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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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DOE OSTI2024

Observation of the J / ψ → μ + μ − μ + μ − decay in proton-proton collisions at s = 13 TeV

The J / ψ → μ + μ − μ + μ − decay has been observed with a statistical significance in excess of five standard deviations. The analysis is based on an event sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 33.6 fb − 1 . Normalizing to the J / ψ → μ + μ − decay mode leads to a branching fraction of [ 10.1 − 2.7 + 3.3 ( stat ) ± 0.4 ( syst ) ] × 10 − 7 , a value that is consistent with the standard model prediction. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of groomed event shape observables in deep-inelastic electron-proton scattering at HERA

The H1 Collaboration at HERA reports the first measurement of groomed event shape observables in deep inelastic electron-proton scattering (DIS) at $\sqrt{s} =319$ GeV, using data recorded between the years 2003 and 2007 with an integrated luminosity of 351 pb -1 . Event shapes provide incisive probes of perturbative and non-perturbative QCD. Grooming techniques have been used for jet measurements in hadronic collisions; this paper presents the first application of grooming to DIS data. The analysis is carried out in the Breit frame, utilizing the novel Centauro jet clustering algorithm that is designed for DIS event topologies. Events are required to have squared momentum-transfer $Q^2 > 150$ GeV 2 and inelasticity $0.2< y < 0.7$. We report measurements of the production cross section of groomed event 1-jettiness and groomed invariant mass for several choices of grooming parameter. Monte Carlo model calculations and analytic calculations based on Soft Collinear Effective Theory are compared to the measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

First Observation of Neutrino Candidates in ProtoDUNE

The Neutrino Platform at CERN hosts two massive prototypes for the DUNE Far Detector to test the technology for the coming Horizontal Drift and Vertical Drift designs, almost perfectly on axis with the direction of the SPS beamline pointed towards the North Area. The 400 GeV/c SPS protons impacting on the T2 target area may produce exotic particles that could travel ~700 meters to the detectors, in addition to a substantial flux of neutrinos. Simulations of the neutrino flux demonstrate that thousands of neutrino interactions are expected per week in the active volume of NP04 spanning energies from a few GeV up to 180 GeV, constituting the main background for such search. The first step towards establishing a BSM physics program at the Neutrino Platform is therefore to observe neutrinos originating from the SPS beam. A sample of high-energy neutrino events in a DUNE FD-like LArTPC may also be of broader use to the DUNE collaboration. For example, by testing the performance of reconstruction algorithms on highly-energetic neutrino interactions with large hadronic showers. An initial neutrino search was performed by developing filters to remove cosmic events. After filtering, the remaining events were eye-scanned to identify neutrino candidates amongst the residual cosmic background. Over two of the available NP04 runs, 29 neutrino candidates were identified. A separate run taken with the SPS beam off yielded no neutrino candidates. An analysis is now under development that will use all available data, large Monte Carlo samples and full event reconstruction, with the aim of confirming whether NP04 is capable of observing feebly interacting particles originating from the SPS beam.

Pullia, Dario [CERN]↗
DOE OSTI2024

Sustainable Enablers of Knowledge Management Strategies in a Higher Education Institution

By facilitating the capture, organization, and dissemination of knowledge within and beyond the institution, knowledge management (KM) in higher education institutions (HEIs) fuels innovation, enhances research impact, and strengthens collaboration, ultimately leading to the creation of new knowledge and its valuable exchange. However, there is still much to explore in terms of the enablers of knowledge creation, sharing, and transfer. Therefore, this paper aims to identify the enablers of effective KM in the Polytechnique University of Leiria, which serves as a benchmark for other higher education institutions due to its leadership role in RUN-EU, a consortium of European universities. To achieve this, a narrative analysis based on information from SCOPUS and the institute’s website, focusing on innovation, research, and development strategies, is proposed. The findings suggest that for KM initiatives to be successful, they need to be strategically designed, culturally supported, technologically enabled, and integrated into existing workflows.

