Search NASA⌕ Search

SEARCH · Search NASA

Results for “data review”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comprehensive GOM Federal Waters Platform, Incident, Metocean, and Geohazard Dataset

The dataset contains integrated data from an array of disparate data sources, all spatially and temporally linked to platforms in the federal waters of the Gulf of Mexico (platform data from BSEE, 2020). Integrated data includes past reported incidents dating back to 1956 (BSEE, BOEM, MMS), metocean data (see Nelson et al. in review for source information), and geohazard data (see Nelson et al. in review for source information). Proprietary well production information was redacted from this dataset, but was used in resulting analytics.

Full System↗
DOE OSTI2020

Review of the Nuclear Energy Agency (NEA) Ancillary Thermodynamic Database (TDB) Volume (DRAFT REV. 0)

The Nuclear Energy Agency (NEA) Ancillary data volume comprises thermodynamic data of mineral and aqueous species that, in addition to Auxiliary Data (as referred to in previous NEA thermodynamic data volumes), is necessary to calculations of chemical interactions relevant to radioactive waste management and nuclear energy. This SAND report is a review of the NEA Ancillary data critical reviews volume of thermodynamic data parameters. The review given in this report mainly involves data comparison with other thermodynamic data assessments, analysis of thermodynamic parameters, and examination of data sources. Only new and updated data parameters were considered in this review. Overall, no major inconsistencies or errors were found as allowed by the comparisons conducted in this review. Some remarks were noted, for example, on the consideration of relevant studies and/or comparisons on the analysis and retrieval of thermodynamic data parameters not cited in the respective sections.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗
DOE OSTI2023

Review of Current Software for Analyzing Total X-ray Scattering Data from Liquids

The popularity of the pair distribution function (PDF) analysis of X-ray total scattering data has steadily grown as access to ex situ synchrotron data has expanded. Due to the broadening of the PDF user community, there is a growing demand for software that can be used to extract PDFs and is accessible to non-expert users. While user-friendly options have been developed over the past decade for fast, streamlined data analysis, care must be taken in both processing the data and understanding any limitations, especially in the case of liquids. In this review, the same scattering data are analyzed using different total X-ray scattering software, in order to compare the accuracy of the extracted structure factors and associated pair distribution functions. The goal is to assess the best practices for extracting the most accurate liquid data for each software package. The importance of absolute normalization and the application of the most appropriate corrections are emphasized via quantitative comparisons between liquid sulfur and water. Additionally, an awareness of the competing conventions used to define the PDF in crystallography and liquids/glasses is crucial for both the downstream analyses of the data and a comparison with the previous results in the literature.

Gallington, Leighanne C. (ORCID:0000000203837522)↗
DOE OSTI2026

Model scripts associated with “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale”

NOTE: The manuscript associated with this data package is currently in review. The data/scripts may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final scripts and additional metadata. This data package is associated with the publication “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale” submitted to Environmental Science & Technology (Zheng et al. 2026). The project combines mechanistic process modeling with knowledge-guided machine learning (KGML) to evaluate how organic matter chemistry, microbial biomass, and physical substrate accessibility regulate realized respiration rates across river corridors. All data used in this paper have been previously published and can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719 (Goldman et al., 2020). This data package contains 3 R-markdown (Rmd) preprocessing scripts for the previously published data and subsequent modelling workflows. The full workflow with input and output data can be found in the associated GitHub repository at https://github.com/jianqiuz/KGML-WHONDRS.

Biogeochemistry↗
DOE OSTI2024

Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city advancement

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite their effectiveness, these applications often rely on massive amounts of high-dimensional and multi-domain data for monitoring and characterizing different urban sub-systems, presenting challenges in application areas that are limited by data quality and availability, as well as costly efforts for generating urban scenarios and design alternatives. As an emerging research area in deep learning, Generative Artificial Intelligence (GenAI) models have demonstrated their unique values in content generation. This paper aims to explore the innovative integration of GenAI techniques and urban digital twins to address challenges in the planning and management of built environments with focuses on various urban sub-systems, such as transportation, energy, water, and building and infrastructure. The survey starts with the introduction of cutting-edge generative AI models, such as the Generative Adversarial Networks (GAN), Variational Autoencoders (VAEs), Generative Pre-trained Transformer (GPT), followed by a scoping review of the existing urban science applications that leverage the intelligent and autonomous capability of these techniques to facilitate the research, operations, and management of critical urban subsystems, as well as the holistic planning and design of the built environment. Based on the review, we discuss potential opportunities and technical strategies that integrate GenAI models into the next-generation urban digital twins for more intelligent, scalable, and automated smart city development and management.

