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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Dynamic Tripolar Strategic Balance: A Net Assessment (Workshop Summary)

On December 9-10, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “The Dynamic Tripolar Strategic Balance: A Net Assessment.” The discussion was guided by the following key questions: • By what metrics should the strategic balance be assessed? • How dynamic is the balance? How fragile? • Is the United States gaining strategic advantage, losing it, or holding steady, overall? • In order to gain new advantages or re-gain advantages lost, can or should the United States prioritize some domains and accept more risk in others? If so, which ones?

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Joint Sample Analyses of Nuclear Forensic Materials Provided by the Republic of Kazakhstan: U. S. Laboratory Results

This document serves as an interim report to summarize sample analyses performed by Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL) on a series of five nuclear forensics samples provided by the Institute of Nuclear Physics (INP) in the Republic of Kazakhstan. The sample set contains four uranium oxide powders and one low-enriched uranium fuel pellet. The samples were provided as part of a broader collaboration that involved a set of joint sample analyses conducted by INP and the US National Laboratories. The joint analyses are being conducted using well-developed analytical plans. These activities are designed to support the advancement of nuclear forensic science and capacity building in all three institutes in both countries. This report builds upon an earlier preliminary summary of the joint interactions and will be augmented by a final report. The final report will summarize the results and value of all sample analyses performed at the three institutes (INP, LLNL, and LANL). The final report will also provide an intercomparison of the results, analytical methods and best practices employed, as well as outline future collaborative nuclear forensics activities that are being developed in the Kazakhstan region.

and nuclear chemistry↗
DOE OSTI2026

Soil physical and chemical measurements for topsoils collected during NEON campaign in East River, CO (06/14/2018-06/28/2018)

The package is part of the DOE Watershed Function Science Focus Area (SFA) project and includes soil physical and chemical measurements from topsoils collected at the East River, Colorado, in conjunction with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey conducted in June 2018. The soil measurements include soil bulk density, soil volumetric water content, soil microbial biomass C (Carbon), N (Nitrogen) and C:N (C to N ratio), soil DNA yield, soil total extractable organic C, soil total extractable N, soil extractable nitrate, soil extractable ammonium, soil dissolved inorganic N, soil dissolved organic N, soil pH, soil TOC400 (total organic carbon at 400°C), soil ROC (residual oxidizable carbon), soil TIC (total inorganic carbon), soil TOC (total organic carbon), soil TC (total carbon), soil N, soil OM (organic matter) loss on ignition. Additional associated site metadata can be found in the ESS-DIVE package 10.15485/1618130. The dataset includes (1) 2018_NEON_soil_physical_chemical_measurements.csv: soil physical and chemical measurements indexed by soil sample IGSNs; (2) samples.csv: sample metadata file used to register International Generic Sample Numbers (IGSNs); (3) flmd.csv: file level metadata file; and (4) dd.csv: data dictionary file. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS (Catchment Hydrology and ↗
DOE OSTI2026

Comparing the fluorination of Pb+ and Po+: insights into p-block relativistic effects for superheavy elements

It is expected that the chemical properties of the heaviest of the superheavy elements (SHEs, = 113 – 118) do not align with what is suggested by their current positions on the periodic table. Specifically, the onset of significant relativistic effects, including increased spin–orbit splitting of the p-orbitals may lead to enhanced stability of low-oxidation states. Notably, it is predicted that flerovium ( = 114) may exhibit pseudo-noble gas behavior from a electron configuration that acts as an ‘inert pair’. Even though it is expected that the – splitting becomes pronounced toward the end of the p-block’s sixth row, there is currently limited experimental evidence to confirm its extent or impact. Here, the production of gas-phase lead ( = 82) and polonium ( = 84) fluoride cations (PbF and PoF ) were compared to elucidate differences in accessible oxidation states. The PoF and PbF species were produced and identified with the FIONA spectrometer at the Lawrence Berkeley National Laboratory 88-Inch Cylctron Facility. Polonium showed notably different fluorination chemistry than lead, producing PoF and PoF as primary products compared to lead’s PbF and PbF . The distribution of PoF products observed offer insights as to the role of spin–orbit splitting for polonium. Similar studies of superheavy elements would elucidate the accessibility of their low-oxidation states as well as to inform chemical predictions for eighth-row elements not yet discovered.