Santos, Eleonora (ORCID:0000000346930804)↗
DOE OSTI2026

AT2025ulz and S250818k: Leveraging DESI Spectroscopy in the Hunt for a Kilonova Associated with a Subsolar-mass Gravitational-wave Candidate

On 2025 August 18, the LIGO–Virgo–KAGRA collaboration reported a subthreshold gravitational-wave candidate detection consistent with a subsolar-mass neutron star merger, denoted S250818k. An optical transient, AT2025ulz, was discovered within the localization region. AT2025ulz initially appeared to meet the expected behavior of kilonova emission, the telltale signature of a binary neutron star merger. The transient subsequently rebrightened after ∼5 days and was classified as a Type IIb supernova. In this work, we analyze the observations of its host galaxy obtained by the Dark Energy Spectroscopic Instrument (DESI). From the DESI spectrum, we obtain a secure redshift of z = 0.084840 ± 0.000006. If S250818k has an astrophysical origin, this places the transient within 2σ of the gravitational-wave distance and results in an integral overlap between the gravitational-wave alert and the transient location of log 10 $\mathcal{I} ≈ 3.9 - 4.2$. Our analysis of the host galaxy’s spectral energy distribution reveals a star-forming, dusty galaxy with stellar mass ∼10 10 M ⊙ , broadly consistent with the population of both short gamma-ray bursts and core-collapse supernova host galaxies. We also present our follow-up of DESI-selected candidate host galaxies using the Fraunhofer Telescope at the Wendelstein Observatory, and show the promise of DESI for associating or rejecting candidate electromagnetic counterparts to gravitational-wave alerts. These results emphasize the value of DESI’s extensive spectroscopic dataset in rapidly characterizing host galaxies, enabling spectroscopic host subtraction, and guiding targeted follow-up.

Hall, Xander J. [Carnegie Mellon University, Pitts↗
DOE OSTI2026

A Search for Millimeter-bright Blazars as Astrophysical Neutrino Sources

The powerful jets of blazars have been historically considered as likely sites of high-energy cosmic-ray acceleration. However, the particulars of the launched jet and the locations of leptonic and hadronic jet loading remain unclear. In the case when leptonic and hadronic particle injection occur jointly, a temporal correlation between synchrotron radiation and neutrino production is expected. We use a first catalog of millimeter wavelength (95–225 GHz) blazar light curves from the Atacama Cosmology Telescope for a time-dependent correlation with 12 yr of muon neutrino events from the IceCube South Pole Neutrino Observatory. Such millimeter emission traces activity of the bright jet base, which is often self-absorbed at lower frequencies and potentially gamma-ray opaque. We perform an analysis of the population, as well as analyses of individual, selected sources. We do not observe a significant signal from the stacked population. TXS 0506+056 is found as the most significant, individual source, though this detection is not globally significant in our analysis of selected active galactic nuclei. Our results suggest that the majority of millimeter-bright blazars are neutrino dim. In general, it is possible that many blazars have lighter, leptonic jets, or that only selected blazars provide exceptional conditions for neutrino production.

Abbasi, R. [Loyola University, Chicago, IL (United↗
DOE OSTI2025

A multifunctional sesquiterpene synthase integrates with cytochrome P450s to reinforce the terpenoid defense network in maize

Terpenoids, the largest and most structurally diverse class of plant natural products, play essential roles in maize defense and ecological interactions. In this study, we identified and functionally characterized a sesquiterpenoid-based defense pathway in maize centered on α-santalenoic acid, a pathogen-inducible sesquiterpenoid antibiotic. Using a combination of metabolite-based genome-wide association studies (mGWAS), linkage mapping, and heterologous expression assays, we identified ZmTPS9 as a multiproduct terpene synthase that primarily produces α-santalene and β-bisabolene. Sequence analysis and site-directed mutagenesis revealed that threonine at position 413 is critical for enzyme activity, with its deletion resulting in a complete loss of enzyme activity. The sesquiterpene hydrocarbons produced by ZmTPS9 are further oxidized by three cytochrome P450 monooxygenases, ZmCYP71Z16, ZmCYP71Z18, and ZmCYP71Z19, to yield antimicrobial metabolites including α-santalenoic acid, zealexin D1 (ZD1), and zealexin D2 (ZD2). Together, these findings demonstrate a convergent biosynthetic strategy in maize, where multiproduct terpene synthases and promiscuous P450s collaboratively generate a flexible and robust terpenoid defense network.

