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Electromagnetics and Photonics

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2019

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Articles 1 - 25 of 25

Full-Text Articles in Electrical and Computer Engineering

Generating Electromagnetic Nonuniformly Correlated Beams, Milo W. Hyde Iv, Xifeng Xiao, David G. Voelz Dec 2019

Generating Electromagnetic Nonuniformly Correlated Beams, Milo W. Hyde Iv, Xifeng Xiao, David G. Voelz

Faculty Publications

We develop a method to generate electromagnetic nonuniformly correlated (ENUC) sources from vector Gaussian Schell-model (GSM) beams. Having spatially varying correlation properties, ENUC sources are more difficult to synthesize than their Schell-model counterparts (which can be generated by filtering circular complex Gaussian random numbers) and, in past work, have only been realized using Cholesky decomposition—a computationally intensive procedure. Here we transform electromagnetic GSM field instances directly into ENUC instances, thereby avoiding computing Cholesky factors resulting in significant savings in time and computing resources. We validate our method by generating (via simulation) an ENUC beam with desired parameters. We find the …

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Measurement Of Electron Density And Temperature From Laser-Induced Nitrogen Plasma At Elevated Pressure (1–6 Bar), Ashwin P. Rao [*], Mark Gragston, Anil K. Patnaik, Paul S. Hsu, Michael B. Shattan Nov 2019

Measurement Of Electron Density And Temperature From Laser-Induced Nitrogen Plasma At Elevated Pressure (1–6 Bar), Ashwin P. Rao [*], Mark Gragston, Anil K. Patnaik, Paul S. Hsu, Michael B. Shattan

Faculty Publications

Laser-induced plasmas experience Stark broadening and shifts of spectral lines carrying spectral signatures of plasma properties. In this paper, we report time-resolved Stark broadening measurements of a nitrogen triplet emission line at 1–6 bar ambient pressure in a pure nitrogen cell. Electron densities are calculated using the Stark broadening for different pressure conditions, which are shown to linearly increase with pressure. Additionally, using a Boltzmann fit for the triplet, the electron temperature is calculated and shown to decrease with increasing pressure. The rate of plasma cooling is observed to increase with pressure. The reported Stark broadening based plasma diagnostics in …

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Nonlinearities And Carrier Dynamics In Refractory Plasmonic Tin Thin Films, Heather George, Jennifer Reed, Manuel R. Ferdinandus, Clayton Devault, Alexei Lagutchev, Augustine Urbas, Theodore B. Norris, Vladimir M. Shalaev, Alexandra Boltasseva, Nathaniel Kinsey Oct 2019

Nonlinearities And Carrier Dynamics In Refractory Plasmonic Tin Thin Films, Heather George, Jennifer Reed, Manuel R. Ferdinandus, Clayton Devault, Alexei Lagutchev, Augustine Urbas, Theodore B. Norris, Vladimir M. Shalaev, Alexandra Boltasseva, Nathaniel Kinsey

Faculty Publications

Titanium nitride is widely used in plasmonic applications, due to its robustness and optical properties which resemble those of gold. Despite this interest, the nonlinear properties have only recently begun to be investigated. In this work, beam deflection and non-degenerate femtosecond pump-probe spectroscopy (800 nm pump and 650 nm probe) were used to measure the real and imaginary transient nonlinear response of 30-nm-thick TiN films on sapphire and fused silica in the metallic region governed by Fermi-smearing nonlinearities. In contrast to other metals, it is found that TiN exhibits non-instantaneous positive refraction and reverse saturable absorption whose relaxation is dominated …

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Discontinuous Galerkin Vs. Ie Method For Electromagnetic Scattering From Composite Metallic And Dielectric Structures, Y.-Y. Zhu, Q.-M. Cai, R. Zhang, X. Cao, Y.-W. Zhao, B. Gao, Jun Fan Sep 2019

