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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 37 records · Page 2

Sensitivity of JWST to eV-Scale Decaying Axion Dark Matter

The recently launched James Webb Space Telescope can resolve eV-scale emission lines arising from dark matter decay. We forecast the end-of-mission sensitivity to the decay of axions, a leading dark matter candidate, in the Milky Way using the blank-sky observations expected during standard operations. Searching for unassociated emission lines will constrain axions in the mass range 0.18 to 2.6 eV with axion-photon couplings g a γ γ ≳ 5.5 × 10 − 12 GeV − 1 . In particular, these results will constrain nucleophobic QCD axions to masses ≲ 0.2 eV . Published by the American Physical Society 2025

Roy, Sandip (ORCID:0000000276387454)↗

EVs@Scale Next-Gen Profiles - Fleet Utilization 2024

As part of the U.S. Department of Energy’s EVs@Scale initiative, the Next-Gen Profiles (NGP) project provides a comprehensive, data-driven analysis of electric vehicle (EV) and electric vehicle supply equipment (EVSE) operations across real-world fleet deployments. This paper presents findings from the NGP’s Fleet Utilization study, which investigates operational behavior and asset usage across seventeen EV fleets and two EVSE fleets, encompassing a wide range of vehicle types and use cases. Data collected from diverse sources—varying in format and temporal resolution—are first reformatted into a unified structure. From this harmonized dataset, a suite of rigorously defined performance metrics is calculated at an hourly cadence, enabling consistent cross-comparison of charging, routing, and other key operational behaviors. Amid rapidly increasing EV adoption and growing demands for energy-efficient fleet operations, the analysis reveals clear utilization trends—including diurnal and weekly activity cycles, differences in short versus long charging session dependencies, and route-specific energy usage patterns. These findings highlight the need for tailored infrastructure strategies and the deployment of advanced energy management systems, such as Distributed Energy Resource Management Systems (DERMS) and Site Energy Management Systems (SEMS), which can optimize charging schedules and mitigate peak loads. By leveraging anonymized, harmonized datasets and standardized metrics, this study offers critical insights into fleet behavior and performance, providing a foundation to improve operational efficiency, reduce costs, and enable the scalable deployment of electrified transportation.

Wells, Landon↗

EVs@Scale NextGen Profiles: EVSE Characterization 2024

As part of the U.S. Department of Energy's EVs@Scale consortium, the Next-Generation Profiles (NextGen Profiles) project presents analysis and results from the characterization of high-power conductive and wireless charging infrastructure. High power charging equipment is capable of recharging electric vehicle traction batteries at power levels of 200KW and above. EVSE characterization was conducted over a wide range of DC output current and DC voltage charging for nominal and off-nominal test conditions. Test plans and procedures were developed and refined to define the test configurations and requirements, measurement parameters, and test procedures used throughout NextGen Profiles testing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

EVs@Scale Lab Consortium High-Power Charging Pillar Deep-Dive Technical Meeting

Managed under the the U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, the High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to create an experimental platform for integration and control approaches in a direct current (DC), distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for a DC-coupled charging hub ("DC hub" for short). This report explains the design, development, and implementation process of an experimental platform for the DC hub. DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges in establishing a DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and a lack of common system-level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products, as well as novel, in-house designed solutions, to evaluate different use cases at rated power and voltage levels. The developed proof-of-concept charging platform and open-source SEMS allow the development and testing of various controllers and chargers from different vendors. The DC hub platform integrated EVs, an ESS, a PV system, and building load to demonstrate the flexibility of the platform. The open-source SEMS controlled the devices within the hub using a rule-based implementation, realizing available standards.

