Nanoelectronics are electronic components that are often only a few nanometers in size. The field of nanoelectronics encompasses a wide range of products and materials that share the trait of being so small that physical forces can modify their characteristics on a nanoscale. These nanoscale devices are dominated by quantum processes including atomistic disorder and tunneling.In contrast to nanoelectronics, which involves the scaling down of devices to nanoscale levels, molecular electronics is concerned with electronic activities that take place within molecule structures. Detection of molecular conductance plays a vital role in the field of molecular electronics and nanotechnology. The ability to measure the conductive behavior of molecules is necessary to study their surface properties, defects, electronic structures, and for bio-sensing. To determine the conductance of the molecule, it is necessary to deduce the current passing through it. This is achieved by applying a voltage bias across the molecule and the detection instrument. Instruments like Scanning Tunneling Microscope (STM) and chip-based characterization (Probe Station) are used to fetch the amount of current flowing through the molecules. The current through molecules can be very small to measure and needs to be amplified. Linear amplifiers are widely used for amplifying these small currents, but due to their low dynamic range they are being replaced by logarithmic amplifiers. This thesis project aims to customize a logarithmic amplifier design to the interface with these instruments to measure the current flowing through these molecules. This thesis starts with a review of a linear- current amplifier-based technology that is used for measuring small currents and its challenges. It then introduces logarithmic amplifier for overcoming those obstacles. This thesis involves design, fabrication, and characterization of the built logarithmic amplifier. Furthermore, the setup includes a custom designed logarithmic amplifier that can be used with instruments like Scanning Tunneling Microscope (STM) and probe station. The key objective of the research is to accurately calibrate the logarithmic amplifier for measurement of currents over a wide range from picoamperes to milliamperes. Dummy resistors with different resistance values are used to replace the sample of which the conductance is to be measured, for testing and calibrating purposes. Bandwidth of the circuit is tested using these different values of resistors.

Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. With the aging population, an increase in the prevalence of neurodegenerative disorders is expected. Electrophysiological monitoring of neural signals has been the gold standard for clinicians in diagnosing and treating neurological disorders. However, advances in detection and stimulation techniques have paved the way for relevant information not seen by standard procedures to be captured and used in patient treatment. Amongst these advances have been improved analysis of higher frequency activity and the increased concentration of alternative biomarkers, specifically pH change, during states of increased neural activity. The design and fabrication of devices with the ability to reliably interface with the brain on multiple scales and modalities has been a significant challenge. This dissertation introduces a novel, concentric, multi-scale micro-ECoG array for neural applications specifically designed for seizure detection in epileptic patients. This work investigates simultaneous detection and recording of adjacent neural tissue using electrodes of different sizes during neural events. Signal fidelity from electrodes of different sizes during in vivo experimentation are explored and analyzed to highlight the advantages and disadvantages of using varying electrode sizes. Furthermore, the novel multi-scale array was modified to perform multi-analyte detection experiments of pH change and electrophysiological activity on the cortical surface during epileptic events. This device highlights the ability to accurately monitor relevant information from multiple electrode sizes and concurrently monitor multiple biomarkers during clinical periods in one procedure that typically requires multiple surgeries.

This research explores the potential use of microwave energy to detect various substances in water, with a focus on water quality assessment and pathogen detection applications. There are many non-thermal effects of microwaves on microorganisms and their resonant frequencies could be used to identify and possibly destroy harmful pathogens, such as bacteria and viruses, without heating the water. A wide range of materials, including living organisms like Daphnia and Moina, plants, sand, plastic, and salt, were subjected to microwave measurements to assess their influence on the transmission (S21) measurements. The measurements of the living organisms did not display distinctive resonant frequencies and variations in water volume may be the source of the small measurement differences. Conversely, sand and plastic pellets affected the measurements differently, with their arrangement within the test tube emerging as a significant factor. This study also explores the impact of salinity on measurements, revealing a clear pattern that can be modeled as a series RLC resonator. Although unique resonant frequencies for the tested organisms were not identified, the presented system demonstrates the potential for detecting contaminants based on variations in measurements. Future research may extend this work to include a broader array of organisms and enhance measurement precision.