Discontinuous Galerkin Vs. Ie Method For Electromagnetic Scattering From Composite Metallic And Dielectric Structures, Y.-Y. Zhu, Q.-M. Cai, R. Zhang, X. Cao, Y.-W. Zhao, B. Gao, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an efficient volume surface integral equation (VSIE) method with nonconformal discretization is developed for the analysis of electromagnetic scattering from composite metallic and dielectric (CMD) structures. This VSIE scheme utilizes curved tetrahedral (triangular) elements for volume (surface) modeling and the associated CRWG (CSWG) basis functions for volume current (surface) current modeling. Further, a discontinuous Galerkin (DG) volume integral equation (VIE) method and a DG surface integral equation (SIE) approach are adopted for dielectric and metallic parts, respectively, which allow both conformal and nonconformal volume/surface discretization improving meshing flexibility considerably. Numerical results are provided to demonstrate the accuracy, …

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Near-Field Effects On Partially Coherent Light Scattered By An Aperture, Milo W. Hyde Iv, Michael J. Havrilla Aug 2019

Near-Field Effects On Partially Coherent Light Scattered By An Aperture, Milo W. Hyde Iv, Michael J. Havrilla

Faculty Publications

We investigate how the near field affects partially coherent light scattered from an aperture in an opaque screen. Prior work on this subject has focused on the role of surface plasmons, and how they affect spatial coherence is well documented. Here, we consider other near-field effects that might impact spatial coherence. We do this by examining the statistics of the near-zone field scattered from an aperture in a perfect electric conductor plane—a structure that does not support surface plasmons. We derive the near-field statistics (in particular, cross-spectral density functions) by applying electromagnetic equivalence theorems and the Method of Moments. We …

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3d Plasmonic Design Approach For Efficient Transmissive Huygens Metasurfaces, Bryan M. Adomanis, D. Bruce Burckel, Michael A. Marciniak Jul 2019

3d Plasmonic Design Approach For Efficient Transmissive Huygens Metasurfaces, Bryan M. Adomanis, D. Bruce Burckel, Michael A. Marciniak

Faculty Publications

In this paper we present a design concept for 3D plasmonic scatterers as high- efficiency transmissive metasurface (MS) building blocks. A genetic algorithm (GA) routine partitions the faces of the walls inside an open cavity into a M x N grid of voxels which can be either covered with metal or left bare, and optimizes the distribution of metal coverage needed to generate electric and magnetic modes of equal strength with a targeted phase delay (Φt) at the design wavelength. Even though the electric and magnetic modes can be more complicated than typical low order modes, with their spectral overlap …

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M2 Factor Of A Vector Schell-Model Beam, Milo W. Hyde Iv, Mark F. Spencer Jul 2019

M2 Factor Of A Vector Schell-Model Beam, Milo W. Hyde Iv, Mark F. Spencer

Faculty Publications

Extending existing scalar Schell-model source work, we derive the M2 factor for a general electromagnetic or vector Schell-model source to assess beam quality. In particular, we compute the M2 factors for two vector Schell-model sources found in the literature. We then describe how to synthesize vector Schell-model beams in terms of specified, desired M2 and present Monte Carlo simulation results to validate our analysis.

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Urban Underground Infrastructure Monitoring Iot: The Path Loss Analysis, Abdul Salam, Syed Shah Apr 2019

Urban Underground Infrastructure Monitoring Iot: The Path Loss Analysis, Abdul Salam, Syed Shah

Faculty Publications

The extra quantities of wastewater entering the pipes can cause backups that result in sanitary sewer overflows. Urban underground infrastructure monitoring is important for controlling the flow of extraneous water into the pipelines. By combining the wireless underground communications and sensor solutions, the urban underground IoT applications such as real time wastewater and storm water overflow monitoring can be developed. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. It has been shown that the communication range of up to 4 kilometers can be achieved from an underground …

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An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam Apr 2019

An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam

Faculty Publications

Underground sensing and propagation of Signals in the Soil (SitS) medium is an electromagnetic issue. The path loss prediction with higher accuracy is an open research subject in digital agriculture monitoring applications for sensing and communications. The statistical data are predominantly derived from site-specific empirical measurements, which is considered an impediment to universal application. Nevertheless, in the existing literature, statistical approaches have been applied to the SitS channel modeling, where impulse response analysis and the Friis open space transmission formula are employed as the channel modeling tool in different soil types under varying soil moisture conditions at diverse communication distances …