3D city modeling↗
DOE OSTI2022

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Data for Grogan et al. "Bringing Hydrologic Realism to Water Markets"

This data set provides model output and post-processing files required to reproduce the results, tables, and figures in the paper "Bringing Hydrologic Realism to Water Markets" by Grogan et al. (in review). Other input data used in this study includes: Lisk, M., Grogan, D., Zuidema, S., Caccese, R., Peklak, D., Zheng, J., Fisher-Vanden, K., Lammers, R., Olmstead, S., & Fowler, L. (2023). Harmonized Database of Western U.S. Water Rights (HarDWR) (Version v1) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/2205619 Two models were used in this study: (1) The University of New Hampshire Water Balance Model WBM, and (2) a Water Market Model. Market model code and model output post-processing code that make use of these data can be found here Model output files are: 1. WBM output files: scenario[x]_wbm_output.zip Where [x] is one of 1, 2, 2a, 3, and 3a Each zipped directory contains 7 gridded NetCDF files, each reporting the 10-year annual average value of a given variable, in units of average mm/day: File Name: wbm_indUseGross_yc.nc; Description: Water withdrawals by industry (part of the urban sector) File Name: wbm_domUseGross_yc.nc; Description: Water withdrawals by the domestic sector (part of the urban sector) File Name: wbm_irrigationGross_yc.nc; Description: Water withdrawals for agriculture File Name: wbm_irrigationExtra_yc.nc; Description: Water withdrawals from unsustainable groundwater for agriculture File Name: wbm_indUseEvap_yc.nc; Description: Consumptive water use by industry File Name: wbm_domUseEvap_yc.nc; Description: Consumptive water use by the domestic sector File Name: wbm_irrigationNet_yc.nc; Description: Consumptive water use by agriculture The file full_cell_area.nc gives the area of each grid cell in km2, which is used for converting water depth to water volume. 2. Water market model output & post processing output Folder: marketTrdSummaries/ Description: Files in this folder are used as input to code 1_WelfareCalculation_actual_trades.R. They summarize historical water right trade transactions in each state. File Name: welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: welfare_data_actual.rdata; Description: welfare gains by WMA from actual historical trades, as shown in Figure 3A. This data is the output of code 1_WelfareCalculation_actual_trades.R File Name: welfare_summary_simulated.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 1. Produced by code 2_DemandCurves_simulated_trades.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs_SGMS.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2a. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_data_actual.rdata; Description: Spatial data, actual historical welfare gains by WMA as shown in Figure 3A. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated.rdata; Description: Spatial data, simulated Scenario 1 welfare gains by WMA as shown in Figure 3B. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs.rdata; Description: Spatial data, simulated Scenario 2 welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs_SGMA.rdata; Description: Spatial data, simulated Scenario 2a welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. Additional files are provided for efficient reproduction of tables and figures. These include: File Name: wma_thresold_dates_Scenario2(a).csv; Description: Wet vs. paper right threshold dates for each WMA. Shown in Figure 2A,B. Produced and used by code calculate_thresolds_Figure2.R File Name: WWRTradeBounds (directory); Description: Trade boundary shapefile required to reproduce Figure 3A-D. Used in code Figure3.R File Name: welfare_region_totals.csv; Description: Welfare gains for the entire study region, as shown in Figure 3E. Used in code Figure3.R File Name: Welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: WECC_MERIT_5min_v3b_mask.nc; Description: Gridded file that identified which land grid cells are in the WBM model domain, used for processing in code Figure4.py File Name: Table_1.csv; Description: All data in Table 1, reproducible from WBM output files using code table_1.R

Economics↗
DOE OSTI2024

Development of National New Construction Weighting Factors for the Commercial Building Prototype Analyses (2008-2022)