Human papillomavirus (HPV) infection has a large burden on society. It is a causal agent of 99.7% of all cervical cancer cases. The prevalence of HPV infection worldwide is high, but the burden of HPV infections lies on less developed regions. Cervical cancer is not associated with immediate symptoms, screening methods are needed to detect HPV disease presence before lesions progress to cervical cancer. Protein biomarkers are a growing area of diagnostic medicine and facilitate the detection of disease at an early and treatable stage. Technologies for healthcare diagnostics often require laboratory space or expensive instrumentation, which are not feasible for point of care applications. In order for clinical diagnostics to advance in developing countries, low cost, rapid, portable, and easy to use point of care diagnostic tests are needed. The project adapts the Enzyme Linked Immunosorbent Assays (ELISA) and Nucleic Acid-Programmable Protein Array (NAPPA) to a proof of concept assay for use in magnetic bead based microfluidics. The biomarker used for analyte detection was E7, as a strong correlation has been found between presence of E7 antibodies and development of advanced cervical cancer. It is demonstrated that magnetic microfluidic assay design for rapid detection of antibodies is amenable to fluorescence detection in point of care settings. The data demonstrates that the microfluidic assay is rapid, low-cost, specific, and relevant to serology detection. The assay detects antibody responses to analytes with the point of care reader system and is realized in an on chip capacity. With the integration of anti-GST capture antibodies conjugated to the magnetic beads in the microfluidic system, many analytes can be detected without large changes to the existing assay structure, which gives the ability to adapt the system to analytes of interest rapidly.

For two centuries, electrical stimulation has been the conventional method for interfacing with the nervous system. As interfaces with the peripheral nervous system become more refined and higher-resolution, several challenges appear, including immune responses to invasive electrode application, large-to-small axon recruitment order, and electrode size-dependent spatial selectivity. Optogenetics offers a solution that is less invasive, more tissue-selective, and has small-to-large axon recruitment order. By adding genes to express photosensitive proteins optogenetics provides neuroscientists the ability to genetically select cell populations to stimulate with simple illumination. However, optogenetic stimulation of peripheral nerves uses diffuse light to activate the photosensitive neural cell lines. To increase the specificity of stimulus response, research was conducted to test the hypothesis that multiple, focused light emissions placed around the circumference of optogenetic mouse sciatic nerve could be driven to produce differential responses in hindlimb motor movement depending on the pattern of light presented. A Monte Carlo computer simulation was created to model the number of emitters, the light emission size, and the focal power of accompanying micro-lenses to provide targeted stimulation to select regions within the sciatic nerve. The computer simulation results were used to parameterize the design of micro-lenses. By modeling multiple focused beams, only fascicles within a nerve diameter less than 1 mm are expected to be fully accessible to focused optical stimulation; a minimum of 4 light sources is required to generate a photon intensity at a point in a nerve over the initial contact along its surface. To elicit the same effect in larger nerves, focusing lenses would require a numerical aperture > 1. Microlenses which met the simulation requirements were fabricated and deployed on a flexible nerve cuff which was used to stimulate the sciatic nerve in optogenetic mice. Motor neuron responses from this stimulation were compared to global illumination; stimulation using the optical cuff resulted in fine motor movement of the extensor muscles of the digits in the hindlimb. Increasing optical power resulted in a shift to gross motor movement of hindlimb. Finally, varying illumination intensity across the cuff showed changes in the extension of individual digits.

The objective of this thesis project is to identify -- and better meet -- the assistive seating needs of children, ages 5-14, with cerebral palsy. Student needs were assessed through the collection of survey responses from professionals working closely with students who have CP, and interviews conducted by the author with some participants. After performing a detailed needs assessment, specific design changes were suggested for current adaptive seating systems to improve clinical outcomes and user experience for students with cerebral palsy.

