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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Conclusions of a Mini Technical Interchange Meeting on New Cross Risk Integration Projects Managed by the NASA Space Radiation Element

To enable deep space exploration and sustained human presence in space, the NASA Human Research Program’s (HRP) Space Radiation Element (SRE) funds research to characterize and mitigate adverse health outcomes from exposure to space radiation that include risks of carcinogenesis, cardiovascular disease, and central nervous system decrements. Recently, the SRE was tasked with supporting multiple HRP Elements with innovative and enabling projects to inform risk characterization, facilitate mitigation activities, and support crew health and performance. These projects, such as precision health initiative, NASA Omics Archive (NOA) and human sample repositories, are agnostic to any HRP Element, hence the name, Cross-Risk Integration Projects (CRIP). CRIP serves 3 broad purposes: - Services: Generate samples and data and manage the receipt, inventory, archive, and ultimate redistribution of biospecimens created in HRP-funded spaceflight and analog research activities—includes NASA Omics Archive project and various human and animal sample repositories. - Method Development: Identify and evaluate new-to-NASA research or analysis methods or techniques that could fundamentally improve existing or planned research efforts—includes the Translational Radiation Research and Countermeasures Project. - Enabling Capabilities: Demonstrate real-world application by adapting, adopting, and/or developing capabilities to benefit crew health and performance and improve risk mitigation—includes Precision Health Initiative (Pharmacogenomics) and advanced biological systems and engineered tissue microsystems initiative (tissue chips, organ-on-a-chip). To identify new technologies, future work, and solicitations, the SRE organizes themed sessions at annual HRP Investigators’ Workshops (IWS). These technical interchange meetings (TIMs) provide a venue for the scientific community to present ongoing work and engage in open discussion of results, limitations of current approaches, and incorporation of novel experimental strategies, model systems, and other innovative techniques. Here, a summary of the studies presented at the SRE-sponsored mini-TIM at the HRP IWS along with the goals and objectives of the CRIP projects is communicated. The 90-min TIM had 6 speakers who presented impressive novel ideas and work, some of which are funded under CRIP by the Space Radiation Element.

Janapriya Saha↗
DOE OSTI2020

Investigation of Non-Nuclear Plowshare and Vela Uniform Sites - 20447

The Plowshare Program was initiated by the Atomic Energy Commission, a predecessor agency to the US Department of Energy (DOE), to investigate peaceful uses of nuclear devices. 'Vela Uniform,' part of the broader Project Vela, was designed to use nuclear and other explosions to increase the capability of the United States to detect nuclear tests through seismicity. There were underground nuclear tests conducted off the Nevada National Security Site (NNSS) as part of the Plowshare Program (e.g., the Gnome-Coach, New Mexico, Site) and the Vela Uniform Program (e.g., Project Shoal, Nevada, Site) at which the DOE Office of Legacy Management (LM) has been conducting long-term surveillance and maintenance since fiscal year (FY) 2006. There are many additional locations, particularly for the Plowshare Program, that were considered for nuclear tests or used for non-nuclear tests off the NNSS. Some were only named on paper, but at 30 sites, field work such as drilling test wells and conducting tests using conventional explosives was done. A Plowshare nuclear explosion had been proposed at Project Chariot but was canceled in 1962. In 1992, the discovery of soils contaminated with radionuclides from tracer experiments led to a cleanup by the DOE Office of Environmental Management (EM) of the Project Chariot, Alaska, Site, which was completed in 1994. Following the cleanup of the Project Chariot site, EM was concerned that there might be environmental liabilities at other Plowshare or Vela Uniform sites where field investigations were done, even if the nuclear test was never conducted. The EM Program at the Nevada Site Office began examining records and visiting selected locations that were evaluated for Plowshare and Vela Uniform non-nuclear tests. In total, 161 Plowshare and 14 Vela Uniform sites or proposed projects were identified. The Desert Research Institute (DRI) created summaries of the work carried out at these sites and developed a collection of unclassified documents for them. Preliminary investigations had been conducted at these sites by both LM and EM since the early 2000's. In 2016, in preparation for accepting responsibility for the sites, LM started a program to determine if there were any environmental or safety liabilities associated with them. In 2019, LM formally accepted responsibility for these sites off the NNSS where non-nuclear explosive tests were conducted or where underground nuclear tests were proposed as part of the Plowshare and Vela Uniform programs but were never conducted. LM responsibilities will include maintaining institutional knowledge of the sites, responding to public inquiries, and addressing any concerns at each site. To minimize risk associated with site management, LM has archived all historical records compiled by DRI and has performed limited investigations at sites identified by the prior studies as having a higher potential liability. Preserving records related to site operations reduces the risk of doing unnecessary site investigations in the future caused by the loss of institutional knowledge. During the investigations, some maintenance needs were identified and will be addressed by the end of FY 2021. At the end of FY 2021, investigations, maintenance, and archiving activities will be complete. Remnants of test activities found at sites include craters, mud pits, debris, and open boreholes. Open boreholes are being plugged and abandoned in accordance with state regulatory standards. Other issues are being addressed in accordance with land owner requests and preferences as well as state regulations. Archiving activities include the development of project summaries identifying key operational details and current condition to allow site managers to be easily briefed. The LM experience at non-nuclear Plowshare and Vela Uniform sites applies to other programs where there is the potential for liability associated with the non-nuclear aspects of nuclear programs. This may include support activities or early phases of planned nuclear projects. Preserving institutional knowledge enables land managers to adequately address any concerns associated with operations and lowers risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Warming of the lower Columbia River , 1853 to 2018

