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At least 559 records · Page 31

Trap characterization of high-growth-rate laser-assisted MOCVD GaN

A detailed study comparing defect incorporation between laser-assisted metal-organic chemical vapor deposition (MOCVD)-grown GaN and conventional low- and high-growth-rate MOCVD GaN was conducted. Using deep-level transient and optical spectroscopy, traps throughout the bandgap were characterized where traps were found at EC-0.25 eV, EC-0.57 eV, EC-0.72 eV, EC-0.9 eV, EC-1.35 eV, EC-2.6 eV, and EC-3.28 eV in all three samples. This indicates no new traps were observed in the laser-assisted MOCVD GaN sample. Overall, the trap concentrations in the laser-assisted MOCVD sample were ∼2× higher than the optimal low-growth-rate sample, but this is primarily due to the increase in gallium vacancy EC-2.6 eV and carbon-related EC-3.28 eV trap concentrations. The EC-0.9 eV trap concentration was ∼2× higher in the laser-assisted sample, so proton irradiation experiments were conducted to identify the physical source of this level. The results indicated this was a native point defect likely related to gallium interstitials. Overall, this study shows that the laser-assisted MOCVD growth method is promising for future thick, high-quality GaN epilayers after further growth optimizations.

Physics↗

Towards an Energy Future with Ubiquitous Electric Vehicles: Barriers and Opportunities

The electrification of personal transportation holds great potential for lowering greenhouse gas emissions and reducing climate change. The promise of electric vehicles (EVs) to serve these goals has resulted in a broad range of supporting policies aimed at encouraging widespread EV adoption at both the state and federal levels in the United States and around the world. While the EV revolution and prospects of a world with ubiquitous EVs are impacting various industries and many aspects of daily life, strategic interactions between the power grid and EVs are crucial for a successful energy transition. However, managing the interplay between EVs and the power grid remains a challenge. Motivated by that tension, this paper surveys a variety of solutions, policies, and incentives that are focused on effectively managing EV charging behaviors. The paper’s objective is to explore these tools to ensure that EV owners have ultimate control over their personal vehicles while simultaneously allowing the power grid to mitigate adverse network impacts. Furthermore, this paper examines the role of charging infrastructure technology and its strategic placement in facilitating the seamless integration of EVs into the grid. Additionally, the paper highlights financial mechanisms associated with EV integration and discusses the consequences of these mechanisms.

25 ENERGY STORAGE↗

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗

Timeouts Best Practices

This study investigates common timeouts encountered in the electric vehicle (EV) charging communications process. Many different timeouts are defined within the EV charging communications protocols. These timeouts can either be a fixed value or a defined range of values. In both cases, the timeout defines the duration of time for which one or both parties in the communications session are expected to wait for some action or process to complete before terminating the charge attempt. These timeout-based terminations are intended to prevent the charging process from becoming stuck indefinitely in any particular step. These terminations also enable a retry of the terminated charging session to begin. However, misaligned timeout values can have a significant negative impact on the user experience. Premature termination of charging sessions due to inappropriate timeout settings can lead to charging failures, causing inconvenience, wasted time, and frustration for users. These disruptions can degrade the overall user experience, making it essential to carefully manage and align timeout values with the relevant actions and processes to ensure reliable and satisfactory EV charging sessions. The core objective of this study is to boost reliability and enhance user experience by conducting a thorough review of timeout-based issues in EV charging and delivering a set of recommendations to modify these existing timeouts. These recommendations are informed by feedback gathered from multiple EV charging partners. This document is intended to inform electric vehicle supply equipment (EVSE) and EV manufacturers, EV charging infrastructure developers, and policymakers responsible for designing and implementing EV charging protocols and systems.

