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Articles 1561 - 1590 of 8897

Full-Text Articles in Physical Sciences and Mathematics

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann Apr 2020

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …

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Artificial Intelligence Towards The Wireless Channel Modeling Communications In 5g, Saud Mobark Aldossari Apr 2020

Artificial Intelligence Towards The Wireless Channel Modeling Communications In 5g, Saud Mobark Aldossari

USF Tampa Graduate Theses and Dissertations

Channel prediction is a mathematical predicting of the natural propagation of the signal that helps the receiver to approximate the affected signal, which plays an important role in highly mobile or dynamic channels. The standard wireless communication channel modeling can be facilitated by either deterministic or stochastic channel methodologies. The deterministic approach is based on the electromagnetic theories and every single object in that environment has to be known in that propagation space and an example of this method is ray tracing. While the stochastic modeling method is based on measurements that involve statistical distributions of the channel parameters and …

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Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola Apr 2020

Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola

Faculty Publications

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …

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Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides Apr 2020

Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides

Faculty Publications

We present a novel light detection and ranging (LiDAR) polarimeter that enables measurement of 12 of 16 sample Mueller matrix elements in a single, 10 ns pulse. The new polarization state generator (PSG) leverages Kerr phase modulation in a birefringent optical fiber, creating a probe pulse characterized by temporally varying polarization. Theoretical expressions for the Polarization State Generator (PSG) Stokes vector are derived for birefringent walk-off and no walk-off and incorporated into a time-dependent polarimeter signal model employing multiple polarization state analyzers (PSA). Polarimeter modeling compares the Kerr effect and electro-optic phase modulator–based PSG using a single Polarization State Analyzer …

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Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge Apr 2020

Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge

Master's Theses

Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …

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Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne Apr 2020

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

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Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang Mar 2020

Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang

FIU Electronic Theses and Dissertations

Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …

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One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown Mar 2020

One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown

Theses and Dissertations

Blind deconvolution is used to complete missions to detect adversary assets in space and to defend the nation's assets. A new algorithm was developed to perform blind deconvolution for objects that are spatially separable using multiple frames of data. This new one-dimensional approach uses the expectation-maximization algorithm to blindly deconvolve spatially separable objects. This object separation reduces the size of the object matrix from an NxN matrix to two singular vectors of length N. With limited knowledge of the object and point spread function the one-dimensional algorithm successfully deconvolved the objects in both simulated and laboratory data.

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Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee Mar 2020

Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee

Theses and Dissertations

Remotely piloted aircraft (RPAs) cannot currently refuel during flight because the latency between the pilot and the aircraft is too great to safely perform aerial refueling maneuvers. However, an AAR system removes this limitation by allowing the tanker to directly control the RP A. The tanker quickly finding the relative position and orientation (pose) of the approaching aircraft is the first step to create an AAR system. Previous work at AFIT demonstrates that stereo camera systems provide robust pose estimation capability. This thesis first extends that work by examining the effects of the cameras' resolution on the quality of pose …

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Extracting Range Data From Images Using Focus Error, Erik M. Madden Mar 2020

Extracting Range Data From Images Using Focus Error, Erik M. Madden

Theses and Dissertations

Air-to-air refueling (AAR) has become a staple when performing long missions with aircraft. With modern technology, however, people have begun to research how to perform this task autonomously. Automated air-to-air refueling (A3R) is this exact concept. Combining many different systems, the idea is to allow computers on the aircraft to link up via the refueling boom, refuel, and detach before resuming pilot control. This document lays out one of the systems that is needed to perform A3R, namely, the system that extracts range data. While stereo cameras perform such tasks, there is interest in finding other ways of accomplishing the …

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Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham Mar 2020

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

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Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui Mar 2020

Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui

Theses and Dissertations

Currently, Low-Rate Wireless Personal Area Networks (LR-WPAN) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard are at risk due to open-source tools which allow bad actors to exploit unauthorized network access through various cyberattacks by falsifying bit-level credentials. This research investigates implementing a Radio Frequency (RF) air monitor to perform Near RealTime (NRT) discrimination of Zigbee devices using the IEEE 802.15.4 standard. The air monitor employed a Multiple Discriminant Analysis/Euclidean Distance classifier to discriminate Zigbee devices based upon Constellation-Based Distinct Native Attribute (CB-DNA) fingerprints. Through the use of CB-DNA fingerprints, Physical Layer (PHY) characteristics unique to …

