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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Post-fire soil respiration in late growing season (2023 and 2024), Kougarok Fire Complex, Seward Peninsula, Alaska

Field soil respiration data collected in 2023 and 2024 from burned and unburned tussock tundra sites in the Kougarok Fire Complex, near Nome, on the Seward Peninsula of Alaska. Specifically, we measured soil properties and late-growing season CO2 fluxes in patches of unique plant functional types (forbs, shrubs, and graminoids) across two years in tundra recovering from repeated wildfires over the decade. The goal was to identify the main drivers of soil respiration in Arctic tundra underlain by discontinuous permafrost that is recovering from two recent, repeated wildfires that differed in fire age and number of times burned, thereby resulting in different levels of vegetation and subsurface property changes (i.e., successional trajectories). There are five files in *.csv format with one data file and four data description files including data, dictionary, methods, terminology, and file-level metadata. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), is a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic Phase 3 project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Santos, Fernanda [ORNL] (ORCID:0000000191555623)↗
DOE OSTI2026

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗
DOE OSTI2026

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Air temperature↗
DOE OSTI2026

Radiocarbon age at Teller and Kougarok field sites, Seward Peninsula, Alaska

With extreme climate warming in the Arctic, there is increasing focus on permafrost stability and improving understanding of the impacts of thawing permafrost. Understanding the stability of carbon in Arctic permafrost supports our understanding of the global carbon cycle. Organic (plant / wood) samples were collected from varying depths and landscape features at the Teller 33, Teller 47, Teller 51, Kougarok 64, and Kougarok 86 field sites on the Seward Peninsula, Alaska in the summers of 2014, 2017, 2019, and 2021. Carbon 13 and 14 isotopes were measured to find radiocarbon age for collected samples. We also report fraction modern and delta 14C. This dataset contains a *.csv file of radiocarbon measurements and a *.kml file of measurement locations. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

EARTH SCIENCE > CLIMATE INDICATORS > PALEOCLIMATE ↗
DOE OSTI2026

In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Seward Peninsula, Alaska, 2022

The in-situ soil moisture and thaw depth measurements provided in this dataset were collected coincident with airborne overflights of L-band synthetic aperture radar (SAR) instruments at the Teller, Kougarok, and Council study sites on the Seward Peninsula, Alaska. Overflights occurred on August 19, 2022. Soil moisture data at Teller and Kougarok was collected on August 19, and at Council on August 20. Thaw depth, soil pits, and any additional measurements were recorded on August 20 and 21. Field measurements and flights were conducted during the summer of 2022 as a collaboration between the National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE) Project’s Airborne SAR Campaign and the Next-Generation Ecosystem Experiments (NGEE) Arctic Project. This dataset includes a data file (*.csv), a data dictionary (*_dd.csv) and a file-level metadata (*_flmd.csv). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

EARTH SCIENCE > LAND SURFACE > FROZEN GROUND↗
DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗
DOE OSTI2026

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Integrated geological, economic, and risk assessment of underground hydrogen storage

Underground hydrogen storage (UHS) is a promising option to buffer variable renewable power and support the hydrogen economy. Yet this technology is early-stage, and key uncertainties remain about how coupled processes such as geochemical and geomechanical impacts affect long-term storage security. In this paper, we seek to integrate the results from a large, multi-scale research program to quantify core feasibility metrics and situate these studies within ongoing efforts. Through this work, we evaluate hydrogen recoverability during storage by assessing diffusive losses, losses to geochemical interactions and their subsequent impact on geomechanical properties, and losses to residual saturation during injection and withdrawal. Molecular and laboratory studies show that lithologic heterogeneity, pore geometry, and mineral surface chemistry govern hydrogen–rock interactions, controlling loss pathways. High-pressure coreflooding is used to estimate relative permeabilities and measure parameters needed for reservoir-scale sensitivity analyses. These core-scale experiments found early hydrogen breakthrough at low saturations driven by capillary and viscous fingering, which limits pore-space utilization at early times, while repeated injection and withdrawal cycles improve deliverability over time. Technoeconomic factors and purity requirements for end uses are also considered as part of our comprehensive feasibility analysis. Finally, we underscore the importance of geophysical monitoring and tailored injection strategies to maintain integrity and efficiency. Together, these results provide a quantitative foundation for safe, scalable deployment of UHS and highlight priorities for future integrated studies.

