Matching Items (134)
Description
A thermochromic mid-infrared filter is designed, where a spectrally-selective transmittance peak exists while vanadium dioxide layers are below their transition temperature but broad opaqueness is observed below the transition temperature. This filter takes advantage of interference effects between a silicon spacer and insulating vanadium dioxide to create the transmittance peak and the drastic optical property change between insulating and metallic vanadium dioxide. The theoretical performance of the filter in energy dissipation and thermal camouflaging applications is analyzed and can be optimized by tuning the thicknesses of the thin-film layers.
ContributorsChao, Jeremy (Author) / Wang, Liping (Thesis director) / Taylor, Sydney (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Zeolitic Imidazolate Frameworks (ZIFs) are a promising technology for the separation of gases. ZIFs represent a type of hybrid material that is a subset of metal organic frameworks while displaying zeolite properties. ZIFs have tunable pore metrics, high thermal stability, and large surface areas giving them advantages over traditional zeolites. The experiment sought to determine the flux of hexane vapor through ZIF-68 with Fourier Transform Infrared Spectroscopy (FTIR) mapping. FTIR mapping was used to obtain three spectra per crystal and the concentration gradient was analyzed to determine the flux. ZIF-68 was completely stable when loaded with hexane and exposed to the atmosphere. There was no hexane diffusion out of the crystal. As a result, ZIF-68 was heated to 50°C to increase diffusion and calculate the flux. ZIF-68 adhered to Knudsen Diffusion, and the flux was calculated to be 2.00*10-5 kg mol/s*m2. The small flux occurred because almost no concentration gradient was obtained through the crystal. It was hypothesized that the resistance in the crystal was substantially lower than the resistance at the boundary layer, which would have caused a small concentration gradient. Using film mass transfer theory, the resistance inside the crystal was found to be 1200 times lower than the resistance at the boundary layer confirming the hypothesis.
ContributorsSigrist, Dallas Dale (Author) / Lin, Jerry (Thesis director) / Wang, Liping (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper discusses the theoretical approximation and attempted measurement of the quantum <br/>force produced by material interactions though the use of a tuning fork-based atomic force microscopy <br/>device. This device was built and orientated specifically for the measurement of the Casimir force as a <br/>function of separation distance using a piezo actuator for approaching and a micro tuning fork for the <br/>force measurement. This project proceeds with an experimental measurement of the ambient Casmir force <br/>through the use of a tuning fork-based AFM to determine its viability in measuring the magnitude of the <br/>force interaction between an interface material and the tuning fork probe. The ambient measurements <br/>taken during the device’s development displayed results consistent with theoretical approximations, while<br/>demonstrating the capability to perform high-precision force measurements. The experimental results<br/>concluded in a successful development of a device which has the potential to measure forces of <br/>magnitude 10−6 to 10−9 at nanometric gaps. To conclude, a path to material analysis using an approach <br/>stage, alternative methods of testing, and potential future experiments are speculated upon.
ContributorsMulkern, William Michael (Author) / Wang, Liping (Thesis director) / Kwon, Beomjin (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Tunable Near-Field Radiative Heat Transfer Exceeding Blackbody Limit with Vanadium Dioxide Thin Film
Description
This paper investigates near-field thermal radiation as the primary source of heat transfer between two parallel surfaces. This radiation takes place extremely close to the heated surfaces in study so the experimental set-up to be used will be done at the nanometer scale. The primary theory being investigated is that near-field radiation generates greater heat flux that conventional radiation governed by Planck’s law with maximum for blackbodies. Working with a phase shift material such as VO2 enables a switch-like effect to occur where the total amount of heat flux fluctuates as VO2 transitions from a metal to an insulator. In this paper, the theoretical heat flux and near-field radiation effect are modeled for a set-up of VO2 and SiO2 layers separated by different vacuum gaps. In addition, a physical experimental set-up is validated for future near-field radiation experiments.