Abstract Water temperature is a critical ecological indicator; however, few studies have statistically modeled century‐scale trends in riverine or estuarine water temperature, or their cause. Here, we recover, digitize, and analyze archival temperature measurements from the 1850s onward to investigate how and why water temperatures in the lower Columbia River are changing. To infill data gaps and explore changes, we develop regression models of daily historical Columbia River water temperature using time‐lagged river flow and air temperature as the independent variables. Models were developed for three time periods (mid‐19th, mid‐20th, and early 21st century), using archival and modern measurements (1854–1876; 1938–present). Daily and monthly averaged root‐mean‐square errors overall are 0.89°C and 0.77°C, respectively for the 1938–2018 period. Results suggest that annual averaged water temperature increased by 2.2°C ± 0.2°C since the 1850s, a rate of 1.3°C ± 0.1°C/century. Increased water temperatures are seasonally dependent. An increase of approximately 2.0°C ± 0.2°C/century occurs in the July–Dec time‐frame, while springtime trends are statistically insignificant. Rising temperatures change the probability of exceeding ecologically important thresholds; since the 1850s, the number of days with water temperatures over 20°C increased from ~5 to 60 per year, while the number below 2°C decreased from ~10 to 0 days/per year. Overall, the modern system is warmer, but exhibits less temperature variability. The reservoir system reduces sensitivity to short‐term atmospheric forcing. Statistical experiments within our modeling framework suggest that increased water temperature is driven by warming air temperatures (~29%), altered river flow (~14%), and water resources management (~57%).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evolution of standardization and dissemination of cryo-EM structures and data jointly by the community, PDB, and EMDB

Cryogenic electron microscopy (cryo-EM) methods began to be used in the mid-1970s to study thin and periodic arrays of proteins. Following a half-century of development in cryo-specimen preparation, instrumentation, data collection, data processing and modeling software, cryo-EM has become a routine method for solving structures from large biological assemblies to small biomolecules at near to true atomic resolution. This review explores the critical roles played by the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in partnership with the community to develop the necessary infrastructure to archive cryo-EM maps and associated models. Public access to cryo-EM structure data has in turn facilitated better understanding of structure-function relationships and advancement of image processing and modeling tool development. The partnership between the global cryo-EM community and PDB and EMDB leadership has synergistically shaped the standards for metadata, one-stop deposition of maps and models, and validation metrics to assess the quality of cryo-EM structures. The advent of cryo-electron tomography (cryo-ET) for in situ molecular cell structures at a broad resolution range and their correlations with other imaging data introduces new data archival challenges in terms of data size and complexity in the years to come.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Models, data, and scripts associated with “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning”