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Ultrashort Cross-Correlation In The Middle Infrared: A Novel Approach To Standoff Detection, William Conner Thomas Apr 2019

Ultrashort Cross-Correlation In The Middle Infrared: A Novel Approach To Standoff Detection, William Conner Thomas

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Lasers are a common tool in standoff detection because of their small divergence, large amount of power, and multiple wavelengths available for optical interaction. Optical signatures of targets can be composed of but are not limited to absorption, fluorescence, backscatter, polarization manipulation, and plasma spectra. This work was an investigation of a new signature phenomenon: Dispersion of middle infrared ultrashort laser pulses through gas and vapor phase molecules. Vibrational and rovibrational absorption lines of molecular species affect the spectral phase and spectral amplitude of ultrashort light pulses leading an inititally gaussian temporal profile to become distorted. This dissertation is an …

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Modeling Land Subsidence Using Insar And Airborne Electromagnetic Data, Ryan G. Smith, R. Knight Apr 2019

Modeling Land Subsidence Using Insar And Airborne Electromagnetic Data, Ryan G. Smith, R. Knight

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Land subsidence as a result of groundwater overpumping in the San Joaquin Valley, California, is associated with the loss of groundwater storage and aquifer contamination. Although the physical processes governing land subsidence are well understood, building predictive models of subsidence is challenging because so much subsurface information is required to do so accurately. For the first time, we integrate airborne electromagnetic data, representing the subsurface, with subsidence data, mapped by interferometric synthetic aperture radar (InSAR), to model deformation. By combining both data sets, we are able to solve for hydrologic and geophysical properties of the subsurface to effectively model the …

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Fabrication Of Biased-Magnetorheological Elastomers (B-Mre) Based On Magnetized Ferromagnetic Particles, Choonghan Lee, Woosoon Yim Mar 2019

Fabrication Of Biased-Magnetorheological Elastomers (B-Mre) Based On Magnetized Ferromagnetic Particles, Choonghan Lee, Woosoon Yim

Mechanical Engineering Faculty Research

Magnetorheological elastomers (MREs), like MR fluids, exploit magnetic forces between ferromagnetic particles to produce a material with instantaneously adjustable properties of stiffness and damping with external magnetic fields. In MREs, the particles are a part of a structured elastomer matrix, and an external magnetic field is applied to achieve an instantaneous change of stiffness due to magnetic forces between particles. A drawback of conventional MREs is its inability of softening (reduce stiffness) under an external field. Many engineering applications need an instant change of its stiffness in both directions, which requires a magnetic bias embedded in the MRE. One way …

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Low-Loss, Compact, Spot-Size-Converter Based Vertical Couplers For Photonic Integrated Circuits, Praveen K.J. Singaravelu, G.C.R. Devarapu, Sebastian A. Schulz, Quentin Wilmart, Stéphane Malhouitre, Ségolène Olivier, Liam O’Faolain Mar 2019

Low-Loss, Compact, Spot-Size-Converter Based Vertical Couplers For Photonic Integrated Circuits, Praveen K.J. Singaravelu, G.C.R. Devarapu, Sebastian A. Schulz, Quentin Wilmart, Stéphane Malhouitre, Ségolène Olivier, Liam O’Faolain

Cappa Publications

In recent years, the monolithic integration of new materials such as SiN, Ge and LiNbO3 on silicon (Si) has become important to the Si photonics community due to the possibility of combining the advantages of both material systems. However, efficient coupling between the two different layers is challenging. In this work, we present a spot size converter based on a two-tier taper structure to couple the optical mode adiabatically between Si and SiN. The fabricated devices show a coupling loss as low as 0.058 dB  ±  0.01 dB per transition at 1525 nm. The low coupling loss between the Si …

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A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari Mar 2019

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

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A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak Feb 2019

A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak

Faculty Publications

The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …

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Electrochromic Semiconductors As Colorimetric Sers Substrates With High Reproducibility And Renewability, Shan Cong, Zhen Wang, Wenbin Gong, Zhigang Chen, Weibang Lu, John R. Lombardi, Zhigang Zhao Feb 2019

