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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Commissioning of Extended Electron Beam Ion Source at Brookhaven National Laboratory

Here, the Extended Electron Beam Ion Source (EEBIS) has been installed and commissioned at Brookhaven National Laboratory (BNL) hadron accelerator complex in the spring of 2023. EEBIS has replaced its predecessor, RhicEBIS, which provided ions for BNL hadron facilities for over a decade since 2009. The motivations for the source upgrade are to provide higher intensities of the Au 32+ ion beam for the Relativistic Heavy Ion Collider (RHIC) and to provide of an intense source of polarized 3 He 2+ ions for the future Electron Ion Collider (EIC) at BNL. EEBIS is and will continue to be the primary source for a variety of different ion species for the NASA Space Radiation Laboratory (NSRL) at BNL. EEBIS utilizes two identical, two-meter-long unshielded 5T warm bore superconducting solenoids, and it is operated with electron beam current up to 10 A, providing a high-capacity ion traps to fulfill the requirement for high intensity ion beams. The upstream solenoid contains a “short ion trap” with a length of 95 cm, while the “long ion trap” with a length of 178 cm is located inside the downstream solenoid bore. The main features of EEBIS are: * A Gas injection and ionization cell equipped with a Lorenz pulse valve * High-capacity ZAO non-evaporable getter (NEG) custom linear pumping units * In situ apparatus for pumping speed measurements to monitor NEG activation and saturation * “External drift tube” construction with differential pumping stages to provide space for Lorentz pulse valve and 3 He high-field polarization cell * A Ba oxide electron gun cathode. The design of EEBIS as well as the results of its commissioning and first-year operation are presented and discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A conserved chaperone protein is required for the formation of a noncanonical type VI secretion system spike tip complex

Type VI secretion systems (T6SSs) are dynamic protein nanomachines found in Gram-negative bacteria that deliver toxic effector proteins into target cells in a contact-dependent manner. Prior to secretion, many T6SS effector proteins require chaperones and/or accessory proteins for proper loading onto the structural components of the T6SS apparatus. However, despite their established importance, the precise molecular function of several T6SS accessory protein families remains unclear. In this study, we set out to characterize the DUF2169 family of T6SS accessory proteins. Using gene co-occurrence analyses, we find that DUF2169-encoding genes strictly co-occur with genes encoding T6SS spike complexes formed by valine-glycine repeat protein G (VgrG) and DUF4150 domains. Although structurally similar to Pro-Ala-Ala-Arg (PAAR) domains, “PAAR-like” DUF4150 domains lack PAAR motifs and instead contain a conserved PIPY motif, leading us to designate them PIPY domains. Next, we present both genetic and biochemical evidence that PIPY domains require a cognate DUF2169 protein to form a functional T6SS spike complex with VgrG. This contrasts with canonical PAAR proteins, which bind VgrG on their own to form functional spike complexes. By solving the first crystal structure of a DUF2169 protein, we show that this T6SS accessory protein adopts a novel protein fold. Furthermore, biophysical and structural modeling data suggest that DUF2169 contains a dynamic loop that physically interacts with a hydrophobic patch on the surface of its cognate PIPY domain. Based on these findings, we propose a model whereby DUF2169 proteins function as molecular chaperones that maintain VgrG–PIPY spike complexes in a secretion-competent state prior to their export by the T6SS apparatus.

DUF2169↗
DOE OSTI2024

Subsurface Energy Systems Mapping Inquiry Tool (MapIT)

The Subsurface Energy Systems Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration for subsurface energy exploration and characterization efforts for resource identification (e.g. critical minerals, hydrocarbons, geothermal) as well as injection of geologic sequestration of carbon dioxide (e.g. enhanced oil recovery, saline storage, etc.). Modules within the tool curate data related to geology, faults, fractures, injection and confining zones, hydrologic information, groundwater, groundwater wells, geomechanical and petrophysical data, and geochemical data. User documentation on how to use the tool is also provided. Data have been collected from authoritative national, state, and local sources and made available in this tool. The data is also available as a data catalog and Esri Geodatabase at: https://edx.netl.doe.gov/dataset/mapit-database Disclaimer: There is no guarantee of completeness or appropriateness for individual user’s requirements. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer). This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. https://www.netl.doe.gov/home/disclaimer

Carbon Sequestration↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coherent diffraction imaging in the undergraduate laboratory

We present an undergraduate optics instructional laboratory designed to teach skills relevant to a broad range of modern scientific and technical careers. In this laboratory project, students image a custom aperture using coherent diffraction imaging, while learning principles and skills related to digital image processing and computational imaging, including multidimensional Fourier analysis, iterative phase retrieval, noise reduction, finite dynamic range, and sampling considerations. After briefly reviewing these imaging principles, we describe the required experimental materials and setup for this project. Our experimental apparatus is both inexpensive and portable, and a software application we developed for interactive data analysis is freely available.

