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Articles 841 - 870 of 8897

Full-Text Articles in Physical Sciences and Mathematics

Nonlinear Meissner Effect In Nb3Sn Coplanar Resonators, Junki Makita, C. Sundahl, Gianluigi Ciovati, C. B. Eom, Alex Gurevich Jan 2022

Nonlinear Meissner Effect In Nb3Sn Coplanar Resonators, Junki Makita, C. Sundahl, Gianluigi Ciovati, C. B. Eom, Alex Gurevich

Physics Faculty Publications

We investigated the nonlinear Meissner effect (NLME) in Nb3Sn thin-film coplanar resonators by measuring the resonance frequency as a function of a parallel magnetic field at different temperatures. We used low rf power probing in films thinner than the London penetration depth λ(B) to significantly increase the field onset of vortex penetration and measure the NLME under equilibrium conditions. Contrary to the conventional quadratic increase of λ(B) with B expected in s-wave superconductors, we observed a nearly linear increase of the penetration depth with B. We concluded that this behavior of λ(B) is due to weak linked grain …

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A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell Jan 2022

A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell

Graduate Research Theses & Dissertations

A fully solid-state, software-defined, one-handed, handle-type control device built around a machine-learning (ML) model that provides intuitive and simultaneous control in position and orientation each in a full three degrees-of-freedom (DOF) is proposed in this paper. The device, referred to as the “Smart Handle”, and it is compact, lightweight, and only reliant on low-cost and readily available sensors and materials for construction. Mobility chairs for persons with motor difficulties could make use of a control device that can learn to recognize arbitrary inputs as control commands. Upper-extremity exoskeletons used in occupational settings and rehabilitation require a natural control device like …

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Optical Signal Processing With Discrete-Space Metamaterials, Mohammad Moein Moeini Jan 2022

Optical Signal Processing With Discrete-Space Metamaterials, Mohammad Moein Moeini

Wayne State University Dissertations

As digital circuits are approaching the limits of Moore’s law, a great deal of efforthas been directed to alternative computing approaches. Among them, the old concept of optical signal processing (OSP) has attracted attention, revisited in the light of metamaterials and nano-photonics. This approach has been successful in realizing basic mathematical operations, such as derivatives and integrals, but it is difficult to be applied to more complex ones. Inspired by digital filters, we propose a radically new OSP approach, able to realize arbitrary mathematical operations over a nano-photonic platform. We demonstrate this concept for the case of spatial differentiation, image …

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Chimeranet: U-Net For Hair Detection In Dermoscopic Skin Lesion Images, Norsang Lama, Reda Kasmi, Jason R. Hagerty, R. Joe Stanley, Reagan Harris Young, Jessica Miinch, Januka Nepal, Anand Nambisan, William V. Stoecker Jan 2022

Chimeranet: U-Net For Hair Detection In Dermoscopic Skin Lesion Images, Norsang Lama, Reda Kasmi, Jason R. Hagerty, R. Joe Stanley, Reagan Harris Young, Jessica Miinch, Januka Nepal, Anand Nambisan, William V. Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

Hair and ruler mark structures in dermoscopic images are an obstacle preventing accurate image segmentation and detection of critical network features. Recognition and removal of hairs from images can be challenging, especially for hairs that are thin, overlapping, faded, or of similar color as skin or overlaid on a textured lesion. This paper proposes a novel deep learning (DL) technique to detect hair and ruler marks in skin lesion images. Our proposed ChimeraNet is an encoder-decoder architecture that employs pretrained EfficientNet in the encoder and squeeze-and-excitation residual (SERes) structures in the decoder. We applied this approach at multiple image sizes …

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Developing An Open Database To Support Forensic Investigation Of Disasters In South East Asia: Forinsea V1.0, Andres Payo, Raushan Arnhardt, Angelo Carlo R. Galindo, Pham Van Dong, Ma. Aileen Leah G. Guzman, Yasmin O. Hatta, Andrew Bevan, Jose Claro N. Monje Jan 2022

