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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 91 records · Page 5

Numerical Simulation and Modeling of Hydrogen Gas Evolution on Planar and Microwire Array Electrodes

The impact of gas evolution on the electrochemical characteristics of planar electrodes and microwire array electrodes has been analyzed using modeling and simulation. The impacts can mainly be broken into three phenomena: a) a shift in the local reversible hydrogen electrode potential; b) hyperpolarization; and c) an increase in the solution resistance of the electrolyte. The local reversible hydrogen electrode potential shift was found to play the most important role, constituting >40% of the total potential drop between the cathode and reference electrode, following correction for cell resistance. Compared to planar electrodes, a microwire array structure reduces the impact of bubbles on the solution conductance, but the shift in the local reversible hydrogen electrode potential varies with distance from the actual electrode surface.

25 ENERGY STORAGE↗

Birefringence in thermally anisotropic relativistic plasmas and its impact on laser–plasma interactions

One of the paradigm-shifting phenomena triggered in laser–plasma interactions at relativistic intensities is the so-called relativistic transparency. As the electrons become heated by the laser to relativistic energies, the plasma becomes transparent to the laser light even though the plasma density is sufficiently high to reflect the laser pulse in the non-relativistic case. This paper highlights the impact that relativistic transparency can have on laser-matter interactions by focusing on a collective phenomenon that is associated with the onset of relativistic transparency: plasma birefringence in thermally anisotropic relativistic plasmas. Here, the optical properties of such a system become dependent on the polarization of light, and this can serve as the basis for plasma-based optical devices or novel diagnostic capabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗

Effects of a strong applied magnetic field on relativistic laser-plasma interactions

This project investigated the role played by strong external magnetic fields in laser-matter interactions at relativistic intensities and their impact of resulting high-energy density phenomena. The regimes that can benefit from currently available or soon to be available magnetic fields have been identified. The applications of this project include laser-driven ion acceleration and laser-driven plasma heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The right conditions for high-precision dynamic temperature and heat capacity measurement via pyrometry and conductivity

The pursuit of accurate bulk temperature T under extreme conditions has been a long-standing goal of the high pressure science community, complicated by a lack of data to inform models. To reach these extremely high-pressure, high-temperature (high P − T) conditions, a combination of dynamic and heated static experiments (e.g., diamond or gem anvil cel experiments) are used. For example, in a diamond anvil cell (DAC) experiment, a sample placed in the DAC is first pressurized. Following pressurization, the sample T is increased either by heating the entire DAC (usually using resistive heating, and limited to ∼1000K) or by applying intense laser power to the sample surfaces. In a dynamic experiment, the process of pressurizing the sample also heats it. In the case of shock physics experiments, such heating is substantial, easily reaching thousands of Kelvin; in our work we have seen T ∼17000K. Most methods of measuring temperature at ambient are not compatible with experiments under these high-pressure, high-temperature conditions: thermocouples break, melt, or have conductivity properties that differ from ambient where they are calibrated; thermometers would melt; both are too slow. As a result most methods are based on non-contact techniques such as x-ray diffraction broadening, neutron scattering, or optical methods. Of these, optical methods using the visible and near-infrared region of the spectrum are the most commonly used as the sources and detectors are readily available. In the case of optical methods the optical depth, and therefore the measurement location, is limited to the surface. When a window or anvil material is used, heat flows from the sample into the window/anvil. Likewise, if the sample undergoes a change in thermodynamic state, such as expansion upon release, different T may be expected. As a result, the surface or apparent temperature T app measurement will differ from the bulk or interior temperature that is desired. This surface measurement must be related to the bulk measurement using thermal transport models and material models. While it is tempting to conclude that one should just use x-ray methods that directly probe the interior, even these methods have been shown to depend on thermal transport and material models. Regardless of the method used to create the high P − T condition, therefore, we must understand the role of thermal transport and material models upon our interpretation of the T measurement, as well as the errors and uncertainties associated with the choice of models used in the analysis. This is a substantial area of research and this paper is by no means a complete survey of the relevant sources of uncertainty. For example, we have yet to begin to address alternate transport models in a detailed manner (e.g., Tan-Ahrens), or the many models that use additional layers to approximate melting, turbulence, or epitaxial phenomena). Likewise, we have not explored the impact upon uncertainty of thermal models that use temperature-dependent thermal transport coefficients, or the wide range of material models that can be applied. Instead, this paper focuses on using one simple model, the Urtiew-Grover model, to understand the sources of error in T measurement so that we may identify how best to focus future research efforts to return the best improvements and avoid working on over-optimizing a single type of measurement. To this end, we work through some of the best and worst case scenarios for T measurement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Considerations for Hydride Moderator Readiness in Microreactors