Porter, J. Nicholas↗
DOE OSTI2025

Integrated operation scenarios: Chapter 6 of the special issue: on the path to tokamak burning plasma operation

Here we report the progress of the development and optimization of operational scenarios for ITER and beyond, focusing upon baseline, hybrid, and steady-state scenarios since 2007. This includes advancements made by the integrated operation scenarios (IOS) topical group of the international tokamak physical activity as well as contributions from the broader tokamak community. The key area of research involves developing IOSs that encompass tokamak physics, operation, and technology by utilizing integrated modeling and control strategies. This requires leveraging available actuators to simultaneously control plasma position and shape, MHD activities that could lead to disruptions, transport, plasma-wall interaction and power exhaust, fuel cycle, fusion burn, and tritium breeding. The control extends from the plasma initiation phase, through the current ramp-up, flattop, start and end of the fusion burn, and current ramp-down, to the plasma termination phase. A review of the currently developed scenarios and modeling is provided in terms of (i) optimizing plasma initiation in ITER, (ii) preparing for the low activation phase to fully commission all tokamak systems and establish and validate physics and scenario conditions in preparation for deuterim-tritium (DT) operation, (iii) developing and preparing baseline and hybrid scenarios to demonstrate the feasibility of achieving these regimes within device constraints, (iv) exploring steady-state scenarios to meet ITER’s steady-state goals, (v) evaluating and preparing actuators for ITER, (vi) developing integrated control solutions using shared actuators. The most notable achievements include; (i) the development of ITER demonstration discharges by matching various dimensionless parameters, (ii) the development of scenarios in an ITER-like tungsten environment and DT operation, and (iii) the development of scenarios in superconducting tokamaks, enabling long-pulse operations with similar coil constraints to ITER. Along with these significant achievements, outstanding issues and recommendations for further research and development are provided. Importantly, this study goes beyond simply updating the ITER Physics Basis; it carries profound implications for the broader field of burning plasma research, offering valuable insights and guidance for the next generation of fusion experiments and devices.

ITER↗
DOE OSTI2025

Hidden diversity: Transcriptomic and photosynthetic variation among common ‘wild type’ Chlamydomonas strains

The unicellular green alga Chlamydomonas reinhardtii is a widely studied reference organism, particularly in photosynthesis research. It employs photoprotective mechanisms, such as state transitions (ST) and non-photochemical quenching (NPQ), to cope with rapid light changes. Most widely used strains share a recent common ancestor yet differ by up to ~50 000 nuclear variants—genetic diversity that is often overlooked. Even among ‘wild type’ strains, we document significant phenotypic differences, such as pigment accumulation, and nutrient utilization. To elucidate the basis for this variation, we compared transcriptomes and physiological traits of seven commonly used laboratory strains, including the reference strain and the CLiP mutant library parental strain. Despite identical growth conditions, ~40% of genes were differentially expressed between strains. Most of these differences are attributable to changes that have accrued during laboratory propagation, and adverse conditions may have driven transcriptomic drift. At the physiological level, we catalog the range of strain-dependent responses related to photosynthesis and high light (HL) acclimation. Specifically, (i) all strains develop NPQ upon HL exposure, but to various degrees, (ii) they show a substantial variation in ST capacity, and (iii) they regulate the composition of the photosynthetic apparatus differently. We find that NPQ levels do not correlate with LHCSR3 expression, suggesting an additional layer of NPQ regulation. STs are constantly activated and independent of growth light intensities. Overall, our findings highlight significant strain-to-strain differences in virtually all photosynthetic parameters, emphasizing the importance of careful strain selection in future research endeavors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The Henkin-McGill critical temperature test for explosives revisited: An overview of historical and modern method development