Developing An Open Database To Support Forensic Investigation Of Disasters In South East Asia: Forinsea V1.0, Andres Payo, Raushan Arnhardt, Angelo Carlo R. Galindo, Pham Van Dong, Ma. Aileen Leah G. Guzman, Yasmin O. Hatta, Andrew Bevan, Jose Claro N. Monje

Electronics, Computer, and Communications Engineering Faculty Publications

This article describes the development of a bespoke database, FORINSEA1.0, created to address the need for a systematic curation of information needed for the descriptive phase of the FORIN approach and its application to two study areas in the South East Asia region. FORINSEA1.0 allows researchers, for the first time, to explore and make use of subnational, geocoded data on major disasters triggered by natural hazards (flooding, earthquake, landslide and meteorological hazards) since 1945 until 2020 in the hydrological catchment of the Red River in Vietnam and the Marikina Basin in the Philippines. FORINSEA1.0 also contains relevant subnational information on …

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Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel Jan 2022

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

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Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz Jan 2022

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

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Smart City Management Using Machine Learning Techniques, Mostafa Zaman Jan 2022

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …

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License Plate Image Quality Enhancement Utilizing Super Resolution Generative Adversarial Networks, Mark Moelter Jan 2022

License Plate Image Quality Enhancement Utilizing Super Resolution Generative Adversarial Networks, Mark Moelter

Electronic Theses and Dissertations

This thesis focuses primarily on enhancing the image quality of blurred license plates through the use of Super-Resolution Generative Adversarial Networks (SRGANs) [1]. We propose a synthetic dataset with SRGAN model to promote blurred image quality enhancement, and allow for model evaluation on a multitude of image input and output size combinations. SRGAN is mainly used for low-resolution image enhancement, but by heavily blurring the input images, the model is tested on its ability to blindly deblur and upsample images to the desired super-resolution (SR) size. The model enhances the image quality to nearly that of the reference images. The …

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"Demeter" Soil Monitoring System, Ryan Matthews, Rachel Rummer, Temilolu Fayomi, Alex Fuller Jan 2022

"Demeter" Soil Monitoring System, Ryan Matthews, Rachel Rummer, Temilolu Fayomi, Alex Fuller

Williams Honors College, Honors Research Projects

The purpose of this project is to develop a soil monitoring system that can remotely sense and relay soil conditions back to a user. The deMETER soil probe, Demeter is the Greek goddess of the harvest, is designed to aid hobbyist gardeners, small-scale farms, and nurseries to monitor their dynamic soil conditions and maximize their harvest. The probe is a self-powered system that can monitor the moisture and essential nutrients of the soil profile to determine which areas should receive water and fertilizer. This would significantly cut water and fertilizer waste. The solution will include an embedded system with sensors …

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Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev Jan 2022

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

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A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari Jan 2022

A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, the worldwide temperature increase has resulted in rapid deglaciation and a higher risk of glacier-related natural hazards such as flooding and debris flow. Due to the severity of these hazards, continuous observation and detailed analysis of glacier fluctuations are crucial. Many such analyses require an accurately delineated glacier boundary. However, the complexity and heterogeneity of glaciers, particularly debris-covered glaciers (DCGs), poses a challenge for glacier mapping when using conventional remote sensing or machine-learning techniques. Some examples exist about small-scale automated glacier mapping, but large or regional-scale mapping is challenging. Previously, a deep-learning-based approach named GlacierNet2 had been …

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Implementation And Usage Of Low-Cost Turbines For Power Generation In Water Networks, Luis Javier Ortiz Osornio Jan 2022

Implementation And Usage Of Low-Cost Turbines For Power Generation In Water Networks, Luis Javier Ortiz Osornio

All Graduate Theses, Dissertations, and Other Capstone Projects

The following APP is part of an investigation and development, carried out to design, and implement a hydroelectric turbine of horizontal axis, in order to generate electrical energy in rural areas, utilizing existing infrastructure or natural waterways such as irrigation canals, piping, rivers and streams. Every industrialized country, as well as, most of the developing nations, have a stake in agriculture and thus access to the infrastructure required for irrigation purposes. Artificial irrigation canals offer advantages such as a clean continuous flow, with the possibility of flow regulation: this together with their vast availability as agricultural infrastructure constitute the main …

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Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan Jan 2022

Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan

Electronic Theses and Dissertations

Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …

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Sentiment Without Sentiment Analysis: Using The Recommendation Outcome Of Steam Game Reviews As Sentiment Predictor, Anqi Zhang Jan 2022

Sentiment Without Sentiment Analysis: Using The Recommendation Outcome Of Steam Game Reviews As Sentiment Predictor, Anqi Zhang

Electronic Theses and Dissertations

This paper presents and explores a novel way to determine the sentiment of a Steam game review based on the predicted recommendation of the review, testing different regression models on a combination of Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) features. A dataset of Steam game reviews extracted from the Programming games genre consisting of 21 games along with other significant features such as the number of helpful likes on the recommendation, number of hours played, and others. Based on the features, they are grouped into three datasets: 1) either having keyword features only, 2) keyword features …

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Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo Jan 2022

Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

Pair programming is a model of collaborative learning. It has become a well-known pedagogical practice in teaching introductory programming courses because of its potential benefits to students. This study aims to investigate pair patterns in the context of pair program tracing and debugging to determine what characterizes collaboration and how these patterns relate to success, where success is measured in terms of performance task scores. This research used eye-tracking methodologies and techniques such as cross-recurrence quantification analysis. The potential indicators for pair success were used to create a model for predicting pair success. Findings suggest that it is possible to …

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The Uses Of A Dual-Band Corrugated Circularly Polarized Horn Antenna For 5g Systems, Chih-Kai Liu, Wei-Yuan Chiang, Pei-Zong Rao, Pei-Hsiu Hung, Shih-Hung Chen, Chiung-An Chen, Liang-Hung Wang, Patricia Angela R. Abu, Shih-Lun Chen Jan 2022

The Uses Of A Dual-Band Corrugated Circularly Polarized Horn Antenna For 5g Systems, Chih-Kai Liu, Wei-Yuan Chiang, Pei-Zong Rao, Pei-Hsiu Hung, Shih-Hung Chen, Chiung-An Chen, Liang-Hung Wang, Patricia Angela R. Abu, Shih-Lun Chen

Department of Information Systems & Computer Science Faculty Publications

This paper presents the development of a wide-beam width, dual-band, omnidirectional antenna for the mm-wave band used in 5G communication systems for indoor coverage. The 5G indoor environment includes features of wide space and short range. Additionally, it needs to function well under a variety of circumstances in order to carry out its diverse set of network applications. The waveguide antenna has been designed to be small enough to meet the requirements of mm-wave band and utilizes a corrugated horn to produce a wide beam width. Additionally, it is small enough to integrate with 5G communication products and is easy …

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Constraint-Aware And Efficiency-Aware Control Of Air-Path In Fuel Cell Vehicles, Eli Bacher-Chong Jan 2022

Constraint-Aware And Efficiency-Aware Control Of Air-Path In Fuel Cell Vehicles, Eli Bacher-Chong

Graduate College Dissertations and Theses

Fuel cell technology offers the potential for clean, efficient, robust energy productionfor both stationary and mobile applications. But without fast and robust control systems, fuel cells cannot hope to maintain real-life efficiencies near enough to their theoretical potential. This work studies control and constraint management techniques to regulate a nonlinear multivariable air-path system for a proton exchange membrane fuel cell (PEMFC). The control objectives are to avoid oxygen starvation, run at the maximum net efficiency, achieve fast tracking of air flow and pressure set-points, and be easy to calibrate. To operate at maximum efficiency, a set-point map is generated for …

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On The Enhancement Of Penetrating Radar Target Location Accuracy With Visual-Inertial Slam, Joshua Girard Jan 2022

On The Enhancement Of Penetrating Radar Target Location Accuracy With Visual-Inertial Slam, Joshua Girard

Graduate College Dissertations and Theses

This paper presents research concerning the use of visual-inertial Simultaneous Localization And Mapping (SLAM) algorithms to aid in Continuous Wave (CW) radar target mapping. SLAM is an established field in which radarhas been used to internally contribute to the localization algorithms. Instead, the application in this case is to use SLAM outputs to localize radar data and construct three-dimensional target maps which can be viewed in augmented reality. These methods are transferable to other types of radar units and sensors, but this paper presents the research showing how the methods can be applied to calculate depth efficiently with CW radar …