ADVANCED PROPULSION SYSTEMS↗

Ionization Yield in Silicon for eV-Scale Electron-Recoil Processes

The development of single charge resolving, macroscopic silicon detectors has opened a window into rare processes at the O(eV) scale. In order to reconstruct the energy of a given event, or model the charge signal obtained for a given amount of energy absorbed by the electrons in a detector, an accurate charge yield model is needed. In this paper we review existing measurements of charge yield in Silicon, focusing in particular on the region below 1 keV. We highlight a calibration gap between 12-50 eV (referred to as the "UV-gap") and employ a phenomenological model of impact ionization to explore the likely charge yield in this energy regime. Finally, we explore the impact of variations in this model on a test case, that of dark matter scattering off electrons, to illustrate the scientific impact of uncertainties in charge yield.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗

A novel large-scale EV charging scheduling algorithm considering V2G and reactive power management based on ADMM

Electric vehicle aggregators (EVAs) that utilize vehicle-to-grid (V2G) technologies can function as both controllable loads and virtual power plants, providing key energy management services to the distribution system operator (DSO). EVAs can also balance the grid’s reactive power as a virtual static VAR compensator (SVC) and provide voltage stability by utilizing advanced electric vehicle (EV) chargers that are capable of four-quadrant operations to provide reactive power management. Finally, managed charging can benefit EVAs themselves by minimizing power factor penalties in their electricity bills. In this paper, we propose a novel EV charging scheduling algorithm based on a hierarchical distributed optimization framework that minimizes peak load and provides reactive power compensation for the DSO by collaboration with EVAs that manage both the active and the reactive charging and discharging power of participating EVs. Utilizing the alternative direction method of multipliers (ADMM), the proposed distributed optimization approach scales well with increased EV charging infrastructure by balancing active and reactive power while decreasing computational burden. In our proposed hierarchical approach, each EVA schedules the active and reactive EV charging and discharging power for 1) reactive power compensation in order to minimize power factor penalty and electricity cost accrued by the EVA, 2) satisfaction of each EV’s energy demand at minimal charging cost, and 3) peak shaving and load management for the DSO. When compared with an uncoordinated charging model, the efficacy of this proposed model is successfully demonstrated through a 300% decreased peak EV load for the DSO, 28% lower electricity costs for EV users, and 98.55% smaller power factor penalty, along with 17.58% lower overall electricity costs, for EVAs. The performance of our approach is validated in a case study with 50 EVs at multiple EVAs in an IEEE 13-bus test case and compared the results with uncoordinated EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

EVs@Scale High Power Charging Pillar

Slide deck assesses a portfolio of EVs, EVSEs, and Fleets that are expected to utilize High Power Charging (>200kW) to understand charging rates, grid impacts, and asset utilization. Provide DOE, project partners, stakeholders, and the public with analysis on the capability of HPC performance of today's charging infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗

EVs@Scale Next-Gen Profiles - Fleet Utilization 2023

As U.S. fleet operators begin transitioning to electric vehicles (EVs), critical questions arise regarding how to manage this shift without disrupting fleet operations or placing undue stress on the electric grid. A major challenge for fleets is maintaining effective operational schedules while accommodating charging requirements, particularly with high-power charging (HPC) infrastructure, which presents grid stability concerns for utilities. Proposed solutions such as charging substations, megawatt charging systems (MCS), and smart charge management systems (SCMS) offer potential pathways forward, but their effectiveness depends on alignment with real-world fleet behavior and operational constraints. This report investigates the charging and utilization behavior of EV and EVSE fleets actively employing HPC technologies by conducting detailed case study analyses based on telematics data. A suite of predefined metrics—covering charging, routing, and other operational behaviors—is developed to evaluate the impact of fleet activities on grid infrastructure and identify opportunities for optimization. Results highlight variations in charging behavior across fleets, such as weekday versus weekend usage, diurnal charging trends, and the role of operational predictability in enabling SCMS effectiveness. While SCMS can help lower costs and improve energy efficiency for fleets with stable schedules, they may be insufficient for fleets with highly variable or long-haul operations, which may require more robust solutions like MCS. Visualization of aggregated hourly energy metrics reveals that while fleet behaviors are diverse, there are common temporal patterns that could inform infrastructure planning and energy management. These insights emphasize the need for fleet-specific charging strategies that minimize grid impact while supporting reliable fleet operations. Additionally, the report underscores the broader economic stakes of electrification, particularly in high-value markets such as freight, where misaligned transitions could stall EV adoption. By examining current EV and EVSE fleet deployments using predetermined standardized metrics, this study offers a foundation for developing technologies and operational frameworks that support scalable, grid-compatible electrification across a variety of fleet types while establishing a baseline understanding of operational behaviors. In doing so, we aim to ensure that future charging solutions reflect actual fleet needs and grid constraints—an essential step toward maintaining operational continuity and achieving a successful transition to electric fleet operations.