Many overarching standards, regulations, or other requirements necessitate that the critical temperature (T crit ) of an energetic material be known or estimate prior to operations such as heating. However, they rarely, if ever, provide a specific method for doing so. While other methods exist to calculate T crit , such as the Frank-Kamenetskii equation, computer simulation, etc., these cannot be readily utilized for energetics that are physical mixtures (i.e. most pyrotechnics) or materials where detailed material properties required for such calculations are lacking. Here, in this study, a COTS (commercial off-the-shelf) SBAT (Simulated Bulk Auto-ignition Test) apparatus is modified to perform Henkin cookoff tests. This creates a simple, efficient, and cost-effective solution to estimate required T crit values for energetic materials. After a historical overview of the evolution of the Henkin test, several common energetic materials (PETN, RDX, etc.) for which T crit has been readily calculated, and historical data is available, were analyzed for comparison and verification purposes. This was followed by a variety of pyrotechnic mixtures and other materials to where calculation methods cannot be readily used. The modified apparatus, as well as an updated sample shell sealing method, produced results that aligned well with historical data. It also produced reasonable T crit estimates for those materials where the Frank-Kamenetskii equation cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection Description This dataset contains input and output data for the manuscript Mongird, K. et al. (under review) titled "Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection". Input data corresponds to gridded spatial siting attributes that are necessary to conduct a random forest machine learning analysis of siting feature importance. Output data includes SHAP feature analysis outputs, and classification report values. For data on power plant siting results referred to in the manuscript, please refer to the CERF: IM3 Projected Western US Power Plant Locations data download page. The downloadable data includes values for eight different future scenarios for the Western US. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Technical Information The dataset includes two sets of data files: (1) CERF gridded siting parameters and (2) Feature analysis outputs and classification reports. All downloadable data is in csv file format. Files with x/y coordinate information use the Albers Equal Area Conic projection (ESRI:102003). 1. CERF Gridded Siting Parameters This directory provides a balanced sample of gridded CERF siting parameters data for eight different scenarios for the Western US through 2055, seven different technologies, and eight timesteps. This data serves as input to the feature analysis. It contains the following parameters. region_name - name of region (i.e., state) sited - binary value representing whether the grid cell received a siting of that technology type (1=True) rcp - binary value representing scenario resource concentration pathway (0 = RCP4.5, 1 = RCP8.5) ssp - binary value representing scenario shared socioeconomic pathway (0 = SSP3, 1 = SSP5) climate - binary value representing cooler (0) or hotter (1) GCM forcing tech_name - generation technology name sited_year - year that values correspond to transmission_cost - cost of transmission interconnection pipeline_cost - cost of natural gas pipeline interconnection interconnection_cost - total interconnection cost (sum of transmission cost and gas pipeline cost) lmp - associated locational marginal value ($/MWh) associated with the grid cell, timestep, scenario, and technology xcoord - x-coordinate of location ycoord - y-coordinate of location 2a. Feature Analysis Output The dataset includes the feature analysis shap output for locational marginal price and interconnection cost. It contains the following parameters. technology - generator technology name scenario - name of scenario feature - name of feature, either locational_marginal_price or interconnection_cost value - the mean of absolute value of SHAP values for given feature 2b. Feature Analysis Classification Report This download includes the classification report associated with each random forest model. The dataset contains the following parameters. technology - generation technology name scenario - name of scenario test - one of precision (the proportion of predicted positives that are actually correct), recall (the proportion of actual positives that were correctly identified), f1-score (the harmonic mean of precision and recall) 0.0 - value of test for classification of 0 (grid cell not chosen for siting) 1.0 - value of test for classification of 1 (grid cell chosen for siting) accuracy - accuracy of model (i.e., fraction of all predictions that were right) macro avg - Simple average of test values for all classes weighted avg - Weighted average of test values for all classes, weighted based on Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2025

Selective capture and recovery of uranium oxide colloids from aqueous soil suspensions using high gradient magnetic filtration

High Gradient Magnetic Filtration (HGMF) is a promising method for the selective capture and recovery of uranium oxide from surface soils. To date, however, magnetic filtration of uranium oxide has only been demonstrated at a proof-of-principle scale using relatively small filters (<5 cm 3 ) at low flowrates (<60 mL/min). Here, to explore the efficacy of magnetic filtration of uranium oxide at a larger scale, a newly designed HGMF apparatus that is more than an order of magnitude larger than our earlier filters (106 cm 3 ) was designed, fabricated, and tested at relatively high flowrates. Filtration experiments were performed using aqueous uranium oxide particle suspensions with Arizona Road Dust (ARD) as a soil simulant. At a flowrate of 125 mL/min, the apparatus’ uranium capture rate was exceptionally high (96 %), but selectivity was poor due to the high rate of capture for diamagnetic soil constituents (e.g., 77 % for silicon). All particles were captured at a lower rate when the flowrate was increased to 250 mL/min, but uranium selectivity was significantly increased due to the more substantial reduction in diamagnetic particle capture (i.e., capture rate of 77 % and 15 % for uranium and silicon, respectively). When backwashing the apparatus at the same flowrates used during filtration experiments, the rate of uranium recovery tended to be fairly low. Nevertheless, higher flowrates (1 L/min) and sonication were both shown to be highly effective methods of increasing uranium recovery. Magnetic field simulations were also performed to investigate potential optimizations to the design of the apparatus. These simulations showed that the intensity of the applied magnetic field could be increased by increasing the thickness of the steel magnetic housing. Additionally, stochastic trajectory simulations were performed to investigate the potential mechanisms of particle capture.

