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At least 613 records · Page 34

New quantum oscillations in current driven small junctions

The response of current-biased Josephson and normal tunnel junctions (JJs and NTJs) such as those fabricated by Voss and Webb (1981) is predicted from a quantum-mechanical description based on the observation that the response of a current-driven open system is equivalent to that of a closed system subject to an external time-dependent voltage bias. Phenomena expected include voltage oscillations with no dc voltage applied, inverse Shapiro steps of dc voltage in the presence of microwave radiation, voltage oscillation in a JJ and an NTJ coupled by a capacitance to a current-biased junction, JJ voltage oscillation frequency = I/e rather than I/2e, and different NTJ resistance than in the voltage-driven case. The effects require approximate experimental parameter values Ic = 15 nA, C = 1 fF, and T much less than 0.4 K for JJs and Ic = a few nA, C = 1 fF, and R = 3 kiloohms for 100-microV inverse Shapiro steps at 10 GHz in NTJs.

Ben-Jacob, E.↗

Development of a high-efficiency motor/generator for flywheel energy storage

This study addresses the design changes and extensions necessary to construct and test a working prototype of a motor/generator for a magnetically suspended flywheel energy storage system. The brushless motor controller for the motor was specified and the electronic commutation arrangement designed. The laminations were redesigned and fabricated using laser machining. Flux density measurements were made and the results used to redesign the armature windings. A test rig was designed and built, and the motor/generator was installed and speed tested to 9000 rpm. Experimental methods of obtaining the machine voltage and torque constants Kv and Kt, obtaining the useful air-gap flux density, and characterizing the motor and other system components are described. The measured Kv and Kt were approximately 40 percent greater than predicted by theory and initial experiment.

Lashley, Christopher↗

Method and apparatus for I-V data acquisition from solar cells

A method and apparatus for logging current-voltage (I-V) characteristic d of a solar cell module (10) in two modes using a portable instrument. One mode controls the load current through a circuit (36) in 256 equal intervals while voltage is measured from open circuit to at least halfway into the knee of the curve and the other mode controls the load voltage through a circuit (34) in 256 equal intervals from the lowest voltage measurement possible (short circuit) to at least halfway into the knee of the curve, under control of a microcomputer (12). All measurements are packed by discarding each measurement that is within 0.5% of the value predicted from two previous measurements, except every ninth (9th) measurement which is retained. The remaining data is further packed into a memory block of a detachable storage medium (14) by recording the data points in sequence following a header containing data common to all points, with each point having the value of the controlled parameter recorded as the number of increments from the previous point recorded followed by the measured value. The detachable storage medium is preferably a solid state device for reliability, and is transferable to a playback terminal which unpacks the data for analysis and display.

Cole, Steven W.↗

Small Deflection Energy Analyzer for Energy and Angular Distributions

The development of the Small Deflection Energy Analyzer (SDEA) charged-particle spectrometer for energy and angle distributions responds to a longstanding need to measure the wind velocity vector in Earth s thermosphere, and to obtain the ion-drift vector in the ionosphere. The air and ions above 120 km are endowed with bulk velocities and temperatures just like air near the ground, but with separate spatial and temporal variations. It is important to understand these not only for study of the physics and chemistry of the Sun-Earth connection, but also for spacecraft orbit predictions, and communications through the ionosphere. The SDEA consists of a pair of parallel conducting plates separated by a small distance, with an entrance slit on one end, and an exit slit on the other. A voltage applied to these plates develops an electric field between the plates, and this field deflects ions passing through it. If an ion has too little energy, it will strike one of the plates. If it has too much, it will strike the back wall. An ion with the amount of energy being searched for will have its trajectory bent just enough to exit the back slit. The SDEA units are compact, rectangular, and operate with low voltages. The units can be built up into small arrays. These arrays could be used either to widen the field of view or to sharpen an existing one. This approach can also be used to obtain angular distributions in two planes simultaneously, thus cutting down the ion source power requirements in half. This geometry has enabled a new mass-spectrometer concept that can provide miniaturized mass spectrometers for use in industrial plants, air-pollution monitoring, and noxious-gas detection.

