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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Axially symmetric e-lens based on McMillan map

In this work, we investigate the transverse dynamics of a single particle in a model integrable accelerator lattice, based on a McMillan axially symmetric electron lens. Although the McMillan e-lens has been considered as a device potentially capable of mitigating collective space charge forces, some of its fundamental properties have not been described yet. The main goal of our work is to close this gap and understand the limitations and potential of this device. We classify possible regimes with stable trajectories and provide set of canonical action-angle variables, along with an evaluation of the dynamical aperture, Poincar\'e rotation numbers as functions of amplitudes, and spread in nonlinear tunes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

DMMSC Talk

The new monthly Dynamic Mesoscale Material Science Capability Seminar Series features Lab highlights from materials science areas, including cutting-edge research at national and international light sources, in-depth investigations of technical gaps, and advanced studies of accelerator technologies that might provide probes in this region.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Water Microgrids: A Primer for Facility Managers

A water microgrid is similar in concept to an energy microgrid, which the U.S. Department of Energy defines as “a local energy grid with control capability, which means it can disconnect from the traditional grid and operate autonomously.” Similarly, a water microgrid is a local water system that supplies, treats, and distributes water, with the primary objective to meet mission critical water demands during a disruption of the primary supply. A water microgrid has the capability to operate independently of an existing primary water system and includes a layer of sensing capability that provides the necessary monitoring and controls to operate the water microgrid. A water microgrid may offer a viable solution for a site to address resilience gaps identified through the resilience planning process. For example, a site may not have adequate and redundant water supply to meet mission critical demands with vulnerabilities in the operating systems. A water microgrid provides the ability to island the water system from the primary water supply to satisfy water demand requirements throughout an outage or disruption.

42 ENGINEERING↗
DOE OSTI2023

Results of the Micromorphic Upscaling Workflow for the PSAAP III Year 3 Report

Predicting the mechanical response and failure of heterogeneous materials has proven difficult. Multiscale numerical methods based in higher order continuum theories attempt to bridge the gap between microscale and macroscale structural behavior. Micromorphic continuum theories have shown promise. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling workflows. These include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This work discusses micromorphic upscaling efforts of the University of Colorado Boulder PSAAP III multidisciplinary simulation center (MSC). Verification studies are presented that compare the accuracy of the upscaling workflow with analytical solutions for a trivial stress state and homogeneous material using direct numerical simulations (DNS) conducted in the Ratel finite element method (FEM) and GEOS material point method (MPM) codes. These verification studies consider upscaling using the Micromorphic Filter for a “single filter domain”. Finally, DNS of a heterogeneous composite material is upscaled using a “multiple filter domain” method.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Axially Symmetric E-Lens Based on McMillan Map

In this work, we investigate the transverse dynamics of a single particle in a model integrable accelerator lattice, based on a McMillan axially symmetric electron lens. Although the McMillan e-lens has been considered as a device potentially capable of mitigating collective space charge forces, some of its fundamental properties have not been described yet. The main goal of our work is to close this gap and understand the limitations and potential of this device. We classify possible regimes with stable trajectories and provide set of canonical action-angle variables, along with an evaluation of the dynamical aperture, Poincar\'e rotation numbers as functions of amplitudes, and spread in nonlinear tunes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Accelerating the identification of novel secondary metabolites in bioenergy plant root exudates using MicroED

Small molecule metabolites drive inter- and intraspecies communication and dependencies in diverse biological systems, yet a large proportion of these important chemical compounds remain uncharacterized in plants and microbes. Approximately 90% of the metabolites in root exudate profiles are unknown compounds, despite the importance of root exudate composition in plant-microbe interactions. We need advanced analytical capabilities that will support rapid discovery and structural elucidation of metabolites from biological samples that may be limited in quantity and high in complexity. To fill this gap, this project aimed to develop an integrated workflow involving metabolite extraction, separation, and crystallization from plant root exudates followed by characterization using nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and microcrystal electron diffraction (MicroED). Using crude root exudates from sorghum, this project successfully developed higher throughput exudate fractionation strategies to obtain pure compounds for crystallization and identified crystals in multiple fractions that diffracted. Additional efforts to increase the throughput of high-quality crystal generation for MicroED, such as crystallization screening and crystallization chaperone exploration, will be needed to further advance root exudate metabolite identification. The overall optimized sample preparation process can then be integrated with the existing data collection and data analysis pipelines for MicroED at PNNL to facilitate more rapid natural product discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Arctic Critical Infrastructure: Assessing and Predicting the Risk to Critical Permafrost Infrastructure from Climate Change: A New Thermomechanical Approach