HGMF↗
DOE OSTI2026

Fuel-Cladding Eutectic Study of Legacy Fast Flux Test Facility (FFTF) MFF HT9/U-10Zr Metallic Fuel

This report presents the first systematic investigation of fuel-cladding eutectic interaction (FCEI) in irradiated HT9/U-10Zr metallic fuel from the Fast Flux Test Facility (FFTF) Materials Fuels Form (MFF) program, using differential scanning calorimetry (DSC) coupled with scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). Two irradiated fuel cross-sections, MNT07H (9.5 at% burnup, x/L = 0.78) and MNT08H (7.0 at% burnup, x/L = 0.93), were subjected to three successive isothermal annealing rounds (R1–R3) at 820°C for 20 minutes each, yielding a cumulative transient duration of one hour. This study directly addresses a recognized gap in the existing FCEI database, which previously lacked irradiated HT9/U-10Zr data at burnup levels above 8 at%. Two principal findings emerge from the study. First, for both samples, FCEI remained spatially confined within the pre-existing fuel-cladding chemical interaction (FCCI) zone boundaries after R3, with no measurable eutectic penetration into unaffected cladding beyond the original FCCI layer. This self-limiting behavior is consistent with historical Fuel Behavior Test Apparatus (FBTA) results and is attributed to the near-eutectic phase composition of the FCCI zone, which rapidly absorb the available eutectic-forming constituents and then stall penetration once the FCCI zone is consumed. A comparison with unirradiated surrogate data further supports this mechanism: whereas a U–34 at.% Fe sample would be expected to show ~176 µm of iron penetration under comparable conditions, the irradiated samples exhibited only ~20 µm, a discrepancy attributed to irradiation-induced interfacial porosity and pre-existing FCCI composition gradients. Second, for MNT08H, FCEI was observed exclusively on the half of the cladding circumference where pre-existing steady-state FCCI was present, with no detectable FCEI on the opposite half. Three hypotheses are proposed to explain this asymmetry: the inhibiting role of a zirconium-rich rind at the fuel-cladding interface; the chemical sequestration of iron by redistributed zirconium within the fuel matrix; and the persistence of fuel-cladding gaps on the FCEI-free half that preclude direct contact. All three hypotheses require further experimental investigation. The results extend the empirical FCEI database into higher-burnup territory and demonstrate the viability of DSC-based testing as a substitute for the no-longer-available FBTA apparatus. Future work will include additional cross-section testing, compilation of the full FCEI dataset, model evaluation, and DSC testing of ternary fuel compositions to broaden the experimental basis for safety assessment of sodium-cooled fast reactor systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Coatings for CSP Lifetime

The feasibility and performance of tower-technology-based concentrated solar power (CSP) is highly dependent on the efficiency of the energy transformation from sun to heat at the receiver. The higher the solar absorptivity of the receiver coating, the higher the efficiency of the plant as a whole. BrightSource Energy (BSE) has developed a series of High-Performance Coating (HPC) systems in order to achieve high absorptivity over the plant lifetime (25-35 years). This requires stable coatings that are easily applicable on the large receiver surface and will maintain their optical properties under intense solar flux and thousands of heating and cooling cycles in desert conditions. Different coating formulations are required according to the differing plant conditions: receiver materials, operating conditions (temperatures, daily cycles, etc.), and environmental conditions. BSE also developed a coating for the next generation of CSP receivers, such as those being under DOE’s CSP Gen3 program, which will be operated with high temperature heat transfer fluids at temperatures of up to 800°C, which is significantly hotter than the operating temperature of current systems. Once the coating is formulated, the next challenge is evaluating its lifetime properties. BSE has found several independent failure modes that impact HPC absorptivity degradation: • Decrease in HPC optical properties due to oxidation in the receiver tubes surface below the HPC; • HPC film deterioration due to cycling of temperatures and humidity due to daily operation startup and shutdown as well as changing ambient conditions; • Mechanical degradation due to erosion by sand and wind. Existing test methods examine various aspects independently, but do not provide a combined accelerated lifetime result. Creating such a combined test suite, with a way to interpret the results to predict the coating’s projected lifetime, was the ultimate goal of this project. The project was divided into three major workstreams: lab testing (individual failure mode tests and combined failure mode tests); developing a theoretical model for aging; and validation of the test apparatus via on-sun testing in near real-world conditions at CIEMAT-PSA. Developing a test apparatus that accurately controlled the temperature while also introducing the desired solar flux proved more challenging than expected. While in the end we did succeed in creating a test apparatus that can control temperature, solar flux, and humidity, the results did not appear to accelerate the lifetime of the samples as desired. We suspect that to properly accelerate the samples we must also subject the samples to increased amounts of oxygen. Similarly, while we successfully created a combined model that is publicly available, we were unable to validate it sufficiently to feel comfortable recommending it as a general guideline.