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On-Ice Detection, Classification, Localization And Tracking Of Anthropogenic Acoustic Sources With Machine Learning, Steven J. Whitaker Jan 2022

On-Ice Detection, Classification, Localization And Tracking Of Anthropogenic Acoustic Sources With Machine Learning, Steven J. Whitaker

Dissertations, Master's Theses and Master's Reports

Arctic acoustics have been of concern in recent years for the US navy. First-year ice is now the prevalent factor in ice coverage in the Arctic, which changes the previously understood acoustic properties. Due to the ice melting each year, anthropogenic sources in the Arctic region are more common: military exercises, shipping, and tourism. For the navy, it is of interest to detect, classify, localize, and track these sources to have situational awareness of these surroundings. Because the sources are on-water or on-ice, acoustic radiation propagates at a longer distance and so acoustics are the method by which the sources …

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Nonlinear Light - Matter Interactions Of Ultrafast High Intensity Laser Pulses, Henry Meyer Jan 2022

Nonlinear Light - Matter Interactions Of Ultrafast High Intensity Laser Pulses, Henry Meyer

Dissertations and Theses

This thesis focuses on the key nonlinear optical effects that arise from the interactions of intense ultrafast laser pulses with various states of matter. These interactions involve electronic and molecular states and yield new information on the underlying fundamental processes that govern the molecular world. Modern day lasers offer ultrashort pulses, high intensities, and complex polarizations and wavefronts. These extreme conditions have profound effect on the optical properties and behaviors of electronic and molecular states within a material. The changes in these mechanisms effect generation of nonlinear optics, such supercontinuum (SC), stimulated Raman (SRS), self-focusing and filamentation, conical emission (CE), …

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Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire Jan 2022

Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire

Graduate Theses, Dissertations, and Problem Reports

Facial recognition systems play a vital role in our everyday lives. We rely on this technology from menial tasks to issues as vital as national security. While strides have been made over the past ten years to improve facial recognition systems, morphed face images are a viable threat to the reliability of these systems. Morphed images are generated by combining the face images of two subjects. The resulting morphed face shares the likeness of the contributing subjects, confusing both humans and face verification algorithms. This vulnerability has grave consequences for facial recognition systems used on international borders or for law …

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Recent Advancements In Electrochemical Conversion Of Carbon Dioxide, Nandan Nag, Amit Kumar, Sumit Sharma, Sandeep Kumar, Amit K. Thakur Jan 2022

Recent Advancements In Electrochemical Conversion Of Carbon Dioxide, Nandan Nag, Amit Kumar, Sumit Sharma, Sandeep Kumar, Amit K. Thakur

Civil & Environmental Engineering Faculty Publications

Electrochemical reduction of carbon dioxide into eco-friendly and clean products is a promising approach to eradicate pollution. Although carbon dioxide emission is inhibited by the advent of renewable sources of energy, it is present in the atmosphere and needs to be cleaned. The reduction of carbon dioxide from atmospheric gases can be accomplished by its adsorption and subsequent transportation to electrolytic chambers, where it is reduced to hydrocarbons, organic acids or carbonates. This review focuses on developing a three compartment electrochemical cell to reduce carbon dioxide used as a catholyte. Various factors affecting the electrochemical reduction of carbon dioxide and …

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Cnn Based Sensor Fusion Method For Real-Time Autonomous Robotics Systems, Berat Yildiz, Aki̇f Durdu, Ahmet Kayabaşi, Mehmet Duramaz Jan 2022

Cnn Based Sensor Fusion Method For Real-Time Autonomous Robotics Systems, Berat Yildiz, Aki̇f Durdu, Ahmet Kayabaşi, Mehmet Duramaz

Turkish Journal of Electrical Engineering and Computer Sciences

Autonomous robotic systems (ARS) serve in many areas of daily life. The sensors have critical importance for these systems. The sensor data obtained from the environment should be as accurate and reliable as possible and correctly interpreted by the autonomous robot. Since sensors have advantages and disadvantages over each other they should be used together to reduce errors. In this study, Convolutional Neural Network (CNN) based sensor fusion was applied to ARS to contribute the autonomous driving. In a real-time application, a camera and LIDAR sensor were tested with these networks. The novelty of this work is that the uniquely …