08 HYDROGEN↗
DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multi-Scale Modeling and Prototype Development for Electrochemical CO2 Reduction (CRADA Final Report)

In this CRADA project, Lawrence Livermore National Laboratory, Stanford University, SLAC National Laboratory, and TotalEnergies collaboratively executed a multidisciplinary investigation of electrochemical reduction of CO2 to produce sustainable fuels and chemicals. Overall, the project led to an increased understanding of the fundamental processes involved in CO2 electrolysis, from the atomistic scale to the full electrolyzer device scale, ultimately leading to design guidelines for CO2 electrolyzers that will help in their future commercialization. As the model systems, Ag- and Cu-based catalysts were investigated in various forms depending on the electrochemical platform that was utilized to study the activity, selectivity, and durability towards electrochemical CO2 reduction. By employing experimental, theoretical, and computational techniques, the project team experimentally validated multi-physics models, evaluated the experimental levers that lead to increased electrolyzer reaction selectivity and energy efficiency, and used computational optimization to design higher performance electrodes. The learnings of this project were extensively documented in publicly available peer-reviewed journal publications and conference presentations, which serve as a foundation for further work to build from.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗
DOE OSTI2026

Achieving strength-ductility synergy in hierarchical aluminum metal matrix composites via friction extrusion

We report the fabrication of aluminum metal matrix composites (Al-MMCs) with hierarchical architectures via friction extrusion (FE), a scalable, single-step, solid-phase processing technique. Precursor pucks containing 0–15 vol% Al₂O₃ particles were extruded into fully dense AA6061-based composite rods. The FE induced a tree-ring-like architecture of concentric particle-rich and particle-lean bands, yielding refined grains in particle-rich regions and coarser grains elsewhere. At the nanoscale, magnesium in AA6061 selectively reacted with Al₂O₃ particles to form virus-like nodes, improving particle–matrix bonding. This multi-scale design strategy, combining mesoscale architecture, microscale grain refinement, and nanoscale interface engineering overcome the conventional strength–ductility trade-off. Tensile testing showed substantial increases in yield and ultimate tensile strengths while retaining high ductility ( > 20%). Enhanced strain hardening, driven by the accumulation of geometrically necessary dislocations at interfaces, contributed to the performance. The hierarchical microstructure produced by FE demonstrates a promising pathway for scalable fabrication of lightweight MMCs for structural applications requiring a combined high strength and ductility.

Kalsar, Rajib [Pacific Northwest National Laborato↗
DOE OSTI2026

Significant Rural Contributions to Severe Coastal Urban Flooding Through Flow Connectivity

Coastal cities are increasingly threatened by hurricane-induced compound flooding. However, the relative contributions of rainfall-surge interactions and other flood drivers, such as runoff from surrounding rural and local impervious areas, in shaping urban flooding remain unclear. Here, we use a multi-scale Earth system modeling framework to disentangle the contributions of diverse flooding drivers. The results show that urban flooding is primarily affected by topographic factors (low elevation, flat slopes, and localized flow constrictions), rather than increased runoff from their impervious surfaces. Importantly, runoff from rural areas contributes more to severely flooded urban areas with inundation depth exceeding 1.7 m than local runoff. Although rainfall–surge interactions and sea-level rise exacerbate inundation along the coastline, over 90% of the compounding effects are absorbed by wetlands. By resolving flooding processes across scales and components, this study emphasizes the role of runoff from surrounding rural areas in shaping zones of severe urban flooding.

58 GEOSCIENCES↗
DOE OSTI2026

Influence of Powder Characteristics and Processing Methods on Creep Performance of Powder Metallurgy Hot Isostatic Pressed SS316