a-santalenoic acid↗
DOE OSTI2025

Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot

This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level. Using charging data from over 4,600 EV drivers, the study analyzed SCM’s impact on the distribution systems of BGE and Pepco, which consists of over 2000 feeders. Unlike prior research that focused on system-wide trends or synthetic feeders, this analysis offers granular, feeder-level insights based on real-world operational data. It highlights how transformer density, load profiles, and infrastructure constraints influence smart charging performance. Results show feeder-level conditions play a crucial role in SCM effectiveness, with most feeders benefiting more from LB, while TOU-based SCM may be sufficient for others. By 2035, LB reduced peak charging loads by 27% on average, compared to 23% under TOU-based SCM, though some feeders saw reductions exceeding 35%, while others experienced minimal impact. Feeders with higher transformer utilization and limited capacity benefited more from LB, which more effectively distributed charging demand during off-peak hours. Beyond reducing grid constraints, SCM offers long-term operational and financial benefits. By shifting EV charging demand strategically, utilities can optimize asset utilization, delay infrastructure investments, and enhance grid performance. In terms of infrastructure upgrade deferrals, at the feeder level, LB consistently reduced peak charging loads and resulting infrastructure upgrade costs, particularly in high EV enrollment areas, decreasing the number of overloaded transformers by up to 35%, while TOU-based SCM achieved 20-30% reductions depending on feeder characteristics. At the system level, LB has the potential to defer total upgrade costs by $\$$186 million for BGE, compared to $\$$159 million under TOU-based SCM. For Pepco, TOU-based SCM performed slightly better, deferring upgrade costs by $\$$30 million, compared to $\$$29 million under LB. Section 4.5 reviews some of the system differences between BGE and Pepco. However, as EV adoption scales, TOU-based SCM will introduce secondary peak charging loads, reinforcing the need for more advanced, adaptive SCM approaches to prevent new grid challenges. As EV adoption continues to grow, feeder-level managed charging strategies will be essential for mitigating grid stress, improving infrastructure efficiency, and maintaining energy affordability for consumers. This report provides critical insights for utilities, Public Utility Commissions (PUCs), and state agencies on the role of feeder-specific smart charging in infrastructure planning, policy development, and grid modernization. The findings underscore the importance of tailored, data-driven SCM solutions that align with local grid conditions, ensuring a resilient, cost-effective transition to increasing EV adoption while safeguarding distribution system performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Artificial Intelligence/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)

This collaborative project integrated an improved version of the Artificial Intelligence/Deep Learning FRNN prediction and control software into the real-time DIII-D PCS (plasma control system). A key AI/DL software challenge is to build a modern high-performance computing (HPC) enabled “synthetic plasma simulator” capable of carrying out HPC-driven real-time plasma control applications. This involves development of a deep learning framework to train the surrogate model for a first-principles-based instability analysis simulator (“SGTC”) derived from the global gyrokinetic code GTC. The role of SGTC is to provide accurate and detailed plasma instability information from a real-time AI-based simulator capability to complement the deep learning prediction and control from experimentally-measured signals, such as ECE Imaging, supplemented by synthetic SGTC-ECEI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Net Zero World COP28 Outcomes Report – Indonesia

This report describes Net Zero World Initiative activities initiated with Indonesia in 2023. The Net Zero World Initiative is a collaborative effort of eight countries, nine U.S. government agencies, 10 U.S. Department of Energy (DOE) national laboratories, and partnering philanthropies and nongovernmental organizations. Its goal is to elevate and enact climate ambition pledges and accelerate the transition to net-zero, resilient, and inclusive energy systems globally. The Net Zero World team, the Government of Indonesia’s Ministry of Energy and Mineral Resources (MEMR), and other stakeholders jointly identified and are advancing action in the four priority focus areas -- Energy Infrastructure Analysis, Island Energy Transition, Building Decarbonization, and Sustainable Transport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

CMIP7 data request: land and land ice priorities and opportunities

The Land and Land Ice Theme in the Coupled Model Intercomparison Project Phase 7 (CMIP7) represents the current understanding of physical processes in land surface ecosystems, hydrology, cryosphere, and their physical interactions with other Earth system components. Simulations from Earth system models (ESMs) could provide crucial information for assessing planetary safety, such as critical tipping elements, and be used to inform climate risks for improving climate impact assessments and policy decisions. This paper presents a collaborative effort to identify scientific opportunities in the Land and Land Ice Theme of the CMIP7 Data Request. The proposed opportunities build upon advances in ESMs, including new freshwater system and land ice processes being included in CMIP7, as well as the scientific community's demand for high-frequency and sub-grid-scale land surface outputs. In total, 25 variable groups that contain 716 variables have been identified to be potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology. Key reflections from this data request effort include advocacy for closer engagement between the user community and modeling groups, reduction in the technical barriers to tracking existing parameters and defining new variables, and more streamlined variable management. These will be essential to enhance the usability and reliability of CMIP7 outputs for climate and Earth system research and applications to a broad audience that relies on the CMIP7 endeavor.

