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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37

Exploiting Fixed Charge to Control Schottky Barrier Height in Si|Al 2 O 3 |MoO x – based Tunnel Diodes

The insertion of a tunneling atomic layer deposited (ALD) Al 2 O 3 film between MoO x and p-type Si has been studied to investigate Schottky barrier height tunability with varied negative fixed charge density. This work seeks to increase the hole-selectivity of MoO x -based contacts through manipulation of interface fixed charge. Fixed charge density and interface trap state densities are determined as a function of alumina processing conditions in metal-oxide-semiconductor capacitors (MOSCAPs). Schottky barrier heights were determined from Mott-Schottky analysis of tunnel diodes. An alumina deposition temperature of 80°C and post-deposition annealing at 425°C yielded the highest magnitude of negative fixed charge density (-3.5 × 10 12 q . cm –2 ). High deposition temperature and/or post-deposition annealing produced the lowest interface trap state density (1 × 10 12 eV -1 . cm –2 ). On p-type silicon, Schottky barrier height minimization was not clearly correlated with increasing fixed charge density. However, on n-type silicon, a significant increase in Schottky barrier height was evident (~0.8 eV to > 1 eV) and is attributed to the large negative fixed charge. Here, the findings from this work indicate that Schottky barrier height in carrier selective contacts can be tuned by electrostatic engineering of the SiO x |Al 2 O 3 interface.

aluminum oxide↗

Modeling of Lithium Nucleation and Plating Kinetics Under Fast Charge Conditions

The onset of lithium nucleation and subsequent plating on the graphite particles is a challenging problem in the design of fast charging batteries. Here, a variational phase field formulation has been developed to initiate the nucleation of lithium particles based on the local plating overpotential conditions and allowing to predict the lithium plating under fast charge conditions. The model demonstrates that (1) at small charging current density, there is no nucleation and plating of metallic lithium, and no effect on the intercalation kinetics; (2) at intermediate charging current densities, initially a stagnated growth from isolated lithium nuclei is observed followed by a continuous growth of metallic lithium; (3) at large charging current densities, a continuous growth of metallic lithium resulting from coalescence of small nuclei into large nuclei decreases the excess interfacial energy, which in turn slows down the intercalation kinetics. The formulation sets the stage for predicting and evaluating the influence of various electrolyte compositions, graphite particle morphologies and electrode loadings on the nucleation and plating dynamics under fast charge conditions.

25 ENERGY STORAGE↗

Charging Hub Scenario Sheet Screenshot

The Excel-based CHECT tool estimates the LCOC ($/kWh) by charger type (Level 1, Level 2, and DC fast charging) for a given charging hub scenario. CHECT requires users to input certain charging hub scenario parameters, including the number of chargers, daily utilization, and charger replacement frequency by charger type. Additional inputs such as the charging schedule, local utility rates, capital/operational costs, and financial inputs can be customized by the user, or the tool can generate results using appropriate default values from literature for the charging hub scenario and service location(s). Using the above inputs, CHECT performs a robust techno-economic analysis to generate the LCOC by charger type, broken down by cost category (e.g., capital, operational, utility, taxes) for various combinations of charging hub types (multiunit dwelling or public) and ownership models (residential, utility, or private company). It also outputs the annual discounted cash flows and determines the most sensitive input variables. In addition, the tool allows users to easily compare the LCOC across various ownership models or across different states.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electric Vehicle Managed Charging: Forward-Looking Estimates of Bulk Power System Value

When and where electric vehicle charging occurs has significant implications for power systems supporting widespread electric vehicle deployment with high shares of wind and solar generation. Numerous studies have estimated the value of scheduling or otherwise managing electric vehicle charging in such power systems. This study improves on those earlier works by leveraging detailed simulation models for electric vehicle adoption, electric vehicle use, electric vehicle charging, and bulk power system operations; and linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This study closely analyzes electric vehicle managed charging (EVMC) performance along the dimensions of flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and participation rate, under the assumptions of ubiquitous chargers and all trips completed on time. The study is located in a passenger light-duty vehicle adoption scenario with 100% electric vehicle sales by 2035, and in an envisioned 2038 New England power system for which within-region generation is 84% clean.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Third Quarter 2022