33 ADVANCED PROPULSION SYSTEMS↗

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗

Direct evidence of low work function on SrVO 3 cathode using thermionic electron emission microscopy and high-field ultraviolet photoemission spectroscopy

Perovskite SrVO 3 has recently been proposed as a novel electron emission cathode material. Density functional theory (DFT) calculations suggest multiple low work function surfaces, and recent experimental efforts have consistently demonstrated effective work functions of ~2.7 eV for polycrystalline samples, both results suggesting, but not directly confirming, that some fraction of even lower work function surface is present. In this work, thermionic electron emission microscopy (ThEEM) and high-field ultraviolet photoemission spectroscopy (UPS) are used to study the local work function distribution and measure the work function of a partially oriented- (110)-SrVO 3 perovskite oxide cathode surface. Our results show direct evidence of low work function patches of about 2.0 eV on the cathode surface, with a corresponding onset of observable thermionic emission at 750 °C. We hypothesize that, in our ThEEM and UPS experiments, the high applied electric field suppresses the patch field effect, enabling the direct measurement of local work functions. This measured work function of 2.0 eV is comparable to the previous DFT-calculated work function values of the SrVO-terminated (110) SrVO 3 surface (2.3 eV) and SrO-terminated (100) surface (1.9 eV). The measured 2.0 eV value is also much lower than the work function for the (001) LaB 6 single crystal cathode (~2.7 eV) and comparable to the effective work function of B-type dispenser cathodes (~2.1 eV). If SrVO 3 thermionic emitters can be engineered to access domains of this low 2.0 eV work function, they have the potential to significantly improve thermionic emitter-based technologies.

36 MATERIALS SCIENCE↗

The extracellular vesicle proteomes of Sorghum bicolor and Arabidopsis thaliana are partially conserved

Abstract Plant extracellular vesicles (EVs) are membrane-bound organelles involved mainly in intercellular communications and defense responses against pathogens. Recent studies have demonstrated the presence of proteins, nucleic acids including small RNAs, and lipids along with other metabolites in plant EVs. Here, we describe the isolation and characterization of EVs from sorghum (Sorghum bicolor). Nanoparticle tracking analysis, dynamic light scattering, and cryo-electron tomography showed the presence of a heterogeneous population of EVs isolated from the apoplastic wash of sorghum leaves. Cryo-electron microscopy revealed that EVs had a median size of 110 nm and distinct populations of vesicles with single or multiple lipid bilayers and low or high amounts of contents. The heterogeneity was further supported by data showing that only a subset of EVs that were stained with a membrane dye, Potomac Gold, were also stained with the membrane-permeant esterase-dependent dye, calcein acetoxymethyl ester. Proteomic analysis identified 437 proteins that were enriched in multiple EV isolations, with the majority of these also found in the EV proteome of Arabidopsis (Arabidopsis thaliana). These data suggest a partial conservation of EV contents and function between the monocot, sorghum, and a distantly related eudicot, Arabidopsis.

36 MATERIALS SCIENCE↗

Trap-assisted Auger-Meitner recombination in GaN p-i-n diodes

Most properties of semiconductor devices are dominated by shallow impurities. However, deep defects often play an important role, for instance, in recombination processes or high field transport. While a variety of techniques are available to assess the density and energy levels of impurities, other properties, such as the recombination mechanisms of the defects, escape observation. We report on the direct measurement of hot electrons generated by trap-assisted Auger-Meitner recombination (TAAR) in GaN p-i-n diodes. By performing electron emission spectroscopy (EES) on diodes with surfaces activated to negative electron affinity by cesium, we observe the expected overflow electrons of p-i-n diodes under low current injection. However, when operating the devices at higher current densities, as low as ∼25 A/c⁢m 2 , we measure the emission of high-energy electrons. At variance with the observed hot electrons in light-emitting diodes (LEDs) using EES, the hot electrons generated in p-i-n diodes at our tested currents cannot be from eeh Auger-Meitner recombination due to the diodes' significantly lower carrier densities compared to those in LEDs. During our measurements, we observe the emission of accumulated electrons with energies ∼0.42 eV, ∼0.99 eV, ∼1.43 eV, and ∼2.32 eV above the conduction-band minimum (CBM) at various bias conditions, suggesting the existence of conduction-band features in GaN at these energies where electrons can be long-lived, such as satellite-valley minima and inflection points. We also measure incompletely relaxed hot electrons approaching energies 1.97 ± 0.13 eV and 2.94 ± 0.13 eV above the CBM, as the diodes are biased to high currents, suggesting at least some of the TAAR partaking defects have an energy level ≳1.97 eV and ≳2.94 eV away from either the conduction or valence band edges. Additionally, at our highest operating currents, we measure hot electrons with energies 3.28 ± 0.13 eV above the CBM, providing direct evidence of TAAR processes involving shallow impurities. This unexpected observation of TAAR in GaN p-i-n diodes spotlights the importance of further studies of defects in GaN and the necessity to incorporate the multi-phonon emission, radiative, and TAAR capture steps of defect-assisted recombination cycles into device modeling. Furthermore, this experiment demonstrates the applicability of the simplest semiconductor structures, p-i-n diodes, as a test bed to study the rich recombination physics of semiconductor materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗

