Nanostructured Metal Oxide Coatings for Electrochemical Energy Conversion and Storage Electrodes

The realization of an energy future based on safe, clean, sustainable, and economically viable technologies is one of the grand challenges facing modern society. Electrochemical energy technologies underpin the potential success of this effort to divert energy sources away from fossil fuels, whether one considers alternative energy conversion strategies through photoelectrochemical (PEC) production of chemical fuels or fuel cells run with sustainable hydrogen, or energy storage strategies, such as in batteries and supercapacitors. This dissertation builds on recent advances in nanomaterials design, synthesis, and characterization to develop novel electrodes that can electrochemically convert and store energy.

Chapter 2 of this dissertation focuses on refining the properties of TiO2-based PEC water-splitting photoanodes used for the direct electrochemical conversion of solar energy into hydrogen fuel. The approach utilized atomic layer deposition (ALD); a growth process uniquely suited for the conformal and uniform deposition of thin films with angstrom-level thickness precision. ALD’s thickness control enabled a better understanding of how the effects of nitrogen doping via NH3 annealing treatments, used to reduce TiO2’s bandgap, can have a strong dependence on TiO2’s thickness and crystalline quality. In addition, it was found that some of the negative effects on the PEC performance typically associated with N-doped TiO2 could be mitigated if the NH3-annealing was directly preceded by an air-annealing step, especially for ultrathin (i.e., < 10 nm) TiO2 films. ALD was also used to conformally coat an ultraporous conductive fluorine-doped tin oxide nanoparticle (nanoFTO) scaffold with an ultrathin layer of TiO2. The integration of these ultrathin films and the oxide nanoparticles resulted in a heteronanostructure design with excellent PEC water oxidation photocurrents (0.7 mA/cm2 at 0 V vs. Ag/AgCl) and charge transfer efficiency.

In Chapter 3, two innovative nanoarchitectures were engineered in order to enhance the pseudocapacitive energy storage of next generation supercapacitor electrodes. The morphology and quantity of MnO2 electrodeposits was controlled by adjusting the density of graphene foliates on a novel graphenated carbon nanotube (g-CNT) scaffold. This control enabled the nanocomposite supercapacitor electrode to reach a capacitance of 640 F/g, under MnO2 specific mass loading conditions (2.3 mg/cm2) that are higher than previously reported. In the second engineered nanoarchitecture, the electrochemical energy storage properties of a transparent electrode based on a network of solution-processed Cu/Ni cores/shell nanowires (NWs) were activated by electrochemically converting the Ni metal shell into Ni(OH)2. Furthermore, an adjustment of the molar percentage of Ni plated onto the Cu NWs was found to result in a tradeoff between capacitance, transmittance, and stability of the resulting nickel hydroxide-based electrode. The nominal area capacitance and power performance results obtained for this Cu/Ni(OH)2 transparent electrode demonstrates that it has significant potential as a hybrid supercapacitor electrode for integration into cutting edge flexible and transparent electronic devices.

Numerical Simulations for the Design of Novel Integrated Parallel Reception, Excitation, and Shimming (iPRES) Coil Arrays

Magnetic field inhomogeneity results in image artifacts including signal loss, image blurring and distortions, leading to decreased diagnostic accuracy. Conventional multi-coil (MC) shimming method employs both RF coils and shimming coils, whose mutual interference induces a tradeoff between RF signal-to-noise (SNR) ratio and shimming performance. To address this issue, RF coils were integrated with direct-current (DC) shim coils to shim field inhomogeneity while concurrently emitting and receiving RF signal without being blocked by the shim coils. The currents applied to the new coils, termed iPRES (integrated parallel reception, excitation and shimming), were optimized in the numerical simulation to improve the shimming performance. The objectives of this work is to offer a guideline for designing the optimal iPRES coil arrays to shim the abdomen.

In this thesis work, the main field () inhomogeneity was evaluated by root mean square error (RMSE). To investigate the shimming abilities of iPRES coil arrays, a set of the human abdomen MRI data was collected for the numerical simulations. Thereafter, different simplified iPRES(N) coil arrays were numerically modeled, including a 1-channel iPRES coil and 8-channel iPRES coil arrays. For 8-channel iPRES coil arrays, each RF coil was split into smaller DC loops in the x, y and z direction to provide extra shimming freedom. Additionally, the number of DC loops in a RF coil was increased from 1 to 5 to find the optimal divisions in z direction. Furthermore, switches were numerically implemented into iPRES coils to reduce the number of power supplies while still providing similar shimming performance with equivalent iPRES coil arrays.

The optimizations demonstrate that the shimming ability of an iPRES coil array increases with number of DC loops per RF coil. Furthermore, the z direction divisions tend to be more effective in reducing field inhomogeneity than the x and y divisions. Moreover, the shimming performance of an iPRES coil array gradually reach to a saturation level when the number of DC loops per RF coil is large enough. Finally, when switches were numerically implemented in the iPRES(4) coil array, the number of power supplies can be reduced from 32 to 8 while keeping the shimming performance similar to iPRES(3) and better than iPRES(1). This thesis work offers a guidance for the designs of iPRES coil arrays.