Electric vehicle (EV) charging infrastructure continues to rapidly change and grow. Using data from the U.S. Department of Energy's (DOE) Alternative Fueling Station Locator, this report provides a snapshot of the state of EV charging infrastructure in the United States in the third calendar quarter of 2022 (Q3 2022) by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the eleventh report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator (Fourth Quarter 2022)

Electric vehicle (EV) charging infrastructure continues to rapidly change and grow. Using data from the U.S. Department of Energy's (DOE) Alternative Fueling Station Locator, this report provides a snapshot of the state of EV charging infrastructure in the United States in the fourth calendar quarter of 2022 (Q4 2022) by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the twelfth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator (First Quarter 2023)

Electric vehicle (EV) charging infrastructure continues to rapidly change and grow. Using data from the U.S. Department of Energy's Alternative Fueling Station Locator, this report provides a snapshot of the state of EV charging infrastructure in the United States in the first calendar quarter of 2023 by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with a 2030 infrastructure requirement scenario. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the thirteenth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Second Quarter 2023

Electric vehicle (EV) charging infrastructure continues to rapidly change and grow. Using data from the U.S. Department of Energy's Alternative Fueling Station Locator, this report provides a snapshot of the state of EV charging infrastructure in the United States in the second calendar quarter of 2023 by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with a 2030 infrastructure requirement scenario. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the fourteenth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in response to time-varying electricity prices and increasing shares of personal trip demand served (between 1% and 25% of all metro trips served by the SAEV fleet). Simulation results are presented across various scenarios assuming fleetwide coordination to minimize charging energy costs while constrained by offering adequate mobility service to fleet customers. The results indicate that the SAEV charging load is highly flexible; energy costs were shown to reduce between 13% and 46% across a wide range of simulated scenarios. In addition, these savings were realized without detrimentally impacting the fleet’s ability to service trips.

autonomous vehicle↗

Lessons Learned From Evaluation and Mitigation of Space Charging Threat Due to Use of Isolated (Hybrid) Bearings on the Pace Ocean Color Instrument

A high precision, high resolution Ocean Color Instrument (OCI) was developed for the Plankton, Aerosol, Cloud ocean Ecosystem (PACE) mission which required the use of electrically isolated Hybrid Bearings (silicon nitride balls). While desirable for technical performance of the instrument, this application caused portions of the instrument to become electrically isolated and come under threat of space charging effects from charged particles and the resultant differential charging. An evaluation of the environment, susceptibility of the components, such as bearings and electronics, and mitigation strategies were performed. As part of that process, simulations of the charging environment, analysis of internal mechanism charging and prediction of most likely discharge paths, testing of the bearings for susceptibility as well as resulting damage were performed and analyzed. Additionally, a novel method to deal with charging was developed. Considerations for dealing with electrically isolated mechanisms, results of the above-mentioned efforts as well as lessons learned are presented.

space charging↗

Integrated Dispatching and Charging Management of an Autonomous Electric Vehicle Ride-Hailing Fleet

Electrification and autonomous driving are two important trends in transportation systems. The convergence of these two technologies will introduce opportunities to improve transportation systems' operation and energy efficiency. One potential application is the commercial ride-hailing fleet with autonomous electric vehicles (AEVs). In order to harvest promising benefits from introducing AEVs into ride-hailing fleets, some unavoidable challenges will need to be resolved to ensure the fleets operates functionally and efficiently. This paper discusses the challenges of dispatching AEVs and their interactions with charging infrastructure. An integrated decision making framework for dispatching and charging has been designed using a system optimization approach to study the AEVs' management within the period when they drop off passengers and pick up the next passengers. Its potential fleet-wide benefits have been illustrated by comparing operations under a heuristic approach. A simulation platform has been designed to test different decision making strategies for the ride-hailing AEV fleets operational performance. Using this platform, detailed case studies have been performed with different fleet sizes, dispatching strategies, and charging infrastructure network settings. Comprehensive analyses from various aspects have been conducted to understand the AEVs' fleet operation performance, (e.g., zero occupancy vehicle miles traveled, successfully served ratio of ride-hailing requests, fleet vehicle charging downtime, and charging infrastructure utilization). Results have provided a deep understandings on operation's dynamics under various fleet system configurations and also have demonstrated advantages of the optimization-based approach for the AEV fleet management. Studies in this paper inform better designs on the future of sophisticated management strategies and charging infrastructure to support ride-hailing AEV fleet operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Feasibility Study of Real-Time Carbon Emission Responsive Electric Vehicle Charging Control in Buildings: Preprint