ContributorsSluder, Nicole (Author) / Wang, Liping (Thesis director) / Wang, Ropert (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Open source image analytics and data mining software are widely available but can be overly-complicated and non-intuitive for medical physicians and researchers to use. The ASU-Mayo Clinic Imaging Informatics Lab has developed an in-house pipeline to process medical images, extract imaging features, and develop multi-parametric models to assist disease staging and diagnosis. The tools have been extensively used in a number of medical studies including brain tumor, breast cancer, liver cancer, Alzheimer's disease, and migraine. Recognizing the need from users in the medical field for a simplified interface and streamlined functionalities, this project aims to democratize this pipeline so that it is more readily available to health practitioners and third party developers.
ContributorsBaer, Lisa Zhou (Author) / Wu, Teresa (Thesis director) / Wang, Yalin (Committee member) / Computer Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Video object segmentation (VOS) is an important task in computer vision with a lot of applications, e.g., video editing, object tracking, and object based encoding. Different from image object segmentation, video object segmentation must consider both spatial and temporal coherence for the object. Despite extensive previous work, the problem is still challenging. Usually, foreground object in the video draws more attention from humans, i.e. it is salient. In this thesis we tackle the problem from the aspect of saliency, where saliency means a certain subset of visual information selected by a visual system (human or machine). We present a novel unsupervised method for video object segmentation that considers both low level vision cues and high level motion cues. In our model, video object segmentation can be formulated as a unified energy minimization problem and solved in polynomial time by employing the min-cut algorithm. Specifically, our energy function comprises the unary term and pair-wise interaction energy term respectively, where unary term measures region saliency and interaction term smooths the mutual effects between object saliency and motion saliency. Object saliency is computed in spatial domain from each discrete frame using multi-scale context features, e.g., color histogram, gradient, and graph based manifold ranking. Meanwhile, motion saliency is calculated in temporal domain by extracting phase information of the video. In the experimental section of this thesis, our proposed method has been evaluated on several benchmark datasets. In MSRA 1000 dataset the result demonstrates that our spatial object saliency detection is superior to the state-of-art methods. Moreover, our temporal motion saliency detector can achieve better performance than existing motion detection approaches in UCF sports action analysis dataset and Weizmann dataset respectively. Finally, we show the attractive empirical result and quantitative evaluation of our approach on two benchmark video object segmentation datasets.
ContributorsWang, Yilin (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Cleveau, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
ContributorsYang, Tao (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solar energy has become one of the most popular renewable energy in human’s life because of its abundance and environment friendliness. To achieve high solar energy conversion efficiency, it usually requires surfaces to absorb selectivity within one spectral range of interest and reflect strongly over the rest of the spectrum. An economic method is always desired to fabricate spectrally selective surfaces with improved energy conversion efficiency. Colloidal lithography is a recently emerged way of nanofabrication, which has advantages of low-cost and easy operation.
In this thesis, aluminum metasurface structures are proposed based on colloidal lithography method. High Frequency Structure Simulator is used to numerically study optical properties and design the aluminum metasurfaces with selective absorption. Simulation results show that proposed aluminum metasurface structure on aluminum oxide thin film and aluminum substrate has a major reflectance dip, whose wavelength is tunable within the near-infrared and visible spectrum with metasurface size. As the metasurface is opaque due to aluminum film, it indicates strong wavelength-selective optical absorption, which is due to the magnetic resonance between the top metasurface and bottom Al film within the aluminum oxide layer.
The proposed sample is fabricated based on colloidal lithography method. Monolayer polystyrene particles of 500 nm are successfully prepared and transferred onto silicon substrate. Scanning electron microscope is used to check the surface topography. Aluminum thin film with 20-nm or 50-nm thickness is then deposited on the sample. After monolayer particles are removed, optical properties of samples are measured by micro-scale optical reflectance and transmittance microscope. Measured and simulated reflectance of these samples do not have frequency selective properties and is not sensitive to defects. The next step is to fabricate the Al metasurface on Al_2 O_3 and Al films to experimentally demonstrate the selective absorption predicted from the numerical simulation.
In this thesis, aluminum metasurface structures are proposed based on colloidal lithography method. High Frequency Structure Simulator is used to numerically study optical properties and design the aluminum metasurfaces with selective absorption. Simulation results show that proposed aluminum metasurface structure on aluminum oxide thin film and aluminum substrate has a major reflectance dip, whose wavelength is tunable within the near-infrared and visible spectrum with metasurface size. As the metasurface is opaque due to aluminum film, it indicates strong wavelength-selective optical absorption, which is due to the magnetic resonance between the top metasurface and bottom Al film within the aluminum oxide layer.
