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The zinc oxide nanowires being grown are not developing properly and need to be fixed. In order to do this, the furnace equipment and experimental procedure must be tested until the results produced yield acceptable quality zinc oxide nanowires. After experimentation the nanowires were produced to an acceptable quality. With quality nanowires to experiment with, testing began to examine the effects of different thicknesses of aluminum dopants. Once doped and annealed, the wires were transferred to a substrate with a grid so contact points could be applied. However; the experiment was phased out once this step was half way complete due to the lab shifting to examine co-doping zinc oxide nanowires as explored in part two of this paper. The goal of co-doping zinc oxide film is to create an ideal p
type relationship for power generation, so this project focuses on altering the electrical properties of zinc oxide through doping that will allow more energy to be generated from the solar panels than current zinc oxide solar panels. The zinc oxide film doped with manganese was sputtered onto a silicon substrate. The experiment failed to create a co-doped sample because an x-ray photoelectron spectroscopy reading of the sample proved no nitrogen existed in the zinc oxide doped with manganese film. This experiment leads into this research teams work with co-doping, so instead of viewing this project as a failure it is seen as a learning experience. The research team is examining the results and creating new experiments to run to fix the problem. I currently work with my mentor Dr. Hongbin Yu and Seung Ho Ahn while doing research.
type relationship for power generation, so this project focuses on altering the electrical properties of zinc oxide through doping that will allow more energy to be generated from the solar panels than current zinc oxide solar panels. The zinc oxide film doped with manganese was sputtered onto a silicon substrate. The experiment failed to create a co-doped sample because an x-ray photoelectron spectroscopy reading of the sample proved no nitrogen existed in the zinc oxide doped with manganese film. This experiment leads into this research teams work with co-doping, so instead of viewing this project as a failure it is seen as a learning experience. The research team is examining the results and creating new experiments to run to fix the problem. I currently work with my mentor Dr. Hongbin Yu and Seung Ho Ahn while doing research.
ContributorsBull, David Sean (Author) / Yu, Hongbin (Thesis director) / Ahn, Seung Ho (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor)
Created2014-05
Description
Graphene, a one atomic thick planar sheet of carbon atoms, has a zero gap band structure with a linear dispersion relation. This unique property makes graphene a favorite for physicists and engineers, who are trying to understand the mechanism of charge transport in graphene and using it as channel material for field effect transistor (FET) beyond silicon. Therefore, an in-depth exploring of these electrical properties of graphene is urgent, which is the purpose of this dissertation. In this dissertation, the charge transport and quantum capacitance of graphene were studied. Firstly, the transport properties of back-gated graphene transistor covering by high dielectric medium were systematically studied. The gate efficiency increased by up to two orders of magnitude in the presence of a high top dielectric medium, but the mobility did not change significantly. The results strongly suggested that the previously reported top dielectric medium-induced charge transport properties of graphene FETs were possibly due to the increase of gate capacitance, rather than enhancement of carrier mobility. Secondly, a direct measurement of quantum capacitance of graphene was performed. The quantum capacitance displayed a non-zero minimum at the Dirac point and a linear increase on both sides of the minimum with relatively small slopes. The findings - which were not predicted by theory for ideal graphene - suggested that scattering from charged impurities also influences the quantum capacitance. The capacitances in aqueous solutions at different ionic concentrations were also measured, which strongly suggested that the longstanding puzzle about the interfacial capacitance in carbon-based electrodes had a quantum origin. Finally, the transport and quantum capacitance of epitaxial graphene were studied simultaneously, the quantum capacitance of epitaxial graphene was extracted, which was similar to that of exfoliated graphene near the Dirac Point, but exhibited a large sub-linear behavior at high carrier density. The self-consistent theory was found to provide a reasonable description of the transport data of the epitaxial graphene device, but a more complete theory was needed to explain both the transport and quantum capacitance data.
