Chemical and electrochemical methods for depositing platinum microparticles at the membrane-electrode interface of solid polymer fuel cell oxygen reduction electrodes have been developed and studied.

Physicians’ understanding of bio-signals, measured using medical instruments, becomes the foundation of their decisions and diagnoses of patients, as they rely strongly on what the instruments show. Thus, it is critical and very important to ensure that the instruments’ readings exactly reflect what is happening in the patient’s body so that the detected signal is the real one or at least as close to the real in-body signal as possible and carries all of the appropriate information. This is such an important issue that sometimes physicians use invasive measurements in order to obtain the real bio-signal. Generating an in-body signal from what a measurement device shows is called “signal purification” or “reconstruction,” and can be done only when we have adequate information about the interface between the body and the monitoring device. In this research, first, we present a device that we developed for electrocardiogram (ECG) acquisition and transfer to PC. In order to evaluate the performance of the device, we use it to measure ECG and apply conductive textile as our ECG electrode. Then, we evaluate ECG signals captured by different electrodes, specifically traditional gel Ag/AgCl and dry golden plate electrodes, and compare the results. Next, we propose a method to reconstruct the ECG signal from the signal we detected with our device with respect to the interface characteristics and their relation to the detected ECG. The interface in this study is the skin-electrode interface for conductive textiles. In the last stage of this work, we explore the effects of pressure on skin-electrode interface impedance and its parametrical variation.

Physicians’ understanding of bio-signals, measured using medical instruments, becomes the foundation of their decisions and diagnoses of patients, as they rely strongly on what the instruments show. Thus, it is critical and very important to ensure that the instruments’ readings exactly reflect what is happening in the patient’s body so that the detected signal is the real one or at least as close to the real in-body signal as possible and carries all of the appropriate information. This is such an important issue that sometimes physicians use invasive measurements in order to obtain the real bio-signal. Generating an in-body signal from what a measurement device shows is called “signal purification” or “reconstruction,” and can be done only when we have adequate information about the interface between the body and the monitoring device. In this research, first, we present a device that we developed for electrocardiogram (ECG) acquisition and transfer to PC. In order to evaluate the performance of the device, we use it to measure ECG and apply conductive textile as our ECG electrode. Then, we evaluate ECG signals captured by different electrodes, specifically traditional gel Ag/AgCl and dry golden plate electrodes, and compare the results. Next, we propose a method to reconstruct the ECG signal from the signal we detected with our device with respect to the interface characteristics and their relation to the detected ECG. The interface in this study is the skin-electrode interface for conductive textiles. In the last stage of this work, we explore the effects of pressure on skin-electrode interface impedance and its parametrical variation.

X-ray detector windows must be thin enough to transmit sufficient low-energy x-rays, yet strong enough to withstand up to an atmosphere of differential pressure. Traditional low-energy x-ray windows consist of a support layer and pressure membrane spanning that support. Numerical modeling of several x-ray windows was used to show that both low- and high-energy x-ray transmission can be improved by adding a secondary support structure. Finite element analysis of the x-ray window models showed that the stress from a typical applied load does not exceed the ultimate strength or yield strength of the respective materials. The specific x-ray window models developed in this work may serve as a foundation for improving commercial windows, especially those geared toward low-energy transmission. For local mechanical film testing, microcantilevers were cut in suspended many-layer graphene using a focused ion beam. Multipoint force-deflection mapping with an atomic force microscope was used to record the compliance of the cantilevers. These data were used to estimate the elastic modulus of the film by fitting the compliance at multiple locations along the cantilever to a fixed-free Euler-Bernoulli beam model. This method resulted in a lower uncertainty than is possible from analyzing only a single force-deflection. The breaking strength of the film was also found by deflecting cantilevers until fracture. The average modulus and strength of the many-layer graphene films are 300 GPa and 12 GPa, respectively. The multipoint force-deflection method is well suited to analyze films that are heterogeneous in thickness or wrinkled. Bioimpedance can be measured by applying a known current to the tissue through two (current carrying) electrodes and recording the resulting voltage on two different (pickup) electrodes. Bioimpedance has been used to detect heart rate, respiration rate, blood pressure, and blood glucose. A wrist-based wearable bioimpedance device can measure heart rate by detecting the minute impedance changes caused by the modulation of blood volume in the radial artery. Using finite element analysis, I modeled how electrode position affects sensitivity to pulsatile changes. The highest sensitivity was found to occur when the pickup electrodes were centered over the artery. In this work, we used microfabricated carbon infiltrated-carbon nanotube electrodes to measure the change in contact bioimpedance for dry electrodes, and identical electrodes with a wet electrolyte, on five human subjects in the range of 1 kHz to 100 kHz. We found that the acclimated skin-electrode impedance of the dry electrodes approached that of the wet electrodes, especially for electrodes with larger areas. We also found that the acclimation time does not appear to depend on electrode area or frequency. The skin-electrode impedance after acclimation does depend on electrode area and frequency, decreasing with both. This work shows that if care is taken during the acclimation period, then dry carbon composite electrodes can be used in bioimpedance wearable applications.

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Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research.