Reliability of Open Public Electric Vehicle Direct Current Fast Chargers

The aim was to systematically evaluate the usability of all public electric vehicles (EV) direct current fast chargers (DCFC) in the San Francisco region. To achieve a rapid transition to EVs, a highly reliable and easy to use charging infrastructure is critical to building confidence among consumers. The functionality and usability of all 182 open, public DCFC charging stations with CCS connectors (combined charging system) in the 9 counties of the Bay Area were tested (655 electric vehicle service equipment (EVSE) ports). An EVSE was classified as functional if it charged an EV for 2 minutes. Overall, 73.3% of the 655 EVSEs were functional. The causes of the nonfunctioning EVSEs (23.5%) were blank or unresponsive screens or error messages; payment system failures; charge initiation failures; network failures; or broken connectors. In addition, the cable was too short to reach the EV inlet for 3.2% of the EVSEs. A random sampling of 10% of the EVSEs, approximately 8 days after the first evaluation, found no overall change in functionality. The level of functionality found with field testing conflicts with the 95–98% uptime reported by the EV service providers (EVSPs) who operate the EV charging stations. There is a need for precise and verifiable definitions of uptime, downtime, and excluded time, as applied to public EV chargers. In conclusion, the level of failure of the existing public EV DCFC charge infrastructure highlights the importance of improving the system design and maintenance to improve adoption of EVs.

33 ADVANCED PROPULSION SYSTEMS↗

A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.

25 ENERGY STORAGE↗

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Redetermination of the Dissociation Energy of MgO(+)

In 1986, we reported a dissociation energy (D(sub 0) of 2.31 eV for the X(sup 2)Pi ground state of MgO(+). This value was determined by computing the dissociation energy to the Mg(2+) + O(-) limit and adjusting the value to the Mg(+) + O limit using the experimental Ionization Potential (IP) of Mg(+) and the Electron Affinity (EA) of O. The success of this method relies on the assumption that there is little covalent contribution to the bonding. The very small (0.04 eV) correlation contribution to the binding energy was taken as corroboration for the validity of this approach. Our earlier theoretical value was estimated to be accurate to at least 0.2 eV. It is in excellent agreement with the subsequent value of 2.30 +/- 0.13 eV determined by Freiser and co-workers from photodissociation experiments. It is also consistent with the upper (less than 3.1 eV) and lower (greater than 1.1 eV) bounds determined by Rowe obtained by studying the reactions of Mg(+) with 03 and NO2. However, it is inconsistent with an upper bound of 1.7 eV reported by Kappes and Staley based on their failure to observe MgO(+) in the reaction of Mg(+) with N2O. The picture became somewhat clouded, however, by the recent guided-ion beam mass spectrometric studies of Dalleska and Armentrout. Their initial analysis of the reaction data for Mg(+) + O2 lead to a bond dissociation energy of 2.92 +/- 0.25 eV, which is considerably larger than the value of 2.47 +/- 0.06 eV deduced from their studies of the Mg(+)+NO2 reaction.