ContributorsXia, Jilin (Author) / Tao, N.J. (Thesis advisor) / Ferry, David (Committee member) / Thornton, Trevor (Committee member) / Tsui, Raymond (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2010
Description
This paper will primarily deal with obstacle detection and the benefits that radar technology provides as the primary interface. The concept that is being proposed involves using a non-industrialized radar to achieve similar results when trying to detect a present object. By being able to achieve a working radar detection system at a more general domain, the path to it becoming more universal accessible increases. This, in turn, will hopefully amplify the areas in which radar technology can be applied to and lead to great benefits universally. From the compiled data and the work that has been done to achieve a responsive radar, it is noted that the radar will provide an accurate reading in most conditions that it is introduced to. These conditions vary from range resolution aspects to various weather environments, as well as the visibility aspect. However, based on the results that were achieved, through various testing, there are still some areas in which radar technology needs to improve in, for it to be fully considered as the sole interface when it comes to obstacle detection and its integration into future technology like self-driving cars. Nevertheless, the capabilities of radar technology at this caliber is noted to be quite impressive and similar to other more expansive options that are available.
ContributorsMartinez, Johan (Author) / Yu, Hongbin (Thesis director) / Houghton, Todd (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
Two nested capacitors can produce work if the electric fields are not aligned, and the purpose of this research was to explore the possibility of using that generation instead of DC motors. The work the capacitors produce is determined by the strength of the fields and materials that is composed of. The power density of the object is then determined by the volume. As the electric field increases in strength, the power increases, so to create a very strong internal field. The nested capacitors use a dielectric to prevent breakdown from the strength of the field. Additionally, as the nested capacitors decrease in size, their power density increases rapidly \u2014 becoming close to a dc motor's power density around the 500mm^2 size. When the result was simulated, it was discovered that the electric field was not contained to the dielectric and would result in sparking. Several other concerns would need to be addressed for this to become a viable solution.
ContributorsFryda, George Andrew (Author) / Singh, Anoop (Thesis director) / Yu, Hongbin (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The focus of this study was to address the problem of prohibitively expensive LiDARs currently being used in autonomous vehicles by analyzing the capabilities and shortcomings of affordable LiDARs as replacements. This involved the characterization of affordable LiDARs that are currently available on the market. The characterization of the LiDARs involved testing refresh rates, field of view, distance the sensors could detect, reflectivity, and power of the emitters. The four LiDARs examined in this study were the Scanse, RPLIDAR A2, LeddarTech Vu8, and LeddarTech M16. Of these low cost LiDAR options we find the two best options for use in affordable autonomous vehicle sensors to be the RPLIDAR A2 and the LeddarTech M16.
ContributorsMurphy, Thomas Joseph (Co-author) / Gamal, Eltohamy (Co-author) / Yu, Hongbin (Thesis director) / Houghton, Todd (Committee member) / Electrical Engineering Program (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This research report investigates the feasibility of using RFID in Traffic Sign Recognition (TSR) Systems for autonomous vehicles, specifically driver-less cars. Driver-less cars are becoming more prominent in society but must be designed to integrate with the current transportation infrastructure. Current research in TSR systems use image processing as well as LIDAR to identify traffic signs, yet these are highly dependent on lighting conditions, camera quality and sign visibility. The read rates of current TSR systems in literature are approximately 96 percent. The usage of RFID in TSR systems can improve the performance of traditional TSR systems. An RFID TSR was designed for the Autonomous Pheeno Test-bed at the Arizona State University (ASU) Autonomous Collective Systems (ACS) Laboratory. The system was tested with varying parameters to see the effect of the parameters on the read rate. It was found that high reader strength and low tag distance had a maximum read rate of 96.3 percent, which is comparable to existing literature. It was proven that an RFID TSR can perform as well as traditional TSR systems, and has the capacity to improve accuracy when used alongside RGB cameras and LIDAR.