Herrero, Federico A.↗

20-kV GaN Switch Technology Demonstrated in High-Efficiency Medium-Voltage Power Module

GaN holds significant potential as a material for vertical p-n diodes, enabling the realization of devices with reverse breakdown voltages of 5 kV or higher. Carbon serves as the primary compensating dopant in the growth process, incorporated into GaN during metalorganic chemical vapor deposition (MOCVD) growth. The level of carbon incorporation depends on several factors, including growth rate, ammonia flow, temperature, pressure, and trimethylgallium (TMGa) flow. Through guided empirical modeling, the carbon incorporation in GaN growth could be predicted using a single parameter based on the ratio of ammonia flow to the growth rate. This model accurately predicts carbon concentrations ranging from 1x10 17 to 5x10 14 cm -3 while maximizing growth rates. Other extrinsic dopants have either been reduced below the threshold of consideration or modeled using similar single-parameter relationships. By identifying the dominant extrinsic dopants and accounting for them, an intrinsic defect with a concentration of 2.2x10 15 cm -3 was identified. By combining these relationships, growth conditions for n-GaN were optimized, resulting in electron concentrations as low as 1x10 15 cm -3 . Leveraging these techniques, p-n diodes were grown, achieving a reverse breakdown voltage as high as 3.1 kV.

36 MATERIALS SCIENCE↗

Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb -1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 10 14 1 MeV neutron-equivalent cm -2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation

47 OTHER INSTRUMENTATION↗

Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fluorine-Substituted Lithium Chloride Solid Electrolytes for High-Voltage All-Solid-State Lithium-Ion Batteries

Lithium ternary halides are promising solid electrolytes, owing to their high ionic conductivity and reasonably high oxidative and chemical stability. Recently, fluorine substitution in Li 3 MCl 6 has been suggested as a promising approach for further enhancing oxidation stability. Accordingly, this study outlines a material design strategy for F-substituted Li 3 MCl 6 through systematic theoretical analyses. Calculations reveal that the mixing limit of F in Li 3 MCl 6–x F x is in the range of 0.5–1.5, and the resulting Li 3 MCl 6–x F x phases can retain ionic conductivity above 1 mS/cm up to x = 1.0. Additionally, the calculations also predict that the formation of F-containing passivating phases could increase the oxidation potential for Li3MCl5F to ~6.3 V. The proposed material design strategy is validated through the synthesis of Li 3 YCl 5 F, which is confirmed to show both high ionic conductivity and enhanced oxidation stability. The design guidelines presented herein can accelerate the potential use of halide-based electrolyte chemistries in high-voltage all-solid-state batteries.

25 ENERGY STORAGE↗

Quantification of gas concentrations in NO/NO 2 /C 3 H 8 /NH 3 mixtures using machine learning

We employ machine learning to decode the composition of unknown gas mixtures from the output of an array of four electrochemical sensors. The sensors use metal oxide electrodes paired with a ceramic electrolyte, yttria-stabilized zirconia (YSZ), to produce voltage responses to the presence of gases in complex mixtures. The voltages from the sensor array serve as inputs to a machine learning pipeline which first carries out multi-class classification of mixtures into types based on which gases are present at non-zero concentrations, and subsequently predicts gas concentrations given the mixture type. Thus, our model is able to take a single reading from the sensor array in response to gas mixtures involving NO, NO 2 , C 3 H 8 , and NH 3 , and output a highly accurate prediction of which gases are present in the mixture, along with the concentrations of each constituent gas. Of note, our computational framework can be easily expanded to include additional gases and additional mixture types, allowing it to be used in numerous automotive, industrial and environmental monitoring settings.

47 OTHER INSTRUMENTATION↗

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric↗

Electrochemical Response of Alkaline Batteries Subject to Quasi-Static and Dynamic Loading

We report electrochemical changes were successfully monitored through the coupling of external loading, electrochemical impedance spectroscopy (EIS), and distribution of relaxation times (DRT) analysis. The development of the testing methods allows for detailed observation of changes due to mechanical loading and distinguishes responses between different cell geometries. Comparison of the force vs displacement, voltage vs displacement, and distribution of relaxation times plots to the different cell geometries display failure modes specific to geometry as well as the impact of different loading profiles. Numerical modeling confirmed the movement within individual cells and predicted locations with the most deformation based on the external loading condition applied. The results gathered from combining mechanical loading, electrochemical response, and numerical modeling, yield a viable approach to establishing an improved understanding of the effects of mechanical loading on the electrochemical response of multiple battery geometries and the methods herein may be extensible to additional battery chemistries.

25 ENERGY STORAGE↗

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗

Antenna admittance determination of electron density.