This study presents the development of a computational framework designed to predict the interaction between permafrost and infrastructure, addressing potential failure modes and mitigation strategies in the context of climate change. The framework, rooted in advanced modeling and simulation (mod/sim) techniques, integrates thermomechanical coupling to account for the complex interplay between heat flow, ice content, and mechanical behavior in permafrost. Existing models fail to fully capture these dynamics, particularly as they relate to the effects of ice saturation on structural integrity. Our innovative Arctic Coastal Erosion (ACE) framework fills this gap by coupling thermal and mechanical models to accurately simulate subsidence and deformation in permafrost environments. We applied the ACE framework to a representative runway, demonstrating its capability to predict settlement due to rising temperatures and subsequent permafrost thaw. This proof-of-concept showcases the potential of the framework to evaluate risks to Arctic infrastructure, which supports over four million people and 70% of existing permafrost-based structures. By simulating various infrastructure types and environmental conditions, our research offers insights into failure mechanisms and evaluates structural solutions to mitigate risk. The anticipated deliverables, including a prototype runway exemplar, position this project as a critical advancement in permafrost infrastructure modeling, with applications in national security and resilience planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Autonomous thermal tracking reveals spatiotemporal patterns of seabird activity relevant to interactions with floating offshore wind facilities

Planning is underway for placement of infrastructure needed to begin offshore wind (OSW) energy generation along the West Coast of the United States and elsewhere in the Pacific Ocean. In contrast to the primarily nearshore windfarms currently in the North Atlantic, the seabird communities inhabiting Pacific Wind Energy Areas (WEAs) include significant populations of species that fly by dynamic soaring, a behavior dependent on wind and in which flight height increases steeply with wind speed. Therefore, a more precise and detailed assessment of their 3D airspace use is needed to better understand the potential collision risks that OSW turbines may present to these seabirds. Toward this end, a novel technology called the ThermalTracker-3D (TT3D), which uses thermal imaging and stereo vision, was developed to render high-resolution (on average within ±5 m) flight tracks and related behavior of seabirds. The technology was developed and deployed on a wind-profiling LiDAR buoy in the Humboldt WEA, located 34 to 57 km off California’s coast. During the at-sea deployment between 24 May and 13 August 2021, the TT3D successfully tracked birds moving between 10 and 500 m from the device, around the clock, and in all weather conditions; a total of 1407 detections and their corresponding 3D flight trajectories were recorded. Mean altitudes of detections ranged 6-295 m above sea level (asl). Considering the degree of overlap with anticipated rotor swept zones (RSZ), which extend 25-260 m asl, 79% of detected birds (per m 3 of airspace) moved below the RSZ, 21% moved at heights overlapping the RSZ, and another 0.04% occurred at heights exceeding the RSZ. The high-resolution tracks provided valuable insight into seabird space use, especially at heights that make them vulnerable to collision during various environmental conditions (e.g., darkness, strong winds). Observations made by the TT3D will be useful in filling critical knowledge gaps related to estimating collision and avoidance between seabirds and OSW facilities in the Pacific and elsewhere. Future research will focus on enhancing the TT3D’s identification capabilities to the lowest taxon through validation studies and artificial intelligence, further contributing to seabird conservation efforts associated with OSW.