ContributorsMendoza, Madilyn Kido (Author) / Berman, Spring (Thesis director) / Yu, Hongbin (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In this work, experimental photonic power converter (PPC) design, fabrication and characterization has been used, along with electrical and optical modeling, to study theoretical efficiency limits of monochromatic photovoltaic (PV) energy conversion due to photon recycling. The back-surface reflectance of a photovoltaic (PV) cell is known to strongly influence external radiative efficiency, a photon recycling metric (ERE), especially when reflectance is close to 100 %. Considering a perfect back reflector, an upper PV cell efficiency limit of 70.9 % and 85 % is calculated for 870.7 nm illumination at an intensity that would generate 32 mA/cm2 (1-sun) and 100 A/cm2 (3125-sun eq) photocurrent, respectively. However, when realistic non-idealities are introduced, ideal efficiency can drop by 21 % for both cases as long as the series resistivity for cells under high intensity illumination is limited to 1 mΩ cm^2. This presents a challenge for photonic energy conversion technology where high intensity lasers are typically used to deliver power to equipment from remote locations. This work discusses ways to provide reflectance enhancement while allowing sufficient current flow at the back surface. One way to do this is to use a planar transparent conductive oxide and reflective metal at the back surface. This work measures and compares the back-surface reflectance of IZO/Ag to standard reflective/conductive materials such as Au and Ag. A comparison between cells with the highest V_OC for cells processed with Au and IZO/Ag as reflective back contacts show that the V_OC for the IZO/Ag cell outperforms that of the Au cell by 6.6 mV measuring V_OC=1.071 V with a cell efficiency of 51.0 % at 780 nm LED illumination. Efficiency calculations extrapolated to other monochromatic light sources identified 841 nm as the optimal wavelength for the IZO/Ag cells with a projected efficiency of η_cell=55.5 % for incident intensity corresponding to 1-sun photocurrent. With the fill factors comparable between the cell types, at least at intensities near 1-sun equivalent photocurrent, the IZO/Ag reflective back contact design demonstrates benefits from photon recycling while not sacrificing voltage drop due to series resistance compared to cells with a standard Au back contact.
ContributorsBabcock, Sean Joseph (Author) / King, Richard R (Thesis advisor) / Honsberg, Christiana B (Committee member) / Goryll, Michael (Committee member) / Goodnick, Stephen M (Committee member) / Arizona State University (Publisher)
Created2022
Description
Patterning technologies for micro/nano-structures have been essentially used in a variety of discipline research areas, including electronics, optics, material science, and biotechnology. Therefore their importance has dramatically increased over the past decades. This dissertation presents various advanced patterning processes utilizing cross-discipline technologies, e.g., photochemical deposition, transfer printing (TP), and nanoimprint lithography (NIL), to demonstrate inexpensive, high throughput, and scalable manufacturing for advanced optical applications.
The polymer-assisted photochemical deposition (PPD) method is employed in the form of additive manufacturing (AM) to print ultra-thin (< 5 nm) and continuous film in micro-scaled (> 6.5 μm) resolution. The PPD film acts as a lossy material in the Fabry-Pérot cavity structures and generates vivid colored images with a micro-scaled resolution by inducing large modulation of reflectance. This PPD-based structural color printing performs without photolithography and vacuum deposition in ambient and room-temperature conditions, which enables an accessible and inexpensive process (Chapter 1).
In the TP process, germanium (Ge) is used as the nucleation layer of noble metallic thin films to prevent structural distortion and improve surface morphology. The developed Ge-assisted transfer printing (GTP) demonstrates its feasibility transferring sub-100 nm features with up to 50 nm thickness in a centimeter scale. The GTP is also capable of transferring arbitrary metallic nano-apertures with minimal pattern distortion, providing relatively less expensive, simpler, and scalable manufacturing (Chapter 2).
NIL is employed to fabricate the double-layered chiral metasurface for polarimetric imaging applications. The developed NIL process provides multi-functionalities with a single NIL, i.e., spacing layer, planarized surface, and formation of dielectric gratings, respectively, which significantly reduces fabrication processing time and potential cost by eliminating several steps in the conventional fabrication process. During the integration of two metasurfaces, the Moiré fringe based alignment method is employed to accomplish the alignment accuracy of less than 200 nm in both x- and y-directions, which is superior to conventional photolithography. The dramatically improved optical performance, e.g., highly improved circular polarization extinction ratio (CPER), is also achieved with the developed NIL process (Chapter 3).