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Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi Mar 2020

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

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Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev Mar 2020

Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev

Theses and Dissertations

Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …

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Fiber-Optic Micro-Probes For Measuring Acidity Level, Temperature, And Antigens, Yinfa Ma, Honglan Shi, Qingbo Yang, Hai Xiao Mar 2020

Fiber-Optic Micro-Probes For Measuring Acidity Level, Temperature, And Antigens, Yinfa Ma, Honglan Shi, Qingbo Yang, Hai Xiao

Chemistry Faculty Research & Creative Works

A pH micro-probe, a temperature micro-probe, and an immuno-based micro-probe each include a shaft for transmuting an input light signal and a tip for inserting into a cell or other substance for measuring pH, temperature, and/or antigens. The pH micro-probe and the temperature micro-probe each include a luminescent material positioned on the tip of the micro-probe. The light signal excites the luminescent material so that the luminescent material emits a luminescent light signal. The luminescent light signal has a property value dependent on the pH or temperature being measured and reflects back through the shaft for being measured by a …

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Syllabus Ee330 Electromagnetics, Nicholas Madamopoulos Mar 2020

Syllabus Ee330 Electromagnetics, Nicholas Madamopoulos

Open Educational Resources

Concepts covered in the undergraduate electrical engineering class of electromagnetics

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Infrared-Active Phonon Modes In Single-Crystal Thorium Dioxide And Uranium Dioxide, Sean Knight, Rafal Korlacki, Christina Dugan, James C. Petrosky, Alyssa Lynn Mock, Peter A. Dowben, J. Matthew Mann, Martin M. Kimani, Mathias Schubert Mar 2020

Infrared-Active Phonon Modes In Single-Crystal Thorium Dioxide And Uranium Dioxide, Sean Knight, Rafal Korlacki, Christina Dugan, James C. Petrosky, Alyssa Lynn Mock, Peter A. Dowben, J. Matthew Mann, Martin M. Kimani, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

The infrared-active phonon modes, in single-crystal samples of thorium dioxide (ThO2) and uranium dioxide (UO2), were investigated using spectroscopic ellipsometry and compared with density functional theory. Both ThO2 and UO2 are found to have one infrared-active phonon mode pair [consisting of one transverse optic (TO) and one associated longitudinal optic (LO) mode], which is responsible for the dominant features in the ellipsometric data. At room temperature, our results for the mode pair’s resonant frequencies and broadening parameters are comparable with previous reflectance spectroscopy characterizations and density functional theory predictions. For ThO2, our …

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Deal: Differentially Private Auction For Blockchain Based Microgrids Energy Trading, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen Mar 2020

Deal: Differentially Private Auction For Blockchain Based Microgrids Energy Trading, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen

Publications

Modern smart homes are being equipped with certain renewable energy resources that can produce their own electric energy. From time to time, these smart homes or microgrids are also capable of supplying energy to other houses, buildings, or energy grid in the time of available self-produced renewable energy. Therefore, researches have been carried out to develop optimal trading strategies, and many recent technologies are also being used in combination with microgrids. One such technology is blockchain, which works over decentralized distributed ledger. In this paper, we develop a blockchain based approach for microgrid energy auction. To make this auction more …

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Differential Privacy Techniques For Cyber Physical Systems: A Survey, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen Mar 2020

Differential Privacy Techniques For Cyber Physical Systems: A Survey, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen

Publications

Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT).With the provision of CPSs, the security and privacy threats associated to these systems are also increasing. Passive attacks are being used by intruders to get access to private information of CPSs. In order to make CPSs data more secure, certain privacy preservation strategies such as encryption, and k-anonymity have been presented in the past. However, with the advances in CPSs architecture, these techniques also need certain modifications. Meanwhile, differential privacy emerged as an efficient technique to protect CPSs …

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Measurement Of The 160Gd(P,N)160Tb Excitation Function From 4 18 Mev, Using A Stacked Foil Technique, Ryan K. Chapman Mar 2020

Measurement Of The 160Gd(P,N)160Tb Excitation Function From 4 18 Mev, Using A Stacked Foil Technique, Ryan K. Chapman