The U.S. Department of Energy (DOE) tasked Pacific Northwest National Laboratory (PNNL) with updating commercial building construction weights for the purpose of estimating national and state-by-state energy savings impacts of changes made to various commercial energy codes and standards. A similar activity was last completed by PNNL in 2020 using disaggregate construction volume data acquired from the Dodge Data & Analytics database (formerly McGraw Hill) for the years 2003-2018 (Lei et al, 2020). As time passes, changes in economic and social demand reshape construction volume trends. For the current update, PNNL reviewed the same data source with the latest construction data for the years 2008-2022. For commercial building analyses, PNNL typically uses a suite of 16 prototype buildings simulated in the 19 ASHRAE climate zones with 16 of them present in the United States. The 2008-2022 commercial building weighting factors were derived using the same approach employed to develop the 2003-2018 set (Lei et al, 2020). Applying the construction volume data from the database to the prototypes and climate zones resulted in the following new construction area-based weighting factors. Table ES.1 shows the weighting factors including all building categories found in the database, and Table ES.2 shows the weighting factors normalized to include only buildings represented by the 16 prototypes. Section 3.0 also includes national- and state-level weighting factors by area and building count.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Critical Literature Review of Low Global Warming Potential (GWP) Refrigerants and their Environmental Impact

Refrigeration and air conditioning currently account for ~20% of the total electricity consumption in buildings around the world. Over the next three decades as global temperatures are projected to increase, urbanization and economic growth will lead to an increased demand for refrigeration and cooling. Most commonly used refrigerants belong to the five following classes: (i) chlorofluorocarbons, (ii) hydrochlorofluorocarbons, (iii) hydrofluorocarbons (HFCs), (iv) hydrofluoroolefins (HFOs), and (v) natural refrigerants. Over the past century, there have been shifts in which compounds were used for refrigeration to improve safety and durability, allow for ozone protection, and, most recently, to reduce global warming potential (GWP). Although technological advances have led to increased cooling capacity and safer refrigerants, emissions from refrigeration systems can affect the environment by contributing to greenhouse gas emissions or by depleting the ozone layer, depending on the gas emitted. The focus is increasingly on adopting compounds that are both efficient at cooling and effective for reducing emissions and other adverse environmental impacts. Because of policy and regulatory changes to avert ozone depletion and global climate change, much discussion has centered on the environmental impacts of next-generation refrigerants. Of particular interest are the fluorinated refrigerants, HFCs and HFOs, most of which are defined as per- and polyfluoroalkyl substances (PFAS) and their breakdown products (especially trifluoroacetic acid). The US Environmental Protection Agency in 2021 drafted a Strategic Roadmap for PFAS, which has already resulted in an increase in investment in research on these compounds and has restricted the release of PFAS into the environment through the implementation of monitoring and reporting requirements. A critical evaluation of fluorinated refrigerants and their breakdown products with respect to persistence, biodegradation and toxicity, and global warming potential is needed to guide environmental regulations. This document aims to perform a critical review of the relevant scientific data on the most common refrigerants currently used, their degradation products, and their alternatives. Where available, estimates of precursor production quantities and existing environmental regulatory information are reviewed. Key data of interest for the evaluation include physicochemical properties, environmental fate parameters, ecological or human health toxicity/risk information, and GWP for compounds of interest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Critical Literature Review of Low Global Warming Potential (GWP) Refrigerants and their Environmental Impact