With the progressing electrification of the transportation sector, the source of carbon emissions is gradually shifting from fossil fuel to grid electricity because of electric vehicles (EVs). The carbon intensity of the grid can fluctuate significantly within hours due to the time-varying power generation mix. Therefore, shifting EV charging loads to cleaner hours in response to the carbon intensity signals can reduce carbon emissions. Existing EV charging control methods typically consider the electricity price or the available generation by distributed energy resources (e.g., photovoltaics) to inform decision-making. Such methods tend to reduce energy costs but may neglect the environmental impact of EV charging activities. We propose and compare four carbon emission responsive EV charging controllers with various control rules. The proposed controllers are evaluated based on simulation experiments using metrics such as carbon emission reduction potential, state of charge (SOC) at departure, and peak demand. We found that the need of EV owners to have full batteries at departure could lead to an emission increase when the curtailed EV charge was compensated before departure. Further, up to 12.7% of carbon emission reduction can be achieved if the EV owners reduce the target SOC at departure by less than 15%.

carbon emission↗

Flexible Charging to Unify the Grid and Transportation Sectors for EVs at Scale (FUSE)

Electric vehicle (EV) adoption will expand beyond light-duty vehicles charging at lower-power public locations and family residences to include medium- and heavy-duty applications with more powerful charging at public stations and private depots. The Vehicle Grid Integration (VGI) and Smart Charge Management (SCM) pillar in EVs@Scale supports multiple projects. The FUSE project is developing and evaluating enabling technologies, charging solutions, and infrastructure design approaches to investigate the intricacies and potential benefits of vehicle grid integration and the application of smart charge management to charging of electric vehicles at scale. This presentation summarizes the findings of this research in 2024.

ADVANCED PROPULSION SYSTEMS↗

Economics of electric vehicle corridor fast charging in the United States

Corridor direct-current fast charging (DCFC) stations enable long-distance electric vehicle travel, yet their economics remain uncertain due to high capital costs, low initial utilization, and exposure to utility demand charges. This study evaluates the long-term economics of corridor DCFC across the United States, incorporating capital and operating expenses-including charging equipment and real-world utility tariffs-alongside modeled station utilization, financial incentives, and ancillary retail revenue. In the Baseline scenario, modeled breakeven costs for corridor DCFC average $\$$0.42/kWh over 20 years, yet fewer than half of stations reach cost parity with gasoline on a per-mile basis. Utilization is the primary driver of cost variation, with low-utilization stations costing roughly six times more per kilowatt-hour than the national average. Excluding stations that fail to reach cost parity reduces National Highway System coverage within 50 miles from 94% to 67%, underscoring the trade-off between market-driven deployment and comprehensive network coverage. These results provide guidance for charging providers, utilities, planners, and policymakers seeking to develop and sustain a financially viable national corridor charging network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Time Matters: A Survival Analysis of Public Electric Vehicle Charging Infrastructure Utilization