Theses and Dissertations

A stack of thin Gd, Ti, and Cu foils were irradiated with an 18 MeV proton beam at Lawrence-Berkeley National Laboratory's 88-Inch Cyclotron to investigate the 160Gd(p,n)160Tb nuclear reaction for nuclear forensics applications. This experiment will improve knowledge of 160Tb production rates, allowing 160Tb to be efficiently created in a foil stack consisting of other proton induced isotopes for forensics applications. A set of 15 measured cross sections between 4-18 MeV for 160Gd(p,n)160Tb were obtained using a stacked foil technique. The foil stack consisted of one stainless steel, one iron, fifteen gadolinium, …

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Simulation Of Sporadic-E Parameters Using Phase Screen Method, Daniel W. Stambovsky Mar 2020

Simulation Of Sporadic-E Parameters Using Phase Screen Method, Daniel W. Stambovsky

Theses and Dissertations

A phase screen simulation experiment is designed and implemented to model radio occultation through sporadic-E ionospheric disturbances between a GPS transmitter operating at the L1 frequency and a second receiving satellite in low earth orbit (LEO). Simulations were made to test the linear relationship between plasma intensity and scintillation S4 index both posited (Arras and Wickert, 2018) and contended (Gooch et al., 2020) in previous literature. Results brought into question both the linear relationship and the use of S4 as a whole and an alternate metric was sought.

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Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl Mar 2020

Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl

Theses and Dissertations

The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …

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Detection Of Reconnection Signatures In Solar Flares, Taylor R. Whitney Mar 2020

Detection Of Reconnection Signatures In Solar Flares, Taylor R. Whitney

Theses and Dissertations

Solar flare forecasting is limited by the current understanding of mechanisms that govern magnetic reconnection, the main physical phenomenon associated with these events. As a result, forecasting relies mainly on climatological correlations to historical events rather than the underlying physics principles. Solar physics models place the neutral point of the reconnection event in the solar corona. Correspondingly, studies of photospheric magnetic fields indicate changes during solar flares -- particularly in relation to the field helicity -- on the solar surface as a result of the associated magnetic reconnection. This study utilizes data from the Solar Dynamics Observatory (SDO) Helioseismic and …

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Synthesizing General Electromagnetic Partially Coherent Sources From Random, Correlated Complex Screens, Milo W. Hyde Iv Mar 2020

Synthesizing General Electromagnetic Partially Coherent Sources From Random, Correlated Complex Screens, Milo W. Hyde Iv

Faculty Publications

We present a method to generate any genuine electromagnetic partially coherent source (PCS) from correlated, stochastic complex screens. The method described here can be directly implemented on existing spatial-light-modulator-based vector beam generators and can be used in any application which utilizes electromagnetic PCSs. Our method is based on the genuine cross-spectral density matrix criterion. Applying that criterion, we show that stochastic vector field realizations (corresponding to a desired electromagnetic PCS) can be generated by passing correlated Gaussian random numbers through “filters” with space-variant transfer functions. We include step-by-step instructions on how to generate the electromagnetic PCS field realizations. As an …

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Optimizing Llrf Parameters In The Electron-Ion Collider, William M. Bjorndahl Mar 2020

Optimizing Llrf Parameters In The Electron-Ion Collider, William M. Bjorndahl

Physics

To improve particle interaction in the future Electron-Ion Collider (EIC), we investigated different feedback implementations to control the accelerating voltage and examined the power and beam phase for each instance. Using MATLAB, we studied three feedback mechanisms: Direct, One Turn, and Feedforward. Enacting feedforward yielded the best performance. To minimize the klystron power consumption, we analyzed different Low-Level Radio Frequency (LLRF) parameters such as detuning. Combining theory and simulated results, we found the optimal detuning value that minimizes klystron power consumption.

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Research Progresses In Ni-Co-Mn/Al Ternary Concentration Gradient Cathode Materials For Li-Ion Batteries, Chun-Fang Zhang, Wen-Gao Zhao, Shi-Yao Zheng, Yi-Xiao Li, Zheng-Liang Gong, Zhong-Ru Zhang, Yong Yang Feb 2020

Research Progresses In Ni-Co-Mn/Al Ternary Concentration Gradient Cathode Materials For Li-Ion Batteries, Chun-Fang Zhang, Wen-Gao Zhao, Shi-Yao Zheng, Yi-Xiao Li, Zheng-Liang Gong, Zhong-Ru Zhang, Yong Yang