A circular-aperture flush-mounted antenna for which a theoretical description of the antenna-plasma interaction has been developed was used to obtain a comparison between theoretical and experimental antenna admittance in the presence of ionized boundary layers of low-collision frequency. The antenna was located in a flat-plate model which was in turn located in the expanding-flow environment of a reflected-shock tunnel. The electron-temperature and electron-density distributions in the plate boundary layer at the antenna location were independently measured using voltage-swept thin-wire Langmuir probes for one of the test conditions. The antenna admittance was measured using a four-probe microwave reflectometer and these measured values were found to be in good agreement with those predicted from the theory. Measurements were also performed with another type of circular-aperture antenna which did not satisfy all of the constraints of the theoretical model, although good agreement was obtained between the calculations and the experimental results.

Dunn, M. G.↗

Low-high junction theory applied to solar cells

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open-circuit voltage and improved radiation resistance. Several analytical models for open-circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero surface recombination velocity (SRV) case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells.

Godlewski, M. P.↗

LaF3 infrared detector

A class of infrared detectors is proposed, and experimental results are presented for a prototype device. The material used is LaF3, an ionic conductor with a capacitance that varies exponentially with temperature. The detectivity of a prototype detector is estimated from measured signal voltages and incident power, and a Johnson noise voltage is calculated from the measured resistance. At a modulation frequency of 20 Hz, the estimated detectivity is about 2 million cm/sq root Hz/W. For the parameters characterizing this device, the estimated detectivity is consistent with a theoretical prediction. The theory further predicts an optimum detectivity of about 1 billion cm/sq root Hz/W for much thinner devices than the prototypes.

Sher, A.↗

Charge and discharge profile

Some possible parameters which could be used to predict failures within packs of electrochemical cells based on measurements that are taken while the cells are cycling are discussed. Discharge and charge curves are presented and fitted to measure the efficiency of the cells in terms of voltage vs. time.

Mcdermott, P. P.↗

An Acoustic Charge Transport Imager for High Definition Television Applications: Low-Voltage SAW Amplifiers on Multilayer GaAs/ZnO Substrates

This thesis addresses the acoustoelectric issues concerning the amplification of surface acoustic waves (SAWs) and the reflection of SAWs from slanted reflector gratings on GaAs, with application to a novel acoustic charge transport (ACT) device architecture. First a simple model of the SAWAMP was developed, which was subsequently used to define the epitaxially grown material structure necessary to provide simultaneously high resistance and high electron mobility. In addition, a segmented SAWAMP structure was explored with line widths on the order of an acoustic wavelength. This resulted in the demonstration of SAWAMPS with an order of magnitude less voltage and power requirements than previously reported devices. A two-dimensional model was developed to explain the performance of devices with charge confinement layers less then 0.5 mm, which was experimentally verified. This model was extended to predict a greatly increased gain from the addition of a ZnO overlay. These overlays were experimentally attempted, but no working devices were reported due to process incompatibilities. In addition to the SAWAMP research, the reflection of SAWs from slanted gratings on GaAs was also studied and experimentally determined reflection coefficients for both 45 deg grooves and Al stripes on GaAs have been reported for the first time. The SAWAMp and reflector gratings were combined to investigate the integrated ring oscillator for application to the proposed ACT device and design parameters for this device have been provided.

Hunt, W. D.↗

Cathode Modeling of Solid-State Batteries

The search for safe, reliable, and compact high-capacity energy storage devices has led to increased interest in all-solid-state battery research. The use of solid electrolytes provides enhanced safety and durability due to their reduced flammability and increased mechanical strength compared to organic liquid electrolytes. Still, the use of solid electrolytes remains challenging. Computational modeling plays a substantial role in addressing these challenges. A particle dynamics electromechanical model for simulating electrochemical processes in a solid-state battery cathode will be presented. The model presents cathode microstructure at the particle level as a mixture of ionically conductive solid electrolyte particles, electrically conductive carbon additives, and cathodic reactant particles. After densification, the particle connectivity is analyzed to reconstruct the complex electric network connecting reactant particles with an anodic and cathodic current collectors through the electrolyte and carbon particles. The Kirchhoff’s matrix equation describing this electric network, is solved to obtain values of various critical parameters, such as the overall conductivity of the cathode for lithium ions and electrons, cathodic reactant material utilization, and the distribution of the electric current and voltages within the cathode. In addition, by representing the reactant particles as electrolyte or galvanic microcells governed by the Butler-Volmer electrochemical equation, the overall performance of battery cells during charge or discharge processes, respectively, can be predicted for a given cathodic powder composition. The presented model, executed on a high-performance computing architecture, essentially provides a valuable guidance in designing and developing future solid-state batteries.

solid-state battery↗