Pore, Jennifer L [Nuclear Science Division, Lawren↗
DOE OSTI2025

Data and scripts from: “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”

This data package includes data and scripts from the manuscript “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”.The study addressed common challenges faced in environmental sensing and modeling, including uncertain input data, missing sensor observations, and high-dimensional datasets with interrelated but redundant variables. Point-scaled meteorological and soil sensor observations were perturbed with noises and missing values, and denoising autoencoder (DAE) neural networks were developed to reconstruct the perturbed data and further predict evapotranspiration. This study concluded that (1) the reconstruction quality of each variable depends on its cross-correlation and alignment to the underlying data structure, (2) uncertainties from the models were overall stronger than those from the data corruption, and (3) there was a tradeoff between reducing bias and reducing variance when evaluating the uncertainty of the machine learning models.This package includes:(1) Four ipython scripts (.ipynb): “DAE_train.ipynb” trains and evaluates DAE neural networks, “DAE_predict.ipynb” makes predictions from the trained DAE models, “ET_train.ipynb” trains and evaluates ET prediction neural networks, and “ET_predict.ipynb” makes predictions from trained ET models.(2) One python file (.py): “methods.py” includes all user-defined functions and python codes used in the ipython scripts.(3) A “sub_models” folder that includes five trained DAE neural networks (in pytorch format, .pt), which could be used to ingest input data before being fed to the downstream ET models in ‘ET_train.ipynb” or ‘ET_predict.ipynb’.(4) Two data files (.csv). Daily meteorological, vegetation, and soil data is in “df_data.csv”, where “df_meta.csv” contains the location and time information of “df_data.csv”. Each row (index) in “df_meta.csv” corresponds to each row in “df_data.csv”. These data files are formatted to follow the data structure requirements and be directly used in the ipython scripts, and they have been shuffled chronologically to train machine learning models. The meteorological and soil data was collected using point sensors between 2019-2023 at(4.a) Three shrub-dominated field sites in East River, Colorado (named “ph1”, “ph2” and “sg5” in “df_meta.csv”, where “ph1” and “ph2” were located at PumpHouse Hillslopes, and “sg5” was at Snodgrass Mountain meadow) and(4.b) One outdoor, mesoscale, and herbaceous-dominated experiment in Berkeley, California (named “tb” in “df_meta.csv”, short for Smartsoils Testbed at Lawrence Berkeley National Lab).- See "df_data_dd.csv" and "df_meta_dd.csv" for variable descriptions and the Methods section for additional data processing steps. See "flmd.csv" and "README.txt" for brief file descriptions.- All ipython scripts and python files are written in and require PYTHON language software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geophysical survey associated with NEON AOP survey, East River, CO 2018

The package contains data layers developed and used in Falco et al. 2024: “EcoImaging: Advanced Sensing to Investigate Plant and Abiotic Hierarchical Spatial Patterns in Mountainous Watersheds". The package is part of the DOE Watershed Function Science Focus Area (SFA) project and includes geophysical measurements collected at the East River, Colorado, in conjunction with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey conducted in June 2018. This dataset provide soil geophysical information and were used to investigate soil-plant relationships. The dataset consists of: - NEON_2018_EMI_survey.zip: the electromagnetic induction (EMI) survey as shape-file; - NEON_plot_TDR.csv: plot‑level data from Time‑Domain Reflectometry (TDR) measurements, providing: * volumetric water content (VWC) in percent (%); * soil temperature in degrees Celsius (°C); - file level metadata (flmd.csv) - data dictionary (dd.csv) file This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

Depth-resolved sagebrush root metabolomics, rhizosphere microbial communities, and geochemistry at the East River Watershed