The rapid adoption of plug-in electric vehicles (PEVs) places significant demands on public charging infrastructure, making it critical to understand and optimize charger utilization. This study provides one of the most comprehensive analyses of charging behavior to date by applying a survival analysis to a dataset of nearly 16 million level 2 (L2) and direct current (DC) fast charger sessions across the United States from 2017 to 2022. Using Kaplan-Meier curves and log rank tests, our analysis reveals statistically significant and distinct duration patterns influenced by charger type, time of day, and day of the week. We find that L2 charging sessions exhibit high variability tied to venue type, whereas DC sessions are more uniform, typically lasting 30-45 min. This study introduces the operational efficiency score (OES), a metric for standardizing the performance evaluation of charging stations. Our findings offer actionable insights for optimizing charger deployment, developing dynamic pricing strategies to reduce vehicle dwell time, and improving load management for grid operators, ultimately enhancing the efficiency and availability of public charging infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

0D Nanocrystals as Light‐Driven, Localized Charge‐Injection Sources for the Contactless Manipulation of Atomically Thin 2D Materials

A contactless charge‐injection scheme that allows the local and quasi‐permanent manipulation of atomically thin 2D materials, such as monolayer (1L‐)MoS 2 , over spatial extents of several tens of micrometers, is reported. The possibility to precisely position and localize the charge‐injection source to the micrometer scale post‐fabrication allows the investigation of local unperturbed electronic structure of the 2D material. Thanks to this novel approach, the important impact of sample inhomogeneity on the charge‐carrier percolation that occurs over the entire extent of the 2D flake and proliferates up to 40 μm away from the localized charge injection is elucidated. The apparent driving force for carrier relocation is the initial inhomogeneous electronic landscape of the 2D material. These studies demonstrate that local and contactless charge injection with submicrometer precision delivers an alternative route for charge injection and indicates that local 2D material electronic structure can serve as a key element for novel nanoscale device design.

Ghini, Michele↗

Lewis Acid‐Activated Charge Trapping in Dielectric Polymers for Superior High‐Temperature Electrostatic Energy Storage

Dielectric polymer capacitors are essential for electrostatic energy storage but suffer from charge transport-induced energy losses, particularly at elevated temperatures where thermally activated charge carriers exacerbate conduction. Conventional mitigation strategies rely on introducing heterogeneous interfaces to create charge traps, complicating scalable film fabrication. A homogeneous molecular trapping mechanism would circumvent these complexities, yet remains underexplored. Herein, a charge trapping strategy is devised by modifying the lowest occupied molecular orbitals of dielectric polymers through Lewis acid-base adduct formation. The use of tris(pentafluorophenyl)boron (BCF) as a Lewis acidic molecular additive introduces deeper charge traps in commercial polyetherimide (PEI) while retaining homogeneity. With only 0.5 wt.% loading, the PEI-BCF film exhibits greatly improved breakdown strength, achieving an ultrahigh discharged energy density of 7.3 J cm-3 with excellent cycle stability at 200 °C. This work establishes a facile molecular approach to decoupling charge trapping from heterogeneous interfaces, enabling high-energy-density polymer capacitors operable under extreme thermal conditions.

Fan, Lu↗

Overcoming the Intrinsic Limitations of Fast Charging Lithium‐Ion Batteries Using Integrated Acoustic Streaming

A lithium‐ion battery's maximum charge rate and energy density are intrinsically limited by the ion diffusion rate in the electrolyte. Most research focuses on materials science solutions to this problem, with gradual improvement over the years. A mechanical solution is proposed to integrate an MHz‐order frequency surface acoustic wave (SAW) device into an existing 1.8 Ah multilayered Li‐ion pouch cell to enhance the ion diffusion rate and the overall battery performance. Both the charging rate and cycling lifetime are improved from SAW. At a 6C (10 min) charge and C/3 discharge rate, typical of electric vehicle applications, integrating SAW into the Li‐ion cell doubles the energy density and maintains at least 72% of the battery's initial capacity after 2000 cycles. Moreover, using SAW quantifiably reduces battery degradation in these conditions as determined by optical imaging, scanning electron microscopy, X‐ray diffraction, and neutron diffraction. The use of SAW appears to offer a method to avoid undesirable Li metal plating on the graphite anode during charging, and leads to a much longer battery lifetime and good charge capacity, all despite rapid charging.

Huang, An↗