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Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini Jan 2022

Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini

Theses and Dissertations--Electrical and Computer Engineering

Fault location remains an extremely pivotal feature of the electric power grid as it ensures efficient operation of the grid and prevents large downtimes during fault occurrences. This will ultimately enhance and increase the reliability of the system. Since the invention of the electric grid, many approaches to fault location have been studied and documented. These approaches are still effective and are implemented in present times, and as the power grid becomes even more broadened with new forms of energy generation, transmission, and distribution technologies, continued study on these methods is necessary. This thesis will focus on adopting the artificial …

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Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch Jan 2022

Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch

Masters Theses

"This research presents studies of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X's USim® software to quantify the nozzle's capabilities. A2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T's Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were …

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Techno-Economic Feasibility Of Electrifying Food Markets In Nigeria With Biogas Hybrid Mini-Grids, Demi Temitope Ogunwo Jan 2022

Techno-Economic Feasibility Of Electrifying Food Markets In Nigeria With Biogas Hybrid Mini-Grids, Demi Temitope Ogunwo

Cal Poly Humboldt theses and projects

This thesis explored the feasibility of electrifying a food market in an urban city in Nigeria with a hybrid biogas-powered mini-grid. Under the Energizing Economies Initiative of the Rural Electrification Agency of Nigeria, nine markets in the country currently receive constant access to electricity via hybrid mini-grid systems. As a majority of these systems are diesel-solar-battery systems, this thesis explored the use of biogas generators as a substitute for diesel generators in hybrid mini-grids for food markets. A fruit and vegetable market in Ketu, Lagos was used as a case study for the research. The research for this thesis was …

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Light Trapping Transparent Electrodes, Mengdi Sun Jan 2022

Light Trapping Transparent Electrodes, Mengdi Sun

Electronic Theses and Dissertations, 2020-2023

Transparent electrodes represent a critical component in a wide range of optoelectronic devices such as high-speed photodetectors and solar cells. Fundamentally, the presence of any conductive structures in the optical path leads to dissipation and reflection, which adversely affects device performance. Many different approaches have been attempted to minimize such shadowing losses, including the use of transparent conductive oxides (TCOs), metallic nanowire mesh grids, graphene-based contacts, and high-aspect ratio metallic wire arrays. In this dissertation I discuss a conceptually different approach to achieve transparent electrodes, which involves recapturing photons initially reflected by highly conductive electrode lines. To achieve this, light-redirecting …

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Patterned Liquid Crystal Devices For Near-Eye Displays, Kun Yin Jan 2022

Patterned Liquid Crystal Devices For Near-Eye Displays, Kun Yin

Electronic Theses and Dissertations, 2020-2023

As a promising next-generation display, augmented reality (AR) and virtual reality (VR) have shown attractive features and attracted broad interests from both academia and industry. Currently, these near-eye displays (NEDs) have enabled numerous applications, ranging from education, medical, entertainment, to engineering, with the help of compact and functional patterned liquid crystal (LC) devices. The interplay between LC patterns and NEDs stimulates the development of novel LC devices with unique surface alignments and volume structures, which in turn feedback to achieve more compact and versatile NEDs. This dissertation will focus on the patterned LC with applications in NEDs. Firstly, we propose …

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Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong Jan 2022

Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong

Electronic Theses and Dissertations, 2020-2023

Liquid crystal planar optics (LCPO) with versatile functionalities is emerging as a promising candidate for overcoming various challenges in near-eye displays, like augmented reality (AR) and virtual reality (VR), while maintaining a small form factor. This type of novel optical element exhibits unique properties, such as high efficiency, large angular/spectral bandwidths, polarization selectivity, and dynamic modulation. The basic molecular configuration of these novel reflective LCPO is analyzed, based on the simulation of molecular dynamics. In contrast to previously assumed planar-twist structure, our analysis predicts a slanted helix structure, which agrees with the measured results. The optical simulation model is established …

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