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DOE OSTI2022

Decay spectroscopy of the blocked fission product 130 $\mathrm{I}$

We report numerous applications rely on the identification and quantification of fission products with the activation technique, where γ-rays emitted in the decay are used to estimate the initial activity of the radionuclide of interest. 130 I is a so-called blocked fission product, which can be produced only directly through fission, a property that makes it particularly attractive for nuclear forensics. A source of 130 I was produced using a (p,n) reaction on enriched 130 Te at the Brookhaven Tandem Van de Graaff and its decay was studied with Gammasphere at Argonne National Laboratory. Two new levels were identified, and over 25 transitions were added, removed or re-placed in the level scheme, with intensity measurements made down to I γ = 0.00066 per 100 decays. The uncertainty on the intensities of the strongest transitions, those that are commonly used to quantify the activity of the radionuclide, was improved by a factor of 2 compared to the previous best assessment and discrepancies in the literature values were resolved. A detailed angular correlation analysis further permitted the determination of a number of spin assignments for excited levels and mixing ratios for γ-ray transitions

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

National Critical Minerals Data Dashboard

The Critical Minerals (CM) Data Dashboard provides data-driven insights to help unlock the potential of conventional and unconventional CM resources in the United States. The dashboard focuses on 12 CM essential for producing zero-emission transportation and clean power technology. More information about these CM and potential resources is available in our CM Story Map. Dashboard data sets can be filtered geographically using the options provided along the top of the dashboard. Data sets can also be filtered by various attributes using the options in the expandable side panel on the left side of the screen. The data sets in this dashboard were compiled from multiple sources including the USGS, USEPA, OSMRE, and DHS., Users are encouraged to provide feedback/suggestions on the function and content of the dashboard, as well as any issues that may arise.

Conventional Resources↗

DOE OSTI2020

Sitewide Environmental Impact Statement Site 300 and Arroyo Mocho Lawrence Livermore National Laboratory Alameda and San Joaquin Counties, California (Mid-Term Report)

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300) and 17 acres surrounding the Arroyo Mocho pumping station and the access road to the pumping station (Arroyo Mocho). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April – June, and August 2020. Rare plant surveys were scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. February and March rare plant surveys are scheduled for 2021; therefore, the rare plant survey results in this report should be considered incomplete until the 2021 surveys are conducted. A total of 10 special status plant species were recorded within Site 300 and Arroyo Mocho. Of these 10, three were not previously recorded within the study areas, and include Hospital Canyon larkspur (Delphinium californicum subsp. interius), Jepson’s woolly sunflower (Eriophyllum jepsonii), and Michael’s rein orchid (Piperia michaelii), which all occur at Arroyo Mocho. Special status plant species known from these two sites total 23 rare plant occurrences (populations), which represent an estimated 50,929 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), six occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (49,010 individuals), and 16 occurrences of CRPR 3 & 4 species (1,821 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities. A total of nine vegetation communities were mapped at Arroyo Mocho, of which two are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Final Site 300 Sensitive Botanical Resource Report for the Sitewide Environmental Impact Statement, Lawrence Livermore National Laboratory, Alameda and San Joaquin Counties, California

At the request of Lawrence Livermore National Security (LLNS), Nomad Ecology (Nomad) conducted sensitive botanical resource surveys, and vegetation mapping and classification of the 7,000-acre Lawrence Livermore National Laboratory (LLNL) Experimental Test Site (Site 300). In addition to surveying for sensitive botanical resources, Nomad also compiled existing rare plant and vegetation data provided by LLNL from past monitoring and environmental impact evaluations. The results of these efforts will provide supporting information for a Site-wide Environmental Impact Statement (SWEIS). These surveys were conducted during the months of April-June, and August 2020, and February and March 2021. Rare plant surveys were originally scheduled for February and March 2020; however, February surveys were not initiated because the contract for this work was not finalized, and March surveys were cut short due to the timing of the Covid-19 shelter in place. Therefore, February and March rare plant surveys were conducted in 2021. A total of seven special status plant species were recorded within Site 300. Special status plant species known from the site total 26 rare plant occurrences (populations), which represent an estimated 14,077 rare plant individuals. This total of all special status plant species breaks down to one occurrence of a federally and/or state listed plant species (98 individuals), five occurrences of California Rare Plant Rank (CRPR) 1 & 2 species (11,553 individuals), and 20 occurrences of CRPR 3 & 4 species (2,426 individuals). A total of 35 vegetation communities were mapped at Site 300, of which 20 are considered Sensitive Natural Communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Queued Up: 2025 Edition – Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2024 [Slides]