Journal of Electrochemistry

Nickel-rich ternary materials with large reversible capacity as well as high operating voltage are considered as the most promising candidate for next generation lithium-ion batteries (LIBs). However, the inferior cycle stability and thermal stability have limited their widely commercial applications. Concentration gradient design of Ni-Co-Mn/Al ternary concentration gradient materials have been extensively studied in the past decade, which can ensure high cycle capacity while maintaining excellent cycle stability. In this paper, the latest research progresses in Ni-Co-Mn/Al ternary concentration gradient materials for LIBs are reviewed. Firstly, we summarize the different synthesis methods of ternary concentration-gradient materials, especially focusing on the …

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Research Progresses In Polymeric Proton Exchange Membranes For Fuel Cells, Xu-Po Liu, Yun-Feng Zhang, Shao-Feng Deng, De-Li Wang, Han-Song Cheng Feb 2020

Research Progresses In Polymeric Proton Exchange Membranes For Fuel Cells, Xu-Po Liu, Yun-Feng Zhang, Shao-Feng Deng, De-Li Wang, Han-Song Cheng

Journal of Electrochemistry

Proton exchange membrane (PEM) is one of the key components in PEM fuel cells, which possesses the function of separating the cathode and anode, affording proton transport channels and preventing fuel permeability. The property of PEM significantly influences the performance and service life of fuel cells. Nowadays, the commercially used Nafion membranes have the shortcomings of serious fuel permeability, low proton conductivity at elevated temperature and high price, which limits the rapid development of PEM fuel cells. Therefore, it seems to be urgent to develop novel PEMs with low cost and good comprehensive properties. Polymeric proton exchange membrane is an …

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Electrochemical Preparations And Applications Of Nano-Catalysts With High-Index Facets, Chi Xiao, Na Tian, Zhi-You Zhou, Shi-Gang Sun Feb 2020

Electrochemical Preparations And Applications Of Nano-Catalysts With High-Index Facets, Chi Xiao, Na Tian, Zhi-You Zhou, Shi-Gang Sun

Journal of Electrochemistry

The performance of catalysts highly depends on their surface structure and composition. Nanocrystals bounded by high-index facets usually exhibit high catalytic activity due to their high-density low-coordinated step atoms with high reactivity. In this paper, we have reviewed the preparations of noble metals (e.g., Pt, Pd and Rh) nanocatalysts with high-index facets by electrochemical square-wave potential method developed in our group. The square-wave potential method includes a nucleation procedure to generate nuclei, followed by a square-wave potential procedure for a certain period of time for the growth of nuclei into nanocrystals. The formation mechanism of high-index facets is also discussed. …

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Structures And Electrochemical Properties Of Sn-Cl Co-Doped Li2Mno3 As Positive Materials For Lithium Ion Batteries, Fei Wang, Huan-Huan Zhai, Du-Dan Wang, Yu-Peng Li, Kang-Hua Chen Feb 2020

Structures And Electrochemical Properties Of Sn-Cl Co-Doped Li2Mno3 As Positive Materials For Lithium Ion Batteries, Fei Wang, Huan-Huan Zhai, Du-Dan Wang, Yu-Peng Li, Kang-Hua Chen

Journal of Electrochemistry

Positive material Li2MnO3 shows the highest ratio of lithium to manganese among lithium-rich materials and exhibites the theoretical capacity up to 458 mAh·g-1, making it one of the most promising cathode materials. However, this material has the intrinsic low electrical conductivity and poor cycle stability. In this paper, Li2MnO3, the lithium-rich positive material, was prepared by sol-gel method using acetate as raw material and citric acid as a complexing agent. By using SnC2O4 as a tin source, Sn4+ instead of Mn4+ was introduced to obtain the …

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Investigating The Solution Properties Of Population Model Of Cross-Diffusion Model With Double Nonlinearity And With Variable Density, Dildora Kabilovna Muhamediyeva Feb 2020

Investigating The Solution Properties Of Population Model Of Cross-Diffusion Model With Double Nonlinearity And With Variable Density, Dildora Kabilovna Muhamediyeva

Chemical Technology, Control and Management

The models of two competing populations with double nonlinear diffusion and three types of functional dependencies are considered. The first dependence corresponds to the Malthusian type, the second to the Verhühlst type (logistic population), and the third to Olli-type populations. A common element of this kind of description is the presence of a linear source. Nonlinear sinks are also present in descriptions of populations of the Verhulst and Ollie type. Suitable initial approximations for a rapidly converging iterative process are proposed. Based on a self-similar analysis and comparison of the solutions of the Cauchy problem in the domain for an …

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