This data set consists of results from soil nutrient profile, untargeted metabolomics, mass spec imaging, and amplicon sequencing. Data for soil nutrient profile includes common cations (Ca, Mg, Na, and K etc.) extracted from 3 digesting steps – ammonia acetate (for exchangeable cations), nitric acid (for acid dissolved fraction), and hydrofluoric acid/perchloric acid (HF/HClO4) for whole soil digestion. It also includes concentration of organic carbon, inorganic nitrogen (ammonia and nitrate) and phosphorus (Bray-1 P and nitric acid extract), and total nitrogen and phosphorus. Data for untargeted metabolomics includes metabolomic profile for root exudate/tissues and soil extracts from depths at surface soil to saprolite, that were measured using gas chromatography – mass spectrometry (GC-MS), and liquid chromatography – tandem mass spectrometry (LC-MS/MS). Data for mass spec imaging includes spatial distribution of metabolites that were detected and annotated with Fourier transformation ion cyclotron resonance mass spectrometer (FTICR-MS). Data for amplicon sequencing includes the base paired 16S and ITS ribosomal RNA sequences from Miseq Illumina sequencing. All samples were collected from 2 sampling campaign October 2022 and June 2023. Collectively, these datasets enable a mechanistic evaluation of how nutrient acquisition, especially nitrogen and phosphorus, differs between shallow roots operating in soil and deep roots functioning within the fractured bedrock zone. All files are provided as comma-separated values (CSV) fies (.csv) and (GZIP) file (.gz). The compressed .gz FASTQ files can be read directly in R using the dada2 package as part of the amplicon sequence analysis workflow. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research was performed on a project award 60563 (https://dx.doi.org/10.46936/expl.proj.2022.60563/60008727) from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830.

EARTH SCIENCE > AGRICULTURE > SOILS > CARBON↗
DOE OSTI2024

Fiscal Year 2025 Site Sustainability Plan (Rev. 2)

This document is presented as the Site Sustainability Plan (SSP) for Lawrence Livermore National Laboratory (LLNL), consistent with the instructions provided by the Department of Energy (DOE) received in August 2024 as a deliverable for DOE Order 436.1A Departmental Sustainability requirement. LLNL is certified in Environmental Management System (EMS) (ISO 14001) and aligns sustainability efforts with the EMS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

One Million Open-source Cislunar Orbits

Cislunar space, encompassing the region from geosynchronous orbit to beyond the Moon, is poised to become a cornerstone for future exploration, scientific discovery, and national security. Missions in this region, spanning durations from weeks to decades, require robust infrastructure and reliable transit capabilities. The complex gravitational influences of the Moon, Sun, and planets, along with thermal radiation from Earth and the Sun, lead to significant trajectory deviations, resulting in kilometer-scale errors within days. Leveraging the high-performance computing resources at Lawrence Livermore National Laboratory (LLNL), we have simulated one million high-fidelity cislunar trajectories, now publicly available via LLNL’s Green Data Oasis and the Unified Data Library. Generated using the open-source Space Situational Awareness Python package, these trajectories match the precision of commercial tools such as AGI’s Systems Tool Kit and NASA’s General Mission Analysis Tool. This data set is a valuable resource for reference, statistical analysis of cislunar orbit populations, and training machine learning models for rapid orbit classification with minimal observational input. Preliminary analysis reveals stable bands in Keplerian element space, particularly around five geosynchronous radii across a range of inclinations and eccentricities. Beyond this threshold, the Moon’s influence disrupts most unassisted orbits, though co-orbiting L4/L5 Lunar Trojans persist throughout the six-year simulation.

Astronomy and AstroPhysics↗
DOE OSTI2025

Updating Critical Temperature Calculations for Several Secondary High Explosives

In designing experiments where high explosives (HEs) are heated, it is important to have an understanding of where thermal runaway may occur. This determination is often done by using the Frank-Kamenetskii (FK) equation. For several highly-studied HEs, the parameters necessary for FK calculations are typically referenced from decades-old literature, and more recent experimental data have shown that these values require adjustment. For example, some of the legacy parameters dangerously overpredict the critical temperature by tens of degrees relative to more recent observed values. Herein, we first summarize historical results and highlight the importance of insulation effects when estimating critical temperatures for small samples, which is especially relevant to small-scale aging, compatibility, and characterization experiments. Here, we then present updated FK parameters for several common secondary CHNO HEs like RDX, HMX, PETN, and TATB, as well as the first reported values for 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105). Our updated parameters produce critical-temperature curves that are consistent with both mm-scale differentical scanning calorimetry (DSC) measurements and cm-scale data from the Lawrence Livermore National Laboratory one-dimensional time-to-explosion (ODTX) experiment. In analyzing the critical temperature versus sample size curves derived from the transcendental FK equation, we discovered that these curves are remarkably well described by a simple power-law function with a universal power of 0.142 and a HE-specific scaling factor.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Leveraging Radiofrequency Identification Success Beyond Hazardous Material Inventory Management at a National Laboratory