Electric transmission system operators (ISOs, RTOs, or utilities) require proposed power plants seeking to connect to the transmission grid to undergo a series of impact studies before they can be built. This process establishes what new transmission equipment or upgrades may be needed before a project can connect to the system and assigns the costs of that equipment. The lists of projects in this process are known as “interconnection queues”. In collaboration with interconnection.fyi, Berkeley Lab compiled, aggregated, and cleaned interconnection queue data from >50 transmission grid operators (7 ISO/RTOs and 49 non-ISO balancing areas), which collectively represent ~97% of currently installed U.S. electric generating capacity. The dataset includes requests submitted to queues through the end of 2024, and only includes requests seeking to connect to the transmission grid (not distribution-connected or behind-the-meter projects). The files below include both a PDF report and an Excel data file. The PDF report analyzes interconnection data and metrics through the end of 2024. The Excel data file includes (a) the full project-level interconnection queue dataset through 2024, (b) a codebook (data dictionary) describing each data field, and (c) 35 additional tabs featuring tables summarizing a range of interconnection metrics. Key highlights from the Queued Up: 2025 Edition (featuring data through 2024) include: • As of the end of 2024, there were ~10,300 projects actively seeking grid interconnection in the U.S., representing 1,400 GW of generation and approximately 890 GW of storage. • Historic withdrawal rates alongside relatively fewer new requests resulted in a 12% decrease in total active queue volume compared to the prior year. • Active natural gas capacity (136 GW, +72% year-over-year) increased in 2024, while solar (956 GW, -12%), storage (890 GW, -13%), and wind (271 GW, -26%) capacity decreased. • 408 GW of capacity already has a draft or executed interconnection agreement (IA) but has not yet reached commercial operations. • The time projects spend in queues before reaching COD is increasing. For the regions with available data, the median duration from IR to COD has doubled from <2 years for projects built in 2000-2007 to over 4 years for those built in 2018-2024. • Ultimately, most of this proposed capacity will not be built. Only 13% of capacity that submitted interconnection requests from 2000-2019 had reached commercial operations by the end of 2024; 77% of that capacity had been withdrawn and 10% was still active. • FERC Order 2023 and various other reforms are being implemented. These are important measures to reduce interconnection bottlenecks and enhance grid system reliability, but it is too early to measure and assess their full impact. • New additions for the 2025 edition include: (a) additional detail on data processing and gaps; (b) updates on interconnection reforms; (c) new analysis on interconnection agreements, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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 OSTI2026

Queued Up: 2026 Edition, Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2025 [Slides]

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Tonian Carbonates Record Phosphate-Rich Shallow Seas

The early-middle Neoproterozoic is thought to have witnessed significant perturbations to marine P cycling, in turn facilitating the rise of eukaryote-dominated primary production. However, with few robust constraints on aqueous P concentrations, current understanding of Neoproterozoic P cycling is generally model-dependent. To provide new geochemical constraints, we combined microanalytical data sets with solid-state Nuclear Magnetic Resonance, synchrotron-based X-ray Absorption Near Edge Structure spectroscopy, and micro-X-ray Fluorescence imaging to characterize the speciation and distribution of P in Tonian shallow-water carbonate rocks. These data reflect shallow water phosphate concentrations 10–100× higher than modern systems, supporting the hypothesis that tectonically-driven influxes in P periodically initiated kinetically-controlled CaCO 3 deposition, in turn destabilizing marine carbonate chemistry, climate, and nutrient inventories. Alongside these observations, a new compilation and statistical analysis of mudstone geochemistry data indicates that, in parallel, C org and P burial increased across later Tonian continental margins until becoming decoupled at the close of the Tonian, implicating widespread N-limitation triggered by increasing atmospheric O 2 .

58 GEOSCIENCES↗

DOE OSTI2026

Estimating Fine-Resolution Shortwave Broadband Albedo of Croplands from Harmonized Landsat and Sentinel-2 Data

Altered surface albedo due to land-cover conversions and management is a significant driver of global climate change. Albedo can be directly measured at ground stations, and remote sensing data can be used to scale-up albedo values to regional and global levels. Some previous studies have retrieved fine-resolution (10–30 m) instantaneous albedo and coarse-resolution (500–1000 m) daily mean albedo from remote sensing data, but they all required the input of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo information at 500-m resolution, and none have assembled both instantaneous and daily albedo based exclusively on fine-resolution satellite data. Here, to address this issue, we compiled 387 instantaneous and 346 daily albedo records using field net radiometer measurements from the bioenergy croplands at the W. K. Kellogg Biological Station in southwest Michigan. We then connected these albedo records with a suite of variables derived from harmonized Landsat and Sentinel-2 data through two machine learning algorithms (random forest regression and extreme gradient boosting) to retrieve clear-sky instantaneous and daily shortwave broadband albedo. The performance statistics indicate reasonable accuracy of model results [root-mean-square error (RMSE)] around or below 0.03 except for snow-covered surfaces), suggesting that the retrieval of both instantaneous and daily albedo based exclusively on fine-resolution satellite data is promising. To facilitate the use of fine-resolution albedo products at the global level, future efforts need to include more albedo records of diverse surface cover types, as well as to accurately model daily albedo for cloudy days to address the “clear-sky bias.”