This work focuses on qualifying the performance of an optoelectrical measurement system designed to analyze ribonucleic acid (RNA) within a micro sample. The system is capable of measuring light intensity converted to voltage versus time and is a fast, inexpensive, and portable method for rapid detection of biologics such as SARS-CoV-2 virus, or Covid-19 disease. The measurement system consists of a microfluidic chip and a point of care fluorescent reader.The intent of this research is to measure consistency and robustness of the fluorescent reader combined with the microfluidic chip. The consistency and the robustness of the fluorescent reader within the duty cycle of the system power and the measurement system were analyzed with Six Sigma methods. Control charts, analysis of variance (ANOVAs), and variance components calculations were implemented to characterize the reader system. Through the process of this analysis, baseline characteristics were measured and documented providing valuable data for the improved instrument design. The existing microfluidic chip is a prototype that works in combination with the reader based on fluorescent detection. Baseline studies were required to define any issues related to microfluidic autofluorescence. Multiple designs were tested to measure reduction in autofluorescence in the microfluidics. It was found that certain designs performed better than others. One approach for improvement in the microfluidic chip may be achieved by characterizing and source controlling materials, optimizing layers, mask apertures, and mask orientations to determine reliability in the measurable output through the fluorescent reader. Since the reader and the microfluidic are designed to work together, any future studies should explore testing where the two components are considered a coupled system.

Quantifying molecular interactions is critical to the understanding of many biological processes and drug screening. To date, various detection techniques have been developed to determine the binding kinetics. However, because most of the mainstream detection technologies detect signals that scale with the mass of ligands bond to the sensor surface, it is still challenging to quantify the binding kinetics of small molecules. To address this problem, two different detection technologies, charge-sensitive optical detection (CSOD) and critical angle reflection (CAR), are developed for label-free detection of molecular interactions with the ability to detect a wide range of molecules including small molecules. In particular, CSOD technique detects the charge rather than the mass of a molecule with an optical fiber. However, the effective charge of a molecule decreases with the buffer ionic strength. For this reason, the previous CSOD works with diluted buffers, which could affect the measured molecular binding kinetics. Here a technique capable of detecting molecular binding kinetics in normal ionic strength buffers is presented. An H-shaped sample well was developed to overcome this problem. With this new design, the binding kinetics between G-protein-coupled receptors (GPCRs) and their small molecule ligands were measured in normal buffer. To further improve the signal-to-noise ratio of CSOD and move it toward high-throughput detection, CSOD was implemented with a quadrant-cell detector to achieve detection in higher frequency range and decrease low-frequency noise.This improved CSOD technique is capable for direct quantification of binding kinetics of phage-displayed peptides to their target protein using the whole phages. CAR imaging can be performed on surface plasmon resonance (SPR) imaging setups. It was shown that CAR is capable of measuring molecular interactions including proteins, nucleic acids and cell-based detections. In addition, it was shown that CAR can detect small molecule bindings and intracellular signals beyond SPR sensing limit. CAR exhibits several distinct characteristics over SPR, including tunable sensitivity and dynamic range, deeper vertical sensing range, and fluorescence compatibility. CAR is anticipated to have the ability to expand SPR capability in small molecule detection, whole cell-based detection, simultaneous fluorescence imaging, and broader conjugation chemistry.

Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.

Cameras have become commonplace with wide-ranging applications of phone photography, computer vision, and medical imaging. With a growing need to reduce size and costs while maintaining image quality, the need to look past traditional style of cameras is becoming more apparent. Several non-traditional cameras have shown to be promising options for size-constraint applications, and while they may offer several advantages, they also usually are limited by image quality degradation due to optical or a need to reconstruct a captured image. In this thesis, we take a look at three of these non-traditional cameras: a pinhole camera, a diffusion-mask lensless camera, and an under-display camera (UDC).

For each of these cases, I present a feasible image restoration pipeline to correct for their particular limitations. For the pinhole camera, I present an early pipeline to allow for practical pinhole photography by reducing noise levels caused by low-light imaging, enhancing exposure levels, and sharpening the blur caused by the pinhole. For lensless cameras, we explore a neural network architecture that performs joint image reconstruction and point spread function (PSF) estimation to robustly recover images captured with multiple PSFs from different cameras. Using adversarial learning, this approach achieves improved reconstruction results that do not require explicit knowledge of the PSF at test-time and shows an added improvement in the reconstruction model’s ability to generalize to variations in the camera’s PSF. This allows lensless cameras to be utilized in a wider range of applications that require multiple cameras without the need to explicitly train a separate model for each new camera. For UDCs, we utilize a multi-stage approach to correct for low light transmission, blur, and haze. This pipeline uses a PyNET deep neural network architecture to perform a majority of the restoration, while additionally using a traditional optimization approach which is then fused in a learned manner in the second stage to improve high-frequency features. I show results from this novel fusion approach that is on-par with the state of the art.