17 WIND ENERGY↗
DOE OSTI2020

DOE-ART HT(G)R R&D Overview

The US Government currently has no plans to finance or build advanced nuclear reactors. Instead, the DOE performs research and development to raise the technological readiness of new concepts, fuels and component materials so that private industrial partners are more likely to design and build plants. Develop technologies that can enable new concepts and designs to achieve greater levels of safety and resilience, flexibility of use, sustainability and construction or operational affordability. Collaborate with industry to identify and conduct essential research to reduce technical risk associated with advanced reactor technologies. Sustain essential technical expertise and capabilities within national laboratories, universities, and industry to perform needed research. Collaborate with the Nuclear Regulatory Commission and Standards Developing Organizations (ASME, ANS, ANSI, etc.) to address gaps in codes and standards to support advanced reactor designs

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

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

Multi‐Sensor Trajectory Reconstruction of the 24 April 2025 Alaska Fireball and Implications for Planetary Defense

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. Here, the unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals, with fragmentation source locations further guiding the identification of Doppler weather radar signatures of a meteorite fall. Incorporation of a radar-derived terminal point yielded a final trajectory solution, which agreed closely with an independent optical trajectory solution from video analysis. The reconstructed entry parameters from seismoacoustic analysis indicate a velocity of 25.3 km/s, an entry angle of 19°, and an energy release of ∼38 t TNT equivalent. Assuming a chondritic composition, the pre-entry object diameter was ∼0.7 m. Using orbital parameters from the optical solution, we estimate meteoroid composition as most likely an L-type ordinary chondrite. The event occurred in the sub-Arctic, where space-based optical systems face challenges in detection, demonstrating the critical role of dense ground-based seismoacoustic networks in characterizing high-latitude atmospheric entries. This uniquely well-recorded event demonstrates the capability of dense seismoacoustic networks to constrain bolide trajectories, energetics, and fragmentation, with radar and optical data providing critical confirmation and complementary perspectives. These results bridge the methodological gap between planetary-defense monitoring of natural impactors and space-traffic analyses of artificial reentries, illustrating how multi-sensor integration can deliver calibration-grade trajectories even for unpredicted events.

Fireball↗
DOE OSTI2025

Anomalously slow hot carrier cooling and insulator-to-metal transition in a photo-doped Mott insulator

Photo-doped Mott insulators can exhibit novel photocarrier transport and relaxation dynamics and non-equilibrium phases. However, time-resolved real-space imaging of these processes are still lacking. Here, we use scanning ultrafast electron microscopy (SUEM) to directly visualize the spatial-temporal evolution of photoexcited species in a spin-orbit assisted Mott insulator α-RuCl 3 . At low optical fluences, we observe extremely long hot photocarrier transport time over one nanosecond, almost an order of magnitude longer than any known values in conventional semiconductors. At higher optical fluences, we observe nonlinear features suggesting a photo-induced insulator-to-metal transition, which is unusual in a large-gap Mott insulator. Our results demonstrate the rich physics in a photo-doped Mott insulator that can be extracted from spatial-temporal imaging and showcase the capability of SUEM to sensitively probe photoexcitations in strongly correlated electron systems.

42 ENGINEERING↗
DOE OSTI2025

Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems

Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Momentum-exchange interactions in a Bragg atom interferometer suppress Doppler dephasing

Large ensembles of laser-cooled atoms interacting through infinite-range photon-mediated interactions are powerful platforms for quantum simulation and sensing. Here we realize momentum-exchange interactions in which pairs of atoms exchange their momentum states by collective emission and absorption of photons from a common cavity mode, a process equivalent to a spin-exchange or XX collective Heisenberg interaction. The momentum-exchange interaction leads to an observed all-to-all Ising-like interaction in a matter-wave interferometer. A many-body energy gap also emerges, effectively binding interferometer matter-wave packets together to suppress Doppler dephasing in analogy to Mössbauer spectroscopy. The tunable momentum-exchange interaction expands the capabilities of quantum interaction–enhanced matter-wave interferometry and may enable the realization of exotic behaviors, including simulations of superconductors and dynamical gauge fields.