Refrigeration and air conditioning currently account for ~20% of the total electricity consumption in buildings around the world. Over the next three decades as global temperatures are projected to increase, urbanization and economic growth will lead to an increased demand for refrigeration and cooling. Most commonly used refrigerants belong to the five following classes: (i) chlorofluorocarbons, (ii) hydrochlorofluorocarbons, (iii) hydrofluorocarbons (HFCs), (iv) hydrofluoroolefins (HFOs), and (v) natural refrigerants. Over the past century, there have been shifts in which compounds were used for refrigeration to improve safety and durability, allow for ozone protection, and, most recently, to reduce global warming potential (GWP). Although technological advances have led to increased cooling capacity and safer refrigerants, emissions from refrigeration systems can affect the environment by contributing to greenhouse gas emissions or by depleting the ozone layer, depending on the gas emitted. The focus is increasingly on adopting compounds that are both efficient at cooling and effective for reducing emissions and other adverse environmental impacts. Because of policy and regulatory changes to avert ozone depletion and global climate change, much discussion has centered on the environmental impacts of next-generation refrigerants. Of particular interest are the fluorinated refrigerants, HFCs and HFOs, most of which are defined as per- and polyfluoroalkyl substances (PFAS) and their breakdown products (especially trifluoroacetic acid). The US Environmental Protection Agency in 2021 drafted a Strategic Roadmap for PFAS, which has already resulted in an increase in investment in research on these compounds and has restricted the release of PFAS into the environment through the implementation of monitoring and reporting requirements. A critical evaluation of fluorinated refrigerants and their breakdown products with respect to persistence, biodegradation and toxicity, and global warming potential is needed to guide environmental regulations. This document aims to perform a critical review of the relevant scientific data on the most common refrigerants currently used, their degradation products, and their alternatives. Where available, estimates of precursor production quantities and existing environmental regulatory information are reviewed. Key data of interest for the evaluation include physicochemical properties, environmental fate parameters, ecological or human health toxicity/risk information, and GWP for compounds of interest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exploring Secondary Markets to Improve Circularity: A Comparative Case Study of Photovoltaics and Hard-Disk Drives

Each year renewable energy generation increases notably with solar panel installations, but these panels have a limited lifespan and will produce between 2 and 4 million metric tons of waste by 2040. Similarly, there are currently between 20 to 70 million hard-disk drives (HDDs) reaching end-of-life (EOL) annually. The circular economy (CE) strives to recycle and reuse materials that are rare and expensive to obtain, minimizing waste. However, studying the potential circularity of photovoltaics (PV) and HDDs requires various data, for instance, on the maturity of the secondhand markets. In this context, the objective of the present study is to identify the current state of secondhand PV and HDD markets. After conducting a literature review, an automated data collection process was set up for that purpose. The analysis of the literature and collected data assess the maturity of the secondhand PV modules and HDDs markets and highlight differences between them.

agent-based modelling↗
DOE OSTI2022

Machine-Learning Assisted Identification of Accurate Battery Lifetime Models with Uncertainty

Reduced-order battery lifetime models, which consist of algebraic expressions for various aging modes, are widely utilized for extrapolating degradation trends from accelerated aging tests to real-world aging scenarios. Identifying models with high accuracy and low uncertainty is crucial for ensuring that model extrapolations are believable, however, it is difficult to compose expressions that accurately predict multivariate data trends; a review of cycling degradation models from literature reveals a wide variety of functional relationships. Here, a machine-learning assisted model identification method is utilized to fit degradation in a stand-out LFP-Gr aging data set, with uncertainty quantified by bootstrap resampling. The model identified in this work results in approximately half the mean absolute error of a human expert model. Models are validated by converting to a state-equation form and comparing predictions against cells aging under varying loads. Parameter uncertainty is carried forward into an energy storage system simulation to estimate the impact of aging model uncertainty on system lifetime. The new model identification method used here reduces life-prediction uncertainty by more than a factor of three (86% ± 5% relative capacity at 10 years for human-expert model, 88.5% ± 1.5% for machine-learning assisted model), empowering more confident estimates of energy storage system lifetime.

25 ENERGY STORAGE↗
DOE OSTI2020

Gen3 CSP Materials: Critical Review of Limited Existing and New Survey Data

Abstract Novel high temperature (≥ 700°C) Heat Transfer Medias (HTMs, e.g., molten salts) and corrosion-resistant Containment Materials (CMs, e.g., metal alloys or ceramics) are necessary for concentrated solar power (CSP) given the emphasis on higher temperatures and high cycle efficiency in the 3rd generation CSP (Gen3 CSP) technologies. In early 2019, we sent out an online survey to the Gen3 CSP community to fully assess the communal needs for thermophysical properties measurements of which HTMs and CMs, and what temperature range and other testing environments would be ideal for those materials. Based on the recorded responses, seven unique HTMs and twenty-six unique CMs were identified. Since then the list has been constantly updated, following our interactions and inputs from the Gen3 CSP community, with some new materials substituting their older counterparts. Currently, there are total of ten unique HTMs and twenty-nine unique CMs that are under consideration by the Gen3 CSP community. By analyzing the available body of research to date and combining it with our survey data from within the Gen3 CSP community, this paper presents trends of what people in the CSP world are thinking regarding materials worth investigating and suggests which thermophysical property measurements are critical to advance high-temperature CSP systems.