Charging↗

Design and characterization of a phonon-mediated cryogenic particle detector with an eV-scale threshold and 100 keV-scale dynamic range

We present the design and characterization of a cryogenic phonon-sensitive Si detector exploiting the Neganov-Tromov-Luke effect to detect single-charge excitations. This device achieved 2.65(2) eV phonon energy resolution when operated without a voltage bias across the crystal and a corresponding charge resolution of 0.03 electron-hole pairs at 100 V bias. With a continuous-readout data acquisition system and an oine optimum-filter trigger, we obtain a 9.2 eV threshold with a trigger rate of the order of 20 Hz. The detector's energy scale is calibrated up to 120 keV using an energy estimator based on the pulse area. The high performance of this device allows its application to different fields where excellent energy resolution, low threshold, and large dynamic range are required, including dark matter searches, precision measurements of coherent neutrino-nucleus scattering, and ionization yield measurements.

Ren, R↗

Design and Characterization of a Phonon-Mediated Cryogenic Particle Detector with an eV-Scale Threshold and 100 keV-Scale Dynamic Range

We present the design and characterization of a cryogenic phonon-sensitive Si detector exploiting the Neganov-Trofimov-Luke effect to detect single-charge excitations. This device achieved 2.65(2) eV phonon energy resolution when operated without a voltage bias across the crystal and a corresponding charge resolution of 0.03 electron-hole pairs at 100 V bias. With a continuous-readout data acquisition system and an offline optimum-filter trigger, we obtain a 9.2 eV threshold with a trigger rate of the order of 20 Hz. The detector's energy scale is calibrated up to 120 keV using an energy estimator based on the pulse area. The high performance of this device allows its application to different fields where excellent energy resolution, low threshold, and large dynamic range are required, including dark matter searches, precision measurements of coherent neutrino-nucleus scattering, and ionization yield measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Search for an eV-Scale Sterile Neutrino Using Improved High-Energy νμ Event Reconstruction in IceCube

This Letter presents the result of a 3+1 sterile neutrino search using 10.7 yr of IceCube data. We analyze atmospheric muon neutrinos that traverse the Earth with energies ranging from 0.5 to 100 TeV, incorporating significant improvements in modeling neutrino flux and detector response compared to earlier studies. Notably, for the first time, we categorize data into starting and throughgoing events, distinguishing neutrino interactions with vertices inside or outside the instrumented volume, to improve energy resolution. The best-fit point for a 3+1 model is found to be at sin^{2}(2θ_{24})=0.16 and Δm_{41}^{2}=3.5 eV^{2}, which agrees with previous iterations of this Letter. The result is consistent with the null hypothesis of no sterile neutrinos with a p value of 3.1%.

Neutrino detection↗

Exploration of mass splitting and muon/tau mixing parameters for an eV-scale sterile neutrino with IceCube

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $ν$ μ + $\overline{ν}$ μ charged-current interactions in the energy range 500–9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state (Δm$^{2}_{41}$), the mixing matrix element connecting muon flavor to the fourth mass state (|U μ4 | 2 ), and the element connecting tau flavor to the fourth mass state (|U $\tau$4 | 2 ). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The remaining sterile neutrino matrix elements are left fixed, with |U e4 | 2 = 0 and δ 14 = 0, as they have a negligible effect, and δ 24 = π is set to give the most conservative limits. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3%. Profiling the likelihood of each parameter yields the 90% confidence levels: 2.4eV 2 < Δm$^{2}_{41}$) < 9.6eV 2 , 0.0081< |U μ4 | 2 < 0.10, and |U $\tau$4 | 2 < 0.035, which narrows the allowed parameter-space for |U $\tau$4 | 2 . However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of Δm$^{2}_{41}$, |U μ4 | 2 , and |U $\tau$4 | 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

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↗