This data package is associated with the publication “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning’’ submitted to the Journal of Geophysical Research: Machine Learning and Computation (Scheibe et al. 2024). River sediment respiration observations are expensive and labor intensive to obtain and there is no physical model for predicting this quantity. The Worldwide Hydrobiogeochemisty Observation Network for Dynamic River Systems (WHONDRS) observational data set (Goldman et al.; 2020) is used to train machine learning (ML) models to predict respiration rates at unsampled sites. This repository archives training data, ML models, predictions, and model evaluation results for the purposes of reproducibility of the results in the associated manuscript and community reuse of the ML models trained in this project. One of the key challenges in this work was to find an optimum configuration for machine learning models to work with this feature-rich (i.e. 100+ possible input variables) data set. Here, we used a two-tiered approach to managing the analysis of this complex data set: 1) a stacked ensemble of ML models that can automatically optimize hyperparameters to accelerate the process of model selection and tuning and 2) feature permutation importance to iteratively select the most important features (i.e. inputs) to the ML models. The major elements of this ML workflow are modular, portable, open, and cloud-based, thus making this implementation a potential template for other applications. This data package is associated with the GitHub repository found at Please see the file level metadata (flmd; “sl-archive-whondrs_flmd.csv”) for a list of all files contained in this data package and descriptions for each. Please see the data dictionary (dd; “sl-archive-whondrs_dd.csv”) for a list of all column headers contained within comma separated value (csv) files in this data package and descriptions for each. The GitHub repository is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning models trained on the data in “input_data”; (3) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; (4) “examples” contains the visualization of the results in this repository including plotting scripts for the manuscript (e.g., model evaluation, FPI results) and scripts for running predictions with the ML models (i.e., reusing the trained ML models); (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. Furthermore, depending on the number of features used to train the ML models, the preprocessing and postprocessing scripts, and their intermediate results, can also be different branch-to-branch. The “main-*” branches are meant to be starting points (i.e. trunks) for each model branch (i.e. sprouts). Please see the Branch Navigation section in the top-level README.md in the GitHub repository for more details. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please the top-level README.md in the GitHub repository for more details on the automation.

13C↗
DOE OSTI2026

PFLOTRAN modeling data and scripts associated with “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics” submitted to Water Resources Research (Terry et al. 2025). The data package contains the groundwater modeling dataset from PFLOTRAN software. It includes the python script for mesh generation, boundary condition setting, PFLOTRAN input deck formation and postprocessing. It couples groundwater flow and species transport for Hanford Reach river corridor and pipelines the model generation and processing. This model can be used to easily generate the model and analysis for Hanford site. It can also be adjusted to other hydrologic area with ease. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package consists of 6 folders: (1) “data” contains all necessary data as input and intermediate data for processing; (2) “mesh” contains all mesh related files to generate mesh in Hanford Reach river corridor; (3) “model_run” contains the generated script for PFLOTRAN modeling; (4) “notebooks” contains all the Python script to generate the model; (5) “output” contains all the output from the computation; (6) “postprocessing” contains the Python script to generate scientific figure for manuscript. All files are .csv (comma-separated values), .h5 (HDF5 format), .in (input files), .ipynb (Jupyter notebooks), .p (Python pickle), .png (images), .PNG (images), .py (Python scripts), .pyc (Python bytecode), .r (R scripts), .sh (shell scripts), .txt (text files), .vtu (3D mesh/visualization format), .xz (compressed archive), or .zip (compressed archive).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

The Planetary Data System Web Catalog Interface--Another Use of the Planetary Data System Data Model

The Planetary Data System Data Model consists of a set of standardized descriptions of entities within the Planetary Science Community. These can be real entities in the space exploration domain such as spacecraft, instruments, and targets; conceptual entities such as data sets, archive volumes, and data dictionaries; or the archive data products such as individual images, spectrum, series, and qubes.

interface science metadata↗
NASA NTRSDate not supplied

Stewardship Best Practices for Improved Discovery and Reuse of Heterogeneous and Cross-Disciplinary Earth System Data

Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.

best practices↗
NASA NTRSDate not supplied

Laying the Foundations for FAIR-er Science: ISA and the LSDA Data Submission Process in NASA's Evolving Data Management Environment

The Life Sciences Data Archive (LSDA) archives data resulting from research on the effects of spaceflight on humans and the development of countermeasures to mitigate spaceflight hazards. Archivists work with researchers to ensure that unique and high value data products and their metadata are preserved and managed to support current and future research. Currently, LSDA is updating its procedures and data submission requirements in response to the evolving data preservation environment at NASA. LSDA is implementing best practices for research data management through the establishment of clear data submission guidelines, integration of the FAIR (Findability, Accessibility, Interoperability, Reusability) principles, and use of the ISA (Investigation, Study, Assay) research metadata framework for data discoverability and transparency into the data management processes. These changes directly impact LSDA’s requirements for research data submissions. The newly revised Research Data Submission Agreement (RDSA), formerly the Data Submission Agreement (DSA), introduces ISA-compatible metadata collection standards to LSDA’s process. Adherence to LSDA’s data submission guidelines enhances the FAIR-ness of the repository’s collections for future users. This presentation will discuss (1) how submission of research data and associated metadata are impacted by current data management policies, (2) benefits of the adoption of FAIR principles and the ISA metadata framework for retrospective studies utilizing existing LSDA datasets and historic data collections, and (3) the support LSDA will provide to researchers during this transition.