Bauschlicher, Charles W., Jr.↗

Blood Volume: Importance and Adaptations to Exercise Training, Environmental Stresses and Trauma/Sickness

This paper reviews the influence of several perturbations (physical exercise, heat stress, terrestrial altitude, microgravity, and trauma/sickness) on adaptations of blood volume (BV), erythrocyte volume (EV), and plasma volume (PV). Exercise training can induced BV expansion; PV expansion usually occurs immediately, but EV expansion takes weeks. EV and PV expansion contribute to aerobic power improvements associated with exercise training. Repeated heat exposure induces PV expansion but does not alter EV. PV expansion does not improve thermoregulation, but EV expansion improves thermoregulation during exercise in the heat. Dehydration decreases PV (and increases plasma tonicity) which elevates heat strain and reduces exercise performance. High altitude exposure causes rapid (hours) plasma loss. During initial weeks at altitude, EV is unaffected, but a gradual expansion occurs with extended acclimatization. BV adjustments contribute, but are not key, to altitude acclimatization. Microgravity decreases PV and EV which contribute to orthostatic intolerance and decreased exercise capacity in astronauts. PV decreases may result from lower set points for total body water and central venous pressure, which EV decrease bay result form increased erythrocyte destruction. Trauma, renal disease, and chronic diseases cause anemia from hemorrhage and immune activation, which suppressions erythropoiesis. The re-establishment of EV is associated with healing, improved life quality, and exercise capabilities for these injured/sick persons.

Sawka, Michael N.↗

High-Efficiency Multi-Junction Space Solar Development Utilizing Lattice Grading

Progress towards achieving a high one-sun air mass 0 (AM0) efficiency in a monolithic dual junction solar cell comprised of a 1.62 eV InGaP top cell and a 1.1 eV InGaAs bottom cell grown on buffered GaAs is reported. The performance of stand-alone 1.62 eV InGaP and 1.1 eV InGaAs cells is compared to that of the dual junction cell. Projected AM0 efficiencies of 15.7% and 16.5% are expected for the 1.62 eV InGaP and 1.1 eV InGaAs cells grown on buffered GaAs. The dual junction cell has a projected one-sun AM0 conversion efficiency of 17%. The projected efficiencies are based upon the application of an optimized anti-reflective coating (ARC) to the as-grown cells. Quantum efficiency (QE) data obtained from the dual junction cell indicate that is is bottom cell current limited with the top cell generating 50% more current than the bottom cell. A comparison of the QE data for the stand-alone 1.1 eV InGaAs cell to that of the 1.1 eV InGaAs bottom cell in the tandem configuration indicates a degradation of the bottom cell conversion efficiency in the tandem configuration. The origin of this performance degradation is at present unknown. If the present limitation can be overcome, then a one-sun AM0 efficiency of 26% is achievable with the 1.62 eV/1.1 eV dual junction cell grown lattice-mismatched to GaAs.

Stan, Mark A.↗

Aligning Electric Vehicle Customer Charging with Grid Needs

This talk to the National Association of Regulatory Utility Commissioners (NARUC) focuses on "Aligning Electric Vehicle Customer Charging with Grid Needs" to highlight the opportunities associated with managed electric vehicle charging and its value for consumers and the power system. Electric vehicles (EVs) are experiencing a rapid rise in popularity and adoption, and growing EV adoption offers an opportunity to increase electricity demand. With expected widespread EV adoption, supporting charging will require investments in generation, transmission, and distribution systems. Uncoordinated charging of EVs will lead to increased system peak load, possibly exceeding the maximum power that can be supported by distribution systems and generally increasing power system stress. However, vehicles are underutilized assets parked ~96% of the time: managed EV charging can satisfy mobility needs while also supporting the grid. EVs are not a burden for the grid, but a resource: The demand-side flexibility provided by managed EV charging offers significant potential benefits for the grid over multiple timescales and applications., especially for high-renewable systems. Managed charging can support power system planning and operations during normal and extreme conditions, benefitting EV owners and other electricity consumers. Managed charging is shown to consistently provide hundreds of dollars in cost savings per EV each year.

ADVANCED PROPULSION SYSTEMS↗