Using Coding to Improve Localization and Backscatter Communication Performance in Low-Power Sensor Networks

Backscatter communication is an emerging wireless technology that recently has gained an increase in attention from both academic and industry circles. The key innovation of the technology is the ability of ultra-low power devices to utilize nearby existing radio signals to communicate. As there is no need to generate their own energetic radio signal, the devices can benefit from a simple design, are very inexpensive and are extremely energy efficient compared with traditional wireless communication. These benefits have made backscatter communication a desirable candidate for distributed wireless sensor network applications with energy constraints.

The backscatter channel presents a unique set of challenges. Unlike a conventional one-way communication (in which the information source is also the energy source), the backscatter channel experiences strong self-interference and spread Doppler clutter that mask the information-bearing (modulated) signal scattered from the device. Both of these sources of interference arise from the scattering of the transmitted signal off of objects, both stationary and moving, in the environment. Additionally, the measurement of the location of the backscatter device is negatively affected by both the clutter and the modulation of the signal return.

This work proposes a channel coding framework for the backscatter channel consisting of a bi-static transmitter/receiver pair and a quasi-cooperative transponder. It proposes to use run-length limited coding to mitigate the background self-interference and spread-Doppler clutter with only a small decrease in communication rate. The proposed method applies to both binary phase-shift keying (BPSK) and quadrature-amplitude modulation (QAM) scheme and provides an increase in rate by up to a factor of two compared with previous methods.

Additionally, this work analyzes the use of frequency modulation and bi-phase waveform coding for the transmitted (interrogating) waveform for high precision range estimation of the transponder location. Compared to previous methods, optimal lower range sidelobes are achieved. Moreover, since both the transmitted (interrogating) waveform coding and transponder communication coding result in instantaneous phase modulation of the signal, cross-interference between localization and communication tasks exists. Phase discriminating algorithm is proposed to make it possible to separate the waveform coding from the communication coding, upon reception, and achieve localization with increased signal energy by up to 3 dB compared with previous reported results.

The joint communication-localization framework also enables a low-complexity receiver design because the same radio is used both for localization and communication.

Simulations comparing the performance of different codes corroborate the theoretical results and offer possible trade-off between information rate and clutter mitigation as well as a trade-off between choice of waveform-channel coding pairs. Experimental results from a brass-board microwave system in an indoor environment are also presented and discussed.

Expert assessments of retrofitting coal-fired power plants with carbon dioxide capture technologies

A set of 13 US based experts in post-combustion and oxy-fuel combustion CO2 capture systems responded to an extensive questionnaire asking their views on the present status and future expected performance and costs for amine-based, chilled ammonia, and oxy-combustion retrofits of coal-fired power plants. This paper presents the experts' responses for technology maturity, ideal plant characteristics for early adopters, and the extent to which R&D and deployment incentives will impact costs. It also presents the best estimates and 95% confidence limits of the energy penalties associated with amine-based systems. The results show a general consensus that amine-based systems are closer to commercial application, but potential for improving performance and lowering costs is limited; chilled ammonia and oxy-combustion offer greater potential for cost reductions, but not without greater uncertainty regarding scale and technical feasibility. © 2011 Elsevier Ltd.

Improving supply chain performance: Real-time demand information and flexible deliveries

In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.

Nonlinear oscillator metamaterial model: numerical and experimental verification.

We verify numerically and experimentally the accuracy of an analytical model used to derive the effective nonlinear susceptibilities of a varactor-loaded split ring resonator (VLSRR) magnetic medium. For the numerical validation, a nonlinear oscillator model for the effective magnetization of the metamaterial is applied in conjunction with Maxwell equations and the two sets of equations solved numerically in the time-domain. The computed second harmonic generation (SHG) from a slab of a nonlinear material is then compared with the analytical model. The computed SHG is in excellent agreement with that predicted by the analytical model, both in terms of magnitude and spectral characteristics. Moreover, experimental measurements of the power transmitted through a fabricated VLSRR metamaterial at several power levels are also in agreement with the model, illustrating that the effective medium techniques associated with metamaterials can accurately be transitioned to nonlinear systems.

Environmental and technology policies for climate mitigation

We assess different policies for reducing carbon dioxide emissions and promoting innovation and diffusion of renewable energy. We evaluate the relative performance of policies according to incentives provided for emissions reduction, efficiency, and other outcomes. We also assess how the nature of technological progress through learning and research and development (R&D), and the degree of knowledge spillovers, affects the desirability of different policies. Due to knowledge spillovers, optimal policy involves a portfolio of different instruments targeted at emissions, learning, and R&D. Although the relative cost of individual policies in achieving reductions depends on parameter values and the emissions target, in a numerical application to the U.S. electricity sector, the ranking is roughly as follows: (1) emissions price, (2) emissions performance standard, (3) fossil power tax, (4) renewables share requirement, (5) renewables subsidy, and (6) R&D subsidy. Nonetheless, an optimal portfolio of policies achieves emissions reductions at a significantly lower cost than any single policy. © 2007 Elsevier Inc. All rights reserved.