Science & Technology - Other Topics↗
DOE OSTI2026

A Reverse Logistics Tool For Ev Battery Recycling And Repurposing,

The demand for electric vehicles (EVs) in the United States is projected to rise significantly, with sales expected to reach approximately 4.1 million units by 2030. However, the U.S. remains heavily reliant on imports for the batteries and critical raw materials—such as lithium, cobalt, and nickel—that power these vehicles. As of 2024, around 70% of these imports originate from China. This dependency has become even more precarious following China’s imposition of export restrictions in April 2025, a retaliatory move against U.S. tariffs. These developments highlight the strategic vulnerabilities posed by China’s dominant position in the critical materials market. Compounding the issue, decades of intensive extraction have severely depleted global reserves of critical materials, widening the gap between supply and growing demand. This situation underscores the urgent need for the U.S. and other nations to diversify their sources of critical materials and enhance domestic capabilities to secure these resources—an essential step toward ensuring long-term energy security. At the end of their lifecycle—whether due to the battery’s degradation or the retirement of the vehicle—EV batteries are often improperly disposed of or sent to landfills. However, many of these batteries still retain usable capacity and can follow one of three alternative pathways: (a) Re-used: deployed in another vehicle with a shorter driving range, (b) Re-purposed: utilized act as a backup storage/power for data centers, solar panels, and e-scotters or (c) Recycled: broken down to recover the critical materials. To that end, the proposed tool (REBORN) is designed to optimize the reverse logistics network for battery repurposing and recycling. Its goal is to minimize associated costs while identifying optimal locations for battery collection and processing. Ultimately, REBORN ensures that each battery is used to its fullest potential.

Srinivas, SrikarV. [Idaho National Laboratory (INL↗
DOE OSTI2021

Advanced Ultra-Supercritical Component Test (ComTest) Project for 760*C Steam Conditions

ComTest is a $27M Department of Energy-funded project. Phase I, which began in November 2015, served to identify the technology gaps, as well as the scope and cost of required testing. Phase II, which was awarded in December 2018, includes an advanced manufacturing effort to complete U.S. based supply chain development for full commercial scale (800-850 MWe) AUSC components made of nickel-based alloys, components operating at up to 760°C. Completion of Phase II scheduled for September 30, 2021. Strategic Objectives of U.S. AUSC Project include: Power Plant Efficiency Improvements –Develop cost-effective, reliable technologies to improve the efficiency of new and existing high-temperature advanced generation power plants. Close gaps to achieve readiness for commercial scale demonstration of Advanced Ultra-Supercritical (AUSC) technology. Fabricate full-scale versions of key nickel-based alloy components. Validate capabilities of US supply chain for cost certainty. Support cross-cutting high-temperature generation technologies. Obtain ASME Code approval for new materials, components and processes. Increase power plant steam temperatures for higher cycle efficiency (Note: Average efficiency of US coal-fired fleet = 33% HHV; A-USC plant efficiency over 47% HHV at 1,400°F (760°C) steam temperature).

fireside corrosion↗
DOE OSTI2022

Occurrences of REE and CM in volcanic ash beds associated with coals in SW Wyoming & NW Colorado

Rare earth elements (REEs) and critical minerals (CMs) are vital components in the nation’s economy, national security, and the further strengthening of our renewable energy capabilities and infrastructure. Recent work has revealed more insight into previously unknown modes of occurrence for REEs, particularly in coal seams and adjacent noncoal sediments, but many data gaps persist. Temporal relationships between coal beds and adjacent tonstiens, ash beds, or other partings are widely recognized but not fully understood. Variations in REE concentration and their direct or indirect association with coal beds are not predictable. This study presents findings from examining lateral and potentially stratigraphic variation of REE and CM occurrences in coals of late Cretaceous and Paleocene age. In this study we collected and examined samples of differing ages both core and coal mine exposures for qualitative x-ray fluorescence (XRF), and multi-element geochemistry. Preliminary XRF data indicates variable levels of light REEs in a core from the Yampa coalfield of Moffat County in northwest Colorado. An absence of similar enrichments in slightly older coals in the Adaville Formation of the Fold and Thrust belt in southwest Wyoming is described from XRF and ICP-MS evaluation. Previous work has shown an association with the Yampa Bed and REE enrichment in coals of the Upper Cretaceous Williams Fork Formation. While not common and widespread, this association suggests that leaching or reworking of the ash bed could lead to elevated REEs in the adjacent coal. We investigate differences between the two data occurringas geologic compositions and post-depositional histories. In-depth petrography and precise geochemistry should reveal data that at the very least will help improve some aspects of the geologic models of coal basins and the effect of an influx of non-coal sediments.

REE, CM, ash, volcanic ash, coal↗