Effective inventory management can be overshadowed by conflicting priorities in organizational procedures, particularly in research-focused institutions such as national laboratories that handle expensive, delicate, and hazardous materials. Here, this study investigated the potential of radiofrequency identification (RFID) technology, currently used for hazardous chemical inventory, in applications with higher metal interference and absorption, specifically pressure release device (PRD) compliance and nuclear container management, at Lawrence Livermore National Laboratory (LLNL). This study was done to document best practices to enhance inventory identification speeds for inventory reconciliation and inventory recall and to explore optimal configurations for RFID implementation compared to traditional manual methods of equipment management. Tests were conducted to determine the ideal RFID tag orientation (read at angles of 0°, 90°, and 270°), various container layouts (linear, separated, curved, operational), and ID methods such as manual, barcode, and RFID performing three trials per method per orientation. Results indicated that 0° was the optimal read angle for minimizing metallic interference, and the operational and curved arrangements significantly outperformed the linear and separated configurations in read speed. 3D printed mounts were developed and tested, increasing the read range of the RFID reader by up to 235% in cases of high metallic interference. The RFID technology demonstrated an average speed increase of 65% over a simplified manual identification, which supports the conclusion that RFID is a more efficient method for large hazardous inventory management and equipment reconciliation. Additionally, capturing meta-data, such as location and date, can be used to query for inventory recall and automated updating of record information.

42 ENGINEERING↗
DOE OSTI2025

Collective neutrino oscillations in three flavors on qubit and qutrit processors

Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated by the quantum many-body nature of the problem due to neutrino-neutrino interactions, which demands a quantum treatment. An additional complication is the presence of three flavors, which often is approximated by the electron flavor and a heavy lepton flavor. In this work, we provide both qubit and qutrit encodings for all three flavors, and develop optimized quantum circuits for the time evolution and analyze the Trotter error. We conclude our study with a hardware experiment of a system of two neutrinos with superconducting hardware: the IBM Torino device for qubits and Advanced Quantum Testbed device at the Lawrence Berkeley National Laboratory for qutrits. We find that error mitigation greatly helps in obtaining a signal consistent with simulations. Finally, while hardware results are comparable at this stage, we expect the qutrit setup to be more convenient for large-scale simulations since it does not suffer from probability leakage into nonphysical qubit space, unlike the qubit setup.

Neutrino oscillations↗
DOE OSTI2025

Cooling Design and Thermal Analysis for Thermal Shields of a Cryocooler-Cooled Superconducting ECR Ion Source MARS-D Magnet

Here, a demonstrative NbTi based Mixed Axial and Radial field System (MARS-D) is being developed for a next-Generation Electron Cyclotron Resonance Ion Source (ECRIS) at Lawrence Berkeley National Laboratory (LBL), which employs a novel closed-loop coil design scheme that more efficiently utilizes conductor fields and extend the application of NbTi for high frequency (up to 45 GHz) ECR operation. The NbTi MARS-D magnet consists of a single hexagonally shaped closed-loop coil and a set of auxiliary solenoids. A cryostat for cooling the MARS-D magnet is under design at LBL. The MARS-D magnet working around 4.2 K will be bath-cooled in liquid helium using multiple two-stage cryocoolers. An intermediate temperature thermal radiation shield is adopted to reduce the heat leakage imposed on 4.2 K coil cold mass from room temperature. The thermal shield is conduction-cooled by the first-stage cold heads of four two-stage cryocoolers and the cold head of a single-stage cryocooler shared with nine binary leads. The temperature in the area of the shield that warm ends of HTS leads are mounted on is expected no higher than 60 K, which is limited by maximum allowable working temperature of HTS leads. The paper presents thermal analysis on the thermal radiation shield including heat loads and effects of eddy current induced during quench on its material selection.

ECRIS↗
DOE OSTI2025

2D reactive transport model of shale chemical weathering and biogeochemical fluxes along a mountainous hillslope, East River Watershed, Colorado: Input files and simulation results

This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterization of the Multi-Coincident Bismuth Germanate Oxide Spectrometer at the Nuclear Counting Facility