The proposed sample is fabricated based on colloidal lithography method. Monolayer polystyrene particles of 500 nm are successfully prepared and transferred onto silicon substrate. Scanning electron microscope is used to check the surface topography. Aluminum thin film with 20-nm or 50-nm thickness is then deposited on the sample. After monolayer particles are removed, optical properties of samples are measured by micro-scale optical reflectance and transmittance microscope. Measured and simulated reflectance of these samples do not have frequency selective properties and is not sensitive to defects. The next step is to fabricate the Al metasurface on Al_2 O_3 and Al films to experimentally demonstrate the selective absorption predicted from the numerical simulation.
ContributorsGuan, Chuyun (Author) / Wang, Liping (Thesis advisor) / Azeredo, Bruno (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation constructs a new computational processing framework to robustly and precisely quantify retinotopic maps based on their angle distortion properties. More generally, this framework solves the problem of how to robustly and precisely quantify (angle) distortions of noisy or incomplete (boundary enclosed) 2-dimensional surface to surface mappings. This framework builds upon the Beltrami Coefficient (BC) description of quasiconformal mappings that directly quantifies local mapping (circles to ellipses) distortions between diffeomorphisms of boundary enclosed plane domains homeomorphic to the unit disk. A new map called the Beltrami Coefficient Map (BCM) was constructed to describe distortions in retinotopic maps. The BCM can be used to fully reconstruct the original target surface (retinal visual field) of retinotopic maps. This dissertation also compared retinotopic maps in the visual processing cascade, which is a series of connected retinotopic maps responsible for visual data processing of physical images captured by the eyes. By comparing the BCM results from a large Human Connectome project (HCP) retinotopic dataset (N=181), a new computational quasiconformal mapping description of the transformed retinal image as it passes through the cascade is proposed, which is not present in any current literature. The description applied on HCP data provided direct visible and quantifiable geometric properties of the cascade in a way that has not been observed before. Because retinotopic maps are generated from in vivo noisy functional magnetic resonance imaging (fMRI), quantifying them comes with a certain degree of uncertainty. To quantify the uncertainties in the quantification results, it is necessary to generate statistical models of retinotopic maps from their BCMs and raw fMRI signals. Considering that estimating retinotopic maps from real noisy fMRI time series data using the population receptive field (pRF) model is a time consuming process, a convolutional neural network (CNN) was constructed and trained to predict pRF model parameters from real noisy fMRI data
ContributorsTa, Duyan Nguyen (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Hansford, Dianne (Committee member) / Liu, Huan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Biogas’s potential as a renewable fuel source has been an area of increased research in recent years. One issue preventing wide-spread use of biogas as a fuel is the trace amounts of impurities that damage fuel-burning equipment by depositing silicon, sulfur, calcium and other elements on their surface. This study aims to analyze the effects of a high concentration of L4 linear siloxane on solid oxide fuel cell performance until failure occurs. L4 siloxane has not been extensively researched previously, and this investigation aims to provide new data to support similar, though slower, degradation compared to D4, D5 and other siloxanes in solid oxide fuel cells. The experiments were conducted inside a furnace heated to 800℃ with an Ni-YSZ-supported (Nickel-yttria-stabilized zirconia) fuel cell. A fuel source with a flow rate of 20 mL/min of hydrogen gas, 10 mL/min of nitrogen gas and 0.15 mL/min of L4 siloxane was used. Air was supplied to the cathode. The effects of siloxane deposition on cell voltage and power density degradation and resistance increase were studied by using techniques like the current-voltage method, electrochemical impedance spectroscopy, and gas chromatography. The results of the experiment after reduction show roughly constant degradation of 8.35 mV/hr, followed after approximately 8 hours by an increasing degradation until cell failure of 130.45 mV/hr. The initial degradation and stagnation match previous research in siloxane deposition on SOFCs, but the sharp decline to failure does not. A mechanism for solid oxide fuel cell failure is proposed based on the data.
ContributorsRiley, Derall M. (Author) / Milcarek, Ryan J (Thesis advisor) / Wang, Liping (Committee member) / Phelan, Patrick E (Committee member) / Arizona State University (Publisher)
Created2021