination and non-specific amplification, integrates machine learning with nanopore sizing to accurately distinguish true from false positives with 91.67% accuracy. This development significantly enhances the accuracy of LAMP assays, reducing false positives crucial for dependable diagnostics and monitoring. Finally, we developed a clog-free nanopore LAMP sensing system enhanced with automated de-clogging mechanisms to improve the reliability and efficiency of molecular diagnostics. This system combines specialized software and hardware, including a vibration motor managed by a custom-developed LabView Virtual Instrument (VI), to quickly and effectively clear clogs that occur during the LAMP amplicon sensing process. This approach not only maintains the integrity of the nanopore sensor but also optimizes data accuracy and throughput, providing a robust solution for reliable nanopore-based diagnostics. Successfully completing this dissertation could greatly enhance the efficiency, accuracy, and accessibility of nanopore-based, amplification-assay coupled molecular diagnostics. This work promises robust solutions that can be broadly applied across healthcare and environmental monitoring, adapting to diverse needs and settings.Madhavan Swaminathan, Program Head/ChairTom Jackson, Major Field MemberPak Kin Wong, Outside Unit & Field MemberWeihua Guan, Chair & Dissertation AdvisorSeyedehaida Ebrahimi, Major Field Memberrestricted_to_institution2024-10-14T18:33:25Zhttps://etda.libraries.psu.edu/catalog/20465mkd5669