Electrochromic Semiconductors As Colorimetric Sers Substrates With High Reproducibility And Renewability, Shan Cong, Zhen Wang, Wenbin Gong, Zhigang Chen, Weibang Lu, John R. Lombardi, Zhigang Zhao

Publications and Research

Electrochromic technology has been actively researched for displays, adjustable mirrors, smart windows, and other cutting-edge applications. However, it has never been proposed to overcome the critical problems in the field of surface-enhanced Raman scattering (SERS). Herein, we demonstrate a generic electrochromic strategy for ensuring the reproducibility and renewability of SERS substrates, which are both scientifically and technically important due to the great need for quantitative analysis, standardized production and low cost in SERS. This color-changing strategy is based on a unique quantitative relationship between the SERS signal amplification and the coloration degree within a certain range, in which the SERS …

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Mid-Infrared Optical Sensing Using Sub-Wavelength Gratings, Brian Hogan, Liam Lewis, Michael Mcauliffe, Stephen P. Hegarty Feb 2019

Mid-Infrared Optical Sensing Using Sub-Wavelength Gratings, Brian Hogan, Liam Lewis, Michael Mcauliffe, Stephen P. Hegarty

Cappa Publications

Optical sensing has shown great potential for both quantitative and qualitative analysis of compounds. In particular sensors which are capable of detecting changes in refractive index at a surface as well as in bulk material have received much attention. Much of the recent research has focused on developing technologies that enable such sensors to be deployed in an integrated photonic device. In this work we demonstrate experimentally, using a sub-wavelength grating the detection of ethanol in aqueous solution by interrogating its large absorption band at 9.54 µm. Theoretical investigation of the operating principle of our grating sensor shows that in …

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Modeling Land Subsidence Using Insar And Airborne Electromagnetic Data: Dataset, Ryan G. Smith, R. Knight Jan 2019

Modeling Land Subsidence Using Insar And Airborne Electromagnetic Data: Dataset, Ryan G. Smith, R. Knight

Research Data

Supporting dataset for article published in Water Resources Research, Volume 55, Issue 4, pages 2801-2819

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Theoretical Analysis Of A Volume Holographic Lens Using Matlab, Sanjay Keshri, Kevin Murphy, Izabela Naydenova, Suzanne Martin Jan 2019

Theoretical Analysis Of A Volume Holographic Lens Using Matlab, Sanjay Keshri, Kevin Murphy, Izabela Naydenova, Suzanne Martin

Conference Papers

Volume holographic lenses have great potential for different types of applications requiring light redirection and beam shaping such as solar light collection and LED light management. For lighting applications using LEDs, it is essential to make a highly efficient optical element to be placed in front of the LED in order to decrease energy losses. For that reason, a careful theoretical analysis of the properties and operation regime of the lens must be carried out at the design stage. The characteristics of focusing Holographic Optical Elements (HOE) depend on many factors including their thickness, spatial frequency, the angular range of …

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Sensing Of Multiple Parameters With Whispering Gallery Mode Optical Fiber Micro-Resonators, Arun Kumar Mallik Dr, Vishnan Kavungal, Gerald Farrell, Yuliya Semenova Jan 2019

Sensing Of Multiple Parameters With Whispering Gallery Mode Optical Fiber Micro-Resonators, Arun Kumar Mallik Dr, Vishnan Kavungal, Gerald Farrell, Yuliya Semenova

Conference Papers

Monitoring of multiple physical parameters, such as humidity, temperature, strain, concentrations of certain chemicals or gases in various environments is of great importance in many industrial applications both for minimizing adverse effects on human health as well as for maintaining production levels and quality of products. In this paper we demonstrate two different approaches to the design of multi-parametric sensors using coupled whispering gallery mode (WGM) optical fiber micro-resonators. In the first approach, a small array of micro-resonators is coupled to a single fiber taper, while in the second approach each of the micro-resonators within an array is coupled to …

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Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari Jan 2019

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …

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Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari Jan 2019

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

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A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun Jan 2019

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

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Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai Jan 2019

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

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Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos Jan 2019

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

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