Li, Yue [Univ. of California, Los Angeles, CA (Uni↗
DOE OSTI2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Computed Tomography Scanning and Petrophysical Measurements of Eastern Williston Basin Twin Buttes and Hagel Formations

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize core from two wells that represent coal resources across North Dakota. These include the MC23080C Well in Mercer County and the 23-B001 Well in Oliver County. The primary impetus of this work was to capture a detailed digital representation of the core from the MC23080C and 23-B001 Wells. The collaboration between the NETL and the Energy and Environment Research Center (EERC) enables other research entities to access information about this potential carbon ore, rare earth, and critical mineral resource plays in the Williston Basin. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. Fractures, discontinuities, and millimeter-scale features were readily detectable with the medical CT scanner acquired images. Imaging with the NETL medical CT scanner was performed on entire cores. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), gamma density, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for potential future analysis. Higher-resolution industrial and micro-CT images were acquired from selected zones along the depth of the core to visualize the structure in higher detail. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core, with the resulting macro- and micro-descriptions relevant to many subsurface energy-related examinations traditionally performed at NETL.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

New NDA Methods for Thorium Fuel Cycle Safeguards (Final Report)

This project developed portable Neutron Resonance Transmission Analysis (pNRTA) as a new non-destructive assay (NDA) method for thorium fuel cycles safeguards and other applications where multiple isotopes must be measured when present together. pNRTA leverages epithermal neutron resonances to assay multiple safeguards-relevant isotopes (e.g., 233 U and 235 U) when they are present together in a sample. Existing techniques are challenged by this task, driving the need for new active interrogation methods. With selected detectors, pNRTA works in high gamma-ray backgrounds from fission and activation products and 232 U progeny expected in thorium fuel cycle samples. This project leveraged a pNRTA system developed at Pacific Northwest National Laboratory (PNNL) and collaboration with the Massachusetts Institute of Technology (MIT). The system uses a commercially available deuterium-tritium (DT) neutron generator at short standoff (2 m). Key achievements in this project included: first-of-a-kind pNRTA quantitative measurements of 233 U oxide samples, an assessment of neutron detector technologies suitable for pNRTA in high gamma-ray background environments, experimentally demonstrating quantitative assay of samples containing 233 U and 235 U, and modeling studies showing the applicability of pNRTA to a wide range of material forms. Further, a custom algorithm was developed at MIT, which provided mean bias of 9% and relative standard deviation of 36% in assaying 233 U, 235 U, 238 U, and 232 Th content in eight measured samples. These outcomes form a solid technical basis for pNRTA as a new promising capability for international safeguards verification that is portable, non-destructive, quantitative, and isotopic specific.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Combined tracer analysis for DESI 2024 BAO

This paper demonstrates how the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) and future baryon acoustic oscillations (BAO) analyses can optimally combine overlapping tracers (galaxies of distinct types) in the same redshift range. We make a unified catalog of Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) in the redshift range 0.8 < z < 1.1 and investigate the impact on the BAO constraints. DESI DR1 contains ∼ 30% of the final DESI LRG sample and less than 25% of the final ELG sample, and the combination of LRGs and ELGs increases the number density and reduces the shot noise. We developed a pipeline to merge the overlapping tracers using galaxy bias as an approximately optimal weight and tested the pipeline on a suite of Abacus simulations, calibrated on the final version of the DESI Early Data Release. When applying our pipeline to the DESI DR1 catalog, we find an improvement in the BAO constraints of 11% for α iso and ∼ 7.0% for α AP consistent with our findings in mock catalogs. Our analysis was integrated into the DESI DR1 BAO analysis to produce theLRG+ELG result in the 0.8 < z < 1.1 redshift bin, which provided the most precise BAO measurement from DESI DR1 with a 0.86% constraint on the BAO distance scale and a 9.1σ detection of the isotropic BAO feature.

baryon acoustic oscillations↗
DOE OSTI2024

TEAMER - Extreme Events Modeling for the MARMOK-OWC Wave Energy Converter

Through the TEAMER program, Sandia National Laboratories (SNL) collaborated with IDOM Incorporated to study their MARMOK-Oscillating Water Column (MARMOK-OWC) wave energy conversion device. The study yielded a quantitative understanding of hydrodynamic pressures on the oscillating water column (OWC) device surfaces, the mooring tensions, and the dynamic performance of the device under extreme ocean wave conditions. This project utilized a comprehensive multi-phase Navier-Stokes flow solver with an overset body-fit mesh to predict fluid velocities and hydrodynamic forces on the MARMOK-OWC device. Computational Fluid Dynamics (CFD) analysis were conducted using OpenFOAM. This data includes the OpenFOAM cases (setup and data) to run the extreme events developed during the project. This project is part of the TEAMER RFTS 4 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