ContributorsChoi, Shinhyuk (Author) / Wang, Chao (Thesis advisor) / Yu, Hongbin (Committee member) / Holman, Zachary (Committee member) / Hwa, Yoon (Committee member) / Arizona State University (Publisher)
Created2023
Description
The objective of this dissertation is to study the optical and radiative properties of inhomogeneous metallic structures. In the ongoing search for new materials with tunable optical characteristics, porous metals and nanowires provides an extensive design space to engineer its optical response based on the morphology-dependent phenomena.This dissertation firstly discusses the use of aluminum nanopillar array on a quartz substrate as spectrally selective optical filter with narrowband transmission for thermophotovoltaic systems. The narrow-band transmission enhancement is attributed to the magnetic polariton resonance between neighboring aluminum nanopillars. Tuning of the resonance wavelengths for selective filters was achieved by changing the nanopillar geometry. It concludes by showing improved efficiency of Gallium-Antimonide thermophotovoltaic system by coupling the designed filter with the cell.
Next, isotropic nanoporous gold films are investigated for applications in energy conversion and three-dimensional laser printing. The fabricated nanoporous gold samples are characterized by scanning electron microscopy, and the spectral hemispherical reflectance is measured with an integrating sphere. The effective isotropic optical constants of nanoporous gold with varying pore volume fraction are modeled using the Bruggeman effective medium theory.
Nanoporous gold are metastable and to understand its temperature dependent optical properties, a lab-scale fiber-based optical spectrometer setup is developed to characterize the in-situ specular reflectance of nanoporous gold thin films at temperatures ranging from 25 to 500 oC. The in-situ and the ex-situ measurements suggest that the
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specular, diffuse, and hemispherical reflectance varies as a function of temperature due to the morphology (ligament diameter) change observed.
The dissertation continues with modeling and measurements of the radiative properties of porous powders. The study shows the enhanced absorption by mixing porous copper to copper powder. This is important from the viewpoint of scalability to get end products such as sheets and tubes with the requirement of high absorptance that can be produced through three-dimensional printing.
Finally, the dissertation concludes with recommendations on the methods to fabricate the suggested optical filters to improve thermophotovoltaic system efficiencies. The results presented in this dissertation will facilitate not only the manufacturing of materials but also the promising applications in solar thermal energy and optical systems.
ContributorsRamesh, Rajagopalan (Author) / Wang, Liping (Thesis advisor) / Azeredo, Bruno (Thesis advisor) / Phelan, Patrick (Committee member) / Yu, Hongbin (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2022
Description
The integration of Distributed Energy Resources (DER), including wind energy and photovoltaic (PV) panels, into power systems, increases the potential for events that could lead to outages and cascading failures. This risk is heightened by the limited dynamic information in energy grid datasets, primarily due to sparse Phasor Measurement Units (PMUs) placement. This data quality issue underscores the need for effective methodologies to manage these challenges. One significant challenge is the data gaps in low-resolution (LR) data from RTU and smart meters, hindering robust machine learning (ML) applications. To address this, a systematic approach involves preparing data effectively and designing efficient event detection methods, utilizing both intrinsic physics and extrinsic correlations from power systems. The process begins by interpolating LR data using high-resolution (HR) data, aiming to create virtual PMUs for improved grid management. Current interpolation methods often overlook extrinsic spatial-temporal correlations and intrinsic governing equations like Ordinary Differential Equations (ODEs) or Differential Algebraic Equations (DAEs). Physics-Informed Neural Networks (PINNs) are used for this purpose, though they face challenges with limited LR samples. The solution involves exploring the embedding space governed by ODEs/DAEs, generating extrinsic correlations for initial LR data imputation, and enforcing intrinsic physical constraints for refinement. After data preparation, event data dimensions such as spatial, temporal, and measurement categories are recovered in a tensor. To prevent overfitting, common in traditional ML methods, tensor decomposition is used. This technique merges intrinsic and physical information across dimensions, yielding informative and compact feature vectors for efficient feature extraction and learning in event detection. Lastly, in grids with insufficient data, knowledge transfer from grids with similar event patterns is a viable solution. This involves optimizing projected and transferred vectors from tensor decomposition to maximize common knowledge utilization across grids. This strategy identifies common features, enhancing the robustness and efficiency of ML event detection models, even in scenarios with limited event data.
ContributorsMa, Zhihao (Author) / Weng, Yang (Thesis advisor) / Wu, Meng (Committee member) / Yu, Hongbin (Committee member) / Matavalam, Amarsagar Reddy Ramapuram (Committee member) / Arizona State University (Publisher)
Created2023