Gunawan, Andrey↗
DOE OSTI2022

Independent Review of Groundwater Remediation Strategy for Hexavalent Chromium and RDX Groundwater Plumes at Los Alamos National Laboratory (Rev. 1)

Site operations at the Los Alamos National Laboratory (LANL) resulted in the release of oxidized chromium, Cr(VI), into Sandia Canyon from cooling tower effluent from 1956 until 1972. The chromium traveled with the surface water approximately 3 miles downstream before migrating below ground surface. Chromium concentrations exceed 50 μg/L in the upper portion of the aquifer. Another LANL groundwater plume of concern is associated with RDX (Royal Demolition Explosives, 1,3,5-trinitro-1,3,5-triazine). Between 1951 and 1996, RDX was released to the mesa-top facilities' process water outfall, adjacent and underlying soils, and alluvial sediments, along with surface water in Cañon de Valle. Between 2000 and 2010, two remedial actions were deployed, removing much of the near-surface RDX, however, recharge due to precipitation has transported RDX into the perched-intermediate zone and into the regional aquifer. The report documents an independent technical review by scientists from the Department of Energy (DOE) Network of National Laboratories for Environmental Management and Stewardship (NNLEMS) to provide recommendations for potential near term actions to address and optimize remediation for both the Cr(VI) and RDX plumes. The proposed near-term remedial actions include design of pump and treat systems for Cr(VI) and monitoring and study for natural attenuation for RDX. The review assesses existing data, conceptual and numerical modeling, and it recommends a technical integration process to support identifying and implementing strategic, effective and efficient remedies. The DOE Environmental Management Los Alamos Field Office (EM-LA) and their cleanup contractor Newport News Nuclear-BWTX, LLC Los Alamos (N3B) provided the information required for the review. Interviews were also conducted with regulators to obtain the full spectrum of technical, regulatory and scientific perspectives. The independent review team was impressed by the capabilities, experiences, innovativeness, and insightfulness of the technical representatives from both the regulator, the New Mexico Environment Department (NMED) and N3B. Incorporation of vadose zone flow pathways in the conceptual site model (CSM) and configuring the numerical modeling for the site was generally state-of-the-practice (or better). This could be considered state-of-the-art by addressing uncertainties related to spatial extent of hydraulic windows. The reviews from the regulators were thorough and often provided useful concepts for consideration and future/study resolutions. The overarching consensus recommendation of independent review team is that the LANL groundwater plumes should be addressed in context of the emerging "management of complex sites" paradigm.

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

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Transition Metals Separation with Commercial Neutral Extractants – A Review

The increasing use of extraction chromatography resins across fields such as hydrometallurgy, nuclear medicine, and environmental analysis has created a need for a deeper understanding of their interactions with transition metals. Despite extensive research on f-element separations, the behavior of transition metals in these systems remains relatively understudied. This review provides a comprehensive overview of the current state of knowledge on the extraction behavior of transition metals with neutral extractants, including TODGA, TEHDGA, TBP, and CMPO, and their corresponding resins, such as DGA, BDGA, UTEVA, TBP, and TRU. The review summarizes extraction data, extracted complex coordination environments, separation reaction stoichiometries, and associated thermodynamics, highlighting inconsistencies and knowledge gaps in the literature. The study emphasizes the need for further research using spectroscopy and computational methods to elucidate extraction mechanisms and to improve the efficiency and selectivity of transition metal separations. By identifying areas for future research and development, this review aims to stimulate advancements in the field and promote the development of innovative separation technologies. The implications of this research are far-reaching, with potential applications in nuclear waste management, nuclear forensics, metal recovery, and environmental remediation. Overall, this review provides a foundation for future studies on the extraction of transition metals using neutral extractants and resins.

Wall, Nathalie A.↗