A multi-detector γ-ray spectroscopy system including 3 high-purity germanium (HPGe) detectors has been developed at the Nuclear Counting Facility at Lawrence Livermore National Laboratory. This system operates not only in conventional singles γ-ray detection mode but also incorporates features like coincidence and anti-coincidence techniques. These advanced detection modes can significantly enhance the system’s sensitivity, making it a powerful tool for isotope identification and quantification, especially for complex samples with high background and overlapping peaks. In this re port, we present a comprehensive performance characterization of the Multi-Coincident Bismuth Oxide Spectrometer (MCBOS) using a variety of sample types, including 60 Co, 48 Sc, and mixed fission product samples. Each sample provides unique tests for the MCBOS capabilities. Additionally, a GEANT4 model of the MCBOS has been generated to aid with the characterization of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Generator Interconnection Costs to the Transmission System in non-ISO Balancing Authorities [Slides]

Electric transmission system operators—including Independent System Operators (ISOs), Regional Transmission Organizations (RTOs), and utilities—require proposed power plants to undergo a series of interconnection studies before connecting to the grid. These studies assess what transmission upgrades or new infrastructure may be necessary and assign the associated costs to the project. Lawrence Berkeley National Laboratory has compiled, aggregated, and cleaned interconnection cost data, originally for ISOs/RTOs, and now for five non-ISO Balancing Authorities: PacifiCorp, Bonneville Power Authority, Duke Energy Progress, Duke Energy Carolinas and Duke Energy Florida. Insufficient transparency in interconnection cost data may contribute to rapidly expanding interconnection queues, with active queue capacities tripling between 2020 and 2024 in the studied BAs. Most projects withdraw after receiving high interconnection cost estimates. Interconnection costs have increased since the early 2000s, with average costs for "complete" projects reaching $194/kW between 2018 and 2024. Active queue projects and withdrawn projects incur substantially higher costs, primarily due to rising network upgrade costs. Recent interconnection costs in non-ISO balancing authorities are higher than in ISO regions, potentially due to a greater willingness to pay among developers. Utility-scale solar, wind, and storage projects have interconnection costs that exceed those for natural gas. However, when focusing on projects that do not withdraw from the queue, the interconnection costs for these technologies are more similar to natural gas projects. Other key findings include: (1) Larger generation projects benefit from lower proportional interconnection costs, (2) capacity transmission service (NRIS) often requires additional network investments, and (3) projects with high network upgrade costs are often clustered geographically. The dataset includes results from 2,104 interconnection studies conducted between 2000 and 2024, covering projects that are operational, withdrawn, or still progressing through the study process. The Excel file contains (a) the complete project-level interconnection cost dataset, and (b) seven additional tabs summarizing cost metrics across dimensions such as time, market structure, cost category (point of interconnection vs. broader network upgrades), fuel type, service type (ERIS vs. NRIS), generator size, and geography.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

FNCL Enhancements Implementation (FY25 Annual Report)

The FNCL investigations team at Lawrence Livermore National Laboratory (LLNL) has completed research and development of hardware, signal processing, and analysis tools to enhance the measurement capabilities of both the current CAEN SyS VeryFuel Fast Neutron Collar (FNCL) instrument and a next-generation FNCL prototype. The team successfully built and commissioned the LLNL Demonstrator System: a fully integrated, three-panel detector system featuring higher segmentation, plastic scintillators (EJ-276D), Silicon Photomultipliers (SiPMs), no high-voltage requirement, a reduced electronic footprint, and the LLNL-developed Gaussian Mixture Model Pulse Shape Discrimination (GMM-PSD) signal processing. An extensive experimental campaign was conducted at LLNL’s Inherently Safe Subcritical Assembly (ISSA) facility using both the baseline FNCL and the LLNL Demonstrator. The campaign results validated system performance, calibration stability, and the effectiveness of advanced signal processing and analysis algorithms in a relevant environment.

and physical protection↗
DOE OSTI2026

Identifying Barriers to Solar and Storage Hybrids: Modeled vs. empirical wholesale market value and net-value for co-located solar + storage projects [Slides]

Large-scale (1MW+) co-located solar and battery storage projects are expanding rapidly in the United States, but their realized contribution to the bulk power system remains poorly understood because public project-level operating data are limited. The Lawrence Berkeley National Laboratory estimates the wholesale market value of 280 operational photovoltaic-plus-storage (PV+S) projects across the seven ISOs/RTOs and 19 additional balancing authorities, representing roughly 95% of the U.S. PV+S fleet in 2024. We model optimized hourly dispatch under energy, capacity, and ancillary-service market opportunities and compare the resulting value with standalone PV value, project-specific levelized cost estimates, and empirical operating or revenue data where available.

14 SOLAR ENERGY↗