LSDA↗
NASA NTRSDate not supplied

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions rely on plants and crops for crew and ecosystem health. Access to space plant data enables scientists to gain a deeper understanding of biological responses to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, and altered photoperiods. Open Science is the practice of making research available to all, while respecting diverse cultures, fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) mission designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) developed by NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. OSDR started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository (GeneLab), providing detailed metadata on investigation, sample, and assay levels. Today, GeneLab hosts 62 plant datasets which have led to 5 published peer-reviewed meta-analysis publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs are welcoming any ASPB members interested in providing plant expertise for space biology. The addition of ALSDA to OSDR is also expanding analysis capability beyond ‘omics. Now is the time to get involved as a Subject Matter Expert as we establish the framework for modern plant data archiving through the AWGs. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗
NASA NTRSDate not supplied

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, and fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs welcome any ASPB members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗
NASA NTRSDate not supplied

Apollo Botany Experiments and Artemis: Discussion of Botany Experiment Records Digitized as Part of the Apollo Records Synthesis Project (ARSP)

The Artemis Program, with its objective of establishing a sustained human presence on the moon, has rekindled interest in lunar botany as an area of inquiry. Limited availability of collected lunar regolith samples for plant growth experiments underlines the need to leverage all existing historic datasets. As part of NASA’s Life Sciences Data Archive’s (LSDA) Apollo Records Synthesis Project (ARSP), a collection of historic Apollo era botany experiment research records from the former Space Life Sciences Archival Library (SLSAL) collection, these records have been digitized to improve access for data reuse. The records are related to post-mission quarantine experiments conducted to characterize any pathogenic effects of lunar regolith on exposed plant specimens and includes several possible dataset sources such as microscopy photos, laboratory notebooks, correspondence, data sheets, and gas chromatography results. This collection includes the output of investigations of taxa previously under-investigated in the context of space biology. An unusually phylogenetically diverse group of plants are represented in this dataset (including Pinaceae, Poeaceae, Solanaceae, Apiaceae and more). This presentation will discuss the contents of the collection, their historic context, the digitization of the collection, and the opportunities they may provide when placed in the larger corpus of lunar botany regolith experiments.

Archives↗
DOE OSTI2021

PDB ‐101: Educational resources supporting molecular explorations through biology and medicine

Abstract The Protein Data Bank (PDB) archive is a rich source of information in the form of atomic‐level three‐dimensional (3D) structures of biomolecules experimentally determined using macromolecular crystallography, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (3DEM). Originally established in 1971 as a resource for protein crystallographers to freely exchange data, today PDB data drive research and education across scientific disciplines. In 2011, the online portal PDB‐101 was launched to support teachers, students, and the general public in PDB archive exploration ( pdb101.rcsb.org ). Maintained by the Research Collaboratory for Structural Bioinformatics PDB, PDB‐101 aims to help train the next generation of PDB users and to promote the overall importance of structural biology and protein science to nonexperts. Regularly published features include the highly popular Molecule of the Month series, 3D model activities, molecular animation videos, and educational curricula. Materials are organized into various categories (Health and Disease, Molecules of Life, Biotech and Nanotech, and Structures and Structure Determination) and searchable by keyword. A biennial health focus frames new resource creation and provides topics for annual video challenges for high school students. Web analytics document that PDB‐101 materials relating to fundamental topics (e.g., hemoglobin, catalase) are highly accessed year‐on‐year. In addition, PDB‐101 materials created in response to topical health matters (e.g., Zika, measles, coronavirus) are well received. PDB‐101 shows how learning about the diverse shapes and functions of PDB structures promotes understanding of all aspects of biology, from the central dogma of biology to health and disease to biological energy.

Zardecki, Christine↗
DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Prioritizing the selection of CMIP6 model ensemble members for downscaling projections of CONUS temperature and precipitation