The U.S. nuclear energy expansion goals are driving the demand for manufacturing routes that can rapidly produce large, complex, near net shape components. Powder metallurgy hot isostatic pressing (PM HIP) is an advanced manufacturing technique that can be economically scaled-up, while alleviating the supply chain challenges that forging and casting face in terms of cost and lead time constraints. This makes PM-HIP a viable technology to aid and accelerate large-scale part manufacturing for nuclear applications. However, large-scale qualification and deployment of this technology require a thorough understanding of the influence of powder feedstock quality, powder handling history, hot isostatic pressing (HIP) parameters, and subsequent heat treatment on microstructural evolution and elevated temperature mechanical performance. The present work focusses on 316 austenitic stainless steel (SS316) which is most commonly used in high temperature environments for nuclear applications Results from this study show that PM HIPed SS316 meets ASME tensile requirements at room temperature and at elevated temperature. However, creep performance of PM-HIPed SS316 remains inferior to its wrought counterpart, demonstrating that tensile performance alone is not a reliable metric for long duration high temperature integrity. Further, this report delineates powder derived microstructural features that govern creep damage, with key evidences pointing to “microstructural inheritance” from gas atomized powder feedstocks. Commercial SS316 powders of varying chemical compositions and recycling histories were studies, and the results showed large differences in elemental segregation, oxide surface layers and secondary phase distributions. Multi-scale characterization revealed segregation of chromium, molybdenum, manganese and silicon at the boundaries and the precipitation of manganese-, silicon-, and molybdenum-oxides. During HIP consolidation, these surface oxides transform into decorated prior particle boundaries (PPBs) and grain boundary inclusions that persist through conventional post-HIP solution annealing treatment. The retained oxides in post-HIP microstructures were found to influence grain growth, precipitation behavior, and ultimately creep cavitation and fracture. Such post-HIP heat treatments are therefore limited by a complex trade-off between grain growth, and oxide coarsening which aggravate creep damage by acting as nucleation sites for cavities. The objective of this work is to establish an integrated processing–structure–property framework for PM-HIP 316 stainless steel by investigating the influence of powder feedstock characteristics in pre- and post-HIP processing as well as to understand the significance of post-HIP heat treatment on microstructural evolution and creep properties. The results from this report emphasize the significance of powder feedstock integrity in improving creep performance of PM-HIPed SS316, by highlight the effect of rapid solidification, elemental segregation, oxide formation and powder recycling on microstructural defect inheritance following HIP consolidation. Rather than considering HIP processing, solution annealing, and mechanical performance independently, this report treats powder production, HIP consolidation, post-HIP thermal processing, and creep deformation as interconnected stages within a continuous metallurgical process. The resulting framework will provide a scientific basis for developing feedstock engineering strategies capable of improving long-term reliability of PM-HIP stainless steels and accelerating their qualification for advanced nuclear applications.

Ajjarapu, Pavan [Oak Ridge National Laboratory (OR↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Multi-scale structural analysis of swift heavy ion-irradiated ZrO 2 and HfO 2

The radiation-induced monoclinic-to-tetragonal phase transition in ZrO 2 and HfO 2 has been the subject of many investigations, but the transformation pathways and underlying structural mechanisms are still not well understood. In this study, microcrystalline powder samples of ZrO 2 and HfO 2 were irradiated with 946 MeV and 1470 MeV Au ions to a wide fluence range up to 3 × 10 13 ions/cm 2 . To characterize beam-induced structural modifications across all spatial length scales, complementary experimental techniques such as synchrotron X-ray diffraction and spallation neutron total scattering were used. The phase evolution of the tetragonal polymorph with increasing ion fluence is accurately described by a heterogeneous track-overlap model that incorporates both direct- and double-impact processes. These damage accumulation processes are an expression of a core-shell ion track morphology that depends on irradiation conditions and target material. Neutron pair distribution function analysis revealed that ion-beam-induced tetragonal ZrO 2 is merely a configurational average of short-range orthorhombic (Pbcn) domains stabilized by a dense network of domain walls. Furthermore, this knowledge is critical for a better understanding of how crystalline-to-crystalline phase transformations proceed at the atomic scale under extreme conditions.

Monoclinic-to-tetragonal phase transformation↗
DOE OSTI2025

Divergent evolution of slip banding in CrCoNi alloys

Abstract Metallic materials under high stress often exhibit deformation localization, manifesting as slip banding. Over seven decades ago, Frank and Read introduced the well-known model of dislocation multiplication at a source, explaining slip band formation. Here, we reveal two distinct types of slip bands (confined and extended) in compressed CrCoNi alloys through multi-scale testing and modeling from microscopic to atomic scales. The confined slip band, characterized by a thin glide zone, arises from the conventional process of repetitive full dislocation emissions at Frank–Read source. Contrary to the classical model, the extended band stems from slip-induced deactivation of dislocation sources, followed by consequent generation of new sources on adjacent planes, leading to rapid band thickening. Our findings provide insights into atomic-scale collective dislocation motion and microscopic deformation instability in advanced structural materials.

Science & Technology - Other Topics↗
DOE OSTI2026

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