14 SOLAR ENERGY↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2025

Search for Axion Dark Matter from 1.1 to 1.3 GHz with ADMX

Axion dark matter can satisfy the conditions needed to account for all of the dark matter and solve the strong 𝐶⁢𝑃 problem. The Axion Dark Matter eXperiment (ADMX) is a direct dark matter search using a haloscope to convert axions to photons in an external magnetic field. Key to this conversion is the use of a microwave resonator that enhances the sensitivity at the frequency of interest. The ADMX experiment boosts its sensitivity using a dilution refrigerator and near quantum-limited amplifier to reduce the noise level in the experimental apparatus. In the most recent run, ADMX searched for axions between 1.10 and 1.31 GHz to extended Kim-Shifman-Vainshtein-Zakharov sensitivity. This Letter reports on the results of that run, as well as unique aspects of this experimental setup.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

MARVEL Lessons Learned – 2026 Edition Fabrication, Fuel Procurement, Quality Assurance, and Safety Basis

The Microreactor Applications Research Validation and Evaluation (MARVEL) project is intended to be among the first U.S. advanced reactor demonstrations in four decades. By virtue of being sponsored directly by the U.S. Department of Energy (DOE), the reactor is expected to benefit the broader nuclear community by exercising design processes, safety reviews, and supply chains. This project is committed to publicly documenting key lessons learned along the way toward demonstration. Building on a 2025 report that focused on lessons learned from guard vessel fabrication and Primary Coolant Apparatus Test (PCAT) testing (Abou-Jaoude et al. 2025), this 2026 edition captures findings spanning structural fabrication, quality assurance (QA), reactivity control system (RCS) assembly, fuel fabrication and shipment, safety basis development, balance-of-plant design, and overall reactor design.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Completion of Transport Property Measurements on Multiple Actinide Fluoride Mixtures

One of the missions of the US Department of Energy’s Office of Nuclear Energy (DOE-NE) Molten Salt Reactor (MSR) Campaign under the Advanced Reactor Technology program has been to experimentally measure thermophysical properties of MSR-relevent salt systems, with the intent of supporting the development of the Molten Salt Thermal Properties Database (MSTDB). This database is jointly funded by the DOE-NE Nuclear Energy Advanced Modeling and Simulation Program and the MSR Campaign. Multiple DOE national laboratories, including Oak Ridge National Laboratory (ORNL), have been conducting measurements of thermophysical properties to support MSTDB development and provide MSR developers with access to new data that has been measured using modern methodologies and more advanced sample characterization techniques. These data may either fill gaps in the database or provide updated higher quality data to replace legacy data. Researchers at ORNL have recognized significant gaps in the transport property data of actinide-bearing fluoride salt systems of MSR industry interest. Moreover, for the data present in MSTDB in this category, the uncertainty margins are generally high, leading to questionability in our current understanding of the thermophysical characterization of actinide fluoride mixtures. As such, the focus of this study has been to generate new transport property data of actinide fluoride mixtures that are of immediate interest to MSR developers. Specifically, the mixtures NaF-UF 4 (78 - 22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been studied—NaF-UF 4 for thermal conductivity and viscosity and NaF-KF-UF 4 for viscosity. Thermal conductivity measurements have been conducted with a variable gap apparatus, whereas viscosity has been measured with a rolling ball viscometer. Methodological and calibration details are provided for both measurement processes, along with measurement system updates that have enabled easier manufacturing of components and fewer challenges associated with conducting the measurements themselves. The resultant data collected for NaF-UF 4 (78–22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been compared with relevant mixture data within the thermophysical arm of the MSTDB (MSTDB-TP).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