Harmonized Landsat and Sentinel-2↗

DOE OSTI2022

ESS-DIVE Reporting Format for Dataset Package Metadata

ESS-DIVE’s (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) dataset metadata reporting format is intended to compile information about a dataset (e.g., title, description, funding sources) that can enable reuse of data submitted to the ESS-DIVE data repository. The files contained in this dataset include instructions (dataset_metadata_guide.md and README.md) that can be used to understand the types of metadata ESS-DIVE collects. The data dictionary (dd.csv) follows ESS-DIVE’s file-level metadata reporting format and includes brief descriptions about each element of the dataset metadata reporting format. This dataset also includes a terminology crosswalk (dataset_metadata_crosswalk.csv) that shows how ESS-DIVE’s metadata reporting format maps onto other existing metadata standards and reporting formats.Data contributors to ESS-DIVE can provide this metadata by manual entry using a web form or programmatically via ESS-DIVE’s API (Application Programming Interface). A metadata template (dataset_metadata_template.docx or dataset_metadata_template.pdf) can be used to collaboratively compile metadata before providing it to ESS-DIVE.Since being incorporated into ESS-DIVE’s data submission user interface, ESS-DIVE’s dataset metadata reporting format, has enabled features like automated metadata quality checks, and dissemination of ESS-DIVE datasets onto other data platforms including Google Dataset Search and DataCite.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Nuclear Data Sheets for A=48

Experimental nuclear structure data from various reactions and decays are compiled and evaluated for all known nuclides with mass number A=48 (S, Cl, Ar, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni). For each nuclide, detailed evaluated nuclear structure information is presented for each individual reaction and decay, and the best values combining all available data are recommended for spectroscopic properties, such as level energies, half-lives, γ-ray energies and intensities, decay radiations. No excited states have been identified in 48 S, 48 Cl, 48 Co and 48 Ni, among which the first three even have no measured ground-state half-lives and decay modes. For 48 Fe, a level scheme with a sequence of excited states was established for the first time from a recent one-neutron removal measurement by 2021Ya33. Data for excited states in 48 Ar, 48 K and 48 Mn remain limited; no decay scheme has been measured for 48 Ar and 48 K yet, while the decay scheme for 48 Ni is incomplete due to unobserved levels. 48 Ti is the most studied nuclide through various reactions and decays, followed by 48 V, 40 Ca, 48 Sc, and 48 Cr, among which no decay event to 48 Sc has been observed and the decay schemes for 48 V and 48 Cr are considered as incomplete. Furthermore, this work supersedes the previous full evaluations of A=48: 2006Bu08, 1993Bu04, 1985Al14, 1978Be01.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Using MLIR Framework for Codesign of ML Architectures Algorithms and Simulation Tools

MLIR (Multi-Level Intermediate Representation), is an extensible compiler framework that supports high-level data structures and operation constructs. These higher-level code representations are particularly applicable to the artificial intelligence and machine learning (AI/ML) domain, allowing developers to more easily support upcoming heterogeneous AI/ML accelerators and develop flexible domain specific compilers/frameworks with higher-level intermediate representations (IRs) and advanced compiler optimizations. The result of using MLIR within the LLVM compiler framework is expected to yield significant improvement in the quality of generated machine code, which in turn will result in improved performance and hardware efficiency

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Community Data Mining Approach for Surface Complexation Database Development

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. Here the framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2022

libjustify

The libjustify library allows dynamic justification of tabular data in native C. Existing formatting support requires a compile-time commitment to worst-case column widths or complex handcrafted solutions. With libjustify, tabular data is transformed from long, machine-readable format into a human-readable format.

Rountree, BarryL↗

DOE OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗

DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Compilation and Evaluation of Isomeric Fission Yield Ratios

Fission yields are essential data for reactor physics, forensics, and astrophysics. In some cases, the fission yield of a fragment is divided between the ground state and a long-lived excited state, and the relative population of the two states is referred to as the isomeric ratio. In this work, we present a comprehensive compilation of experimental isomeric fission yield ratios for all target and projectile combinations. When possible, these data are combined to provide recommended isomeric fission yield ratios for low energy neutron-induced fission and spontaneous fission. The recommended ratios are compared to the traditional Madland-England model, which attempts to describe the isomeric ratios with a single parameter relating to the angular momentum of the fragment. It is found that the model does not reliably reproduce isomeric ratios outside the few nuclei it was fitted to, and its simplified treatment of the statistical process following population in fission results in average spin values, which are neither constant nor follow a recently observed saw-tooth pattern.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