Given the mismatch between the large volume of data archived for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and limited personnel and computational resources for downscaling, only a small fraction of the CMIP6 archive can be downscaled. In this work, we develop an approach to robustly sample projected hydroclimate states in CMIP6 for downscaling to test whether the selection of a single initial condition (IC) ensemble member from each CMIP6 model is sufficient to span the range of modeled hydroclimate over the conterminous United States (CONUS) and CONUS sub-regions. We calculate the pattern-centered root mean square difference of IC ensemble member anomalies relative to each model’s historical climatology for shared socioeconomic pathway (SSP) projections over 30-year time periods and compare the ratio of inter-model to intra-model variability for this metric. Regardless of SSP, inter-model variability is generally much greater than intra-model variability at the scales of the CONUS as a whole, as well as for most CONUS sub-regions. However, for some variables and scenarios, inter- and intra-model variability are similar at sub-CONUS scales, indicating that selecting a single IC ensemble member per model may be sufficient to sample the range of projected hydroclimate states in the 21st Century across CONUS, but for specific regions and variables, more careful selection of ensemble members may be necessary. Regionally resolved Taylor diagrams identify where more IC ensemble member downscaling efforts should be focused if resources are available to do so. Our results suggest that, with parsimonious sampling, the requisite computational expense of downscaling temperature and precipitation fields over the CONUS for subsequent CMIP activities may increase only marginally despite the great increase in data volumes with each successive CMIP phase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cadmium isotope systematics in sedimentary carbonate: Extending the utility of the cadmium isotope palaeo-productivity proxy

The cadmium (Cd) isotope compositions of seven Holocene (<11.7 ka) carbonate sediments, including the bulk carbonate, as well as the > 140 μm (zooplankton), <63 μm and < 20 μm (phytoplankton) fractions, and individual species of foraminifera isolated from the bulk carbonate were obtained for sub-samples processed using the Cd-cleaning and Mg/Ca cleaning methods. The respective Cd isotope systematics of each carbonate archive were then compared with the Cd isotope signature within the ocean using modern seawater data. We show that a constant Cd isotope fractionation factor of -0.25 ± 0.03 ‰ (2SE, n = 4) describes the partitioning of Cd from seawater into the carbonate phase ($Δ^{114}Cd_{CdC O_3 - seawater}$), allowing for accurate reconstructions of the past seawater nutrient regime. The Cd isotope signature of the < 63 µm and < 20 µm (phytoplankton) fractions can display comparable values to those recorded in the modern surface ocean, and can be used to model the magnitude of Cd uptake and utilisation in the past ocean. Individual species of planktic and benthic foraminifera, which inhabit different depths of the water column, can provide a full surface to deep water column reconstruction of the Cd nutrient regime, while infaunal benthic foraminifera can be used to interrogate the Cd isotope systematics of sediment porewaters. Bulk sediment and the > 140 µm (zooplankton) fraction also retain important information relating to the overlying water column Cd isotope systematics and can serve as essential archives for palaeo-productivity reconstructions where the separation of individual components from the bulk sediment is not possible. This new Cd isotope palaeo-productivity toolkit can considerably aid reconstruction efforts and vastly improves the ability to quantify the role of phytoplankton in modulating carbon sequestration through transitions in Earth’s climate evolution.

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

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology.

IHMCIF↗
DOE OSTI2026

Analysis of attenuation data from the decommissioned ZIon unit 1 reactor pressure vessel beltline weld

In order to examine the attenuation of radiation damage through the thickness of an irradiated reactor pressure vessel (RPV), four segments were acquired from the Zion Unit 1 power plant RPV after the plant was decommissioned. The Zion Unit 1 RPV Beltline Weld Segment 1 was cut into seven blocks, consisting of five base metal and two beltline welds from the high fluence region of the segment. Through-wall test specimens were machined and tested. Specimens included those used for Charpy impact, Master Curve fracture toughness testing, and chemical analysis. The observed through-thickness ductile-to-brittle transition temperatures in the beltline weld deviated significantly from the expected behavior based on the attenuation of fast fluence as a function of depth into the RPV. Beginning at the inside surface, the 41-J Charpy transition temperature was either flat or slightly increasing until the ¾ -T location. The results of a simple, model-based analysis of the Zion beltline weld material that included the irradiation conditions and material chemistry were generally consistent with industry trend curves and the standard attenuation model, rather than the observed data. Although there was no archive material from the RPV available to permit measurement of the unirradiated properties, fracture toughness specimens fabricated from archive surveillance weld were used to obtain an estimate of the initial through-thickness values of the Charpy transition temperature. The Charpy shifts obtained using this approach were similarly in disagreement with the predictions of the US NRC Regulatory Guide 1.99, Rev. 2. However, testing of irradiated Charpy specimens taken from the RPV following post-irradiation annealing (10 hr. at 500 °C) provided a quite different estimate of the unirradiated properties which improved the agreement between the inferred through-thickness Charpy shifts and exponential attenuation model included in Regulatory Guide 1.99/2. In conclusion, the analysis of the Zion data and data obtained in previous post-mortem examinations of decommissioned RPVs indicates that more work is needed to understand the through-thickness properties of RPV materials in order to properly assess through-wall damage attenuation.

Charpy impact↗