The emergence of microreactor technology has helped to drive supporting nuclear materials qualification and acceptance processes. One essential component in these small reactors is a solid moderator, which typically consists of metal hydride and cladding. While the behavior and performance of metal-hydride moderators go back to early advanced reactor development for nuclear-powered aviation and space propulsion, there remains a knowledge gap in the understanding of hydrogen transport–related phenomena and irradiation performance for hydride moderators. This impacts the acceptance/qualification of hydride moderators for microreactors. The goal of this technical note is to lay out a potential path forward for advanced moderator qualification and acceptance for designers and developers of microreactors. The proposed approach has benefited from a model microreactor core with the design parameters of a hydride moderator. Based on the model core and design parameters, a simple chart was developed for the major challenges of hydride moderators where potential incidents, causes, effects, and resolutions are described. The relation between the offered resolutions and the maturity of the metal-hydride moderator technology was emphasized using technological readiness. Technological readiness levels (TRLs) were clustered to three sets: physical phenomena related, reactor irradiations, and system demonstration. Some essential needs to fill the knowledge gaps are discussed for physical phenomena–related TRLs. For reactor irradiations, the importance of identifying goals and priorities is stressed to reach certain TRLs. For system demonstration, it is noted that metal-hydride moderator qualification must comply with the overall microreactor design.

36 MATERIALS SCIENCE↗

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Unraveling Spatio-Temporal Chemistry Evolution in Laser Ablation Plumes and Its Relation to Initial Plasma Conditions

The chemistry evolution in a laser ablation plume depends strongly on its initial physical conditions. In this article, we investigate the impact of plasma generation conditions on the interrelated phenomena of expansion dynamics, plasma chemistry, and physical conditions. Plasmas are produced from a uranium metal target in air using nanosecond, femtosecond, and femtosecond filament-assisted laser ablation. Time-resolved two-dimensional spectral imaging was performed for evaluating the spatio-temporal evolu-tion of atoms, diatoms, polyatomic molecules, and nanoparticles in situ. Emission spectral features reveal that molecular formation occurs at early times in both femtosecond and filament ablation plumes, although with different temporal decay. In contrast, mo-lecular formation is found to occur at much later times in nanosecond plasma evolution. Spectral modeling is used to infer tem-poral behavior of plasma excitation temperature, and results highlighted that nanosecond plume temperatures decay rapidly while plumes generated by filament ablation show slowest decay. In this work, we find U atoms and UO molecules co-exist in ultrafast laser produced plasmas even at early times after plasma onset owing to favorable temperatures for molecular formation. Regardless of irradiation conditions, plume emission features showed presence of higher oxides (i.e. UxOy), although with different temporal histories. Our study provides insight into the impact of plasma generation conditions on chemistry evolution in plasmas produced from traditional focused femtosecond, nanosecond, and filament-assisted laser ablation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The hazard components of representative key risks. The physical climate perspective

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II in order to categorize, assess and communicate a wide range of regional and sectoral key risks, expected to become severe as a consequence of the potentially detrimental convergence of changing climate conditions, exposure and vulnerability of human and natural systems, and responses through (mal)adaptation measures. Other papers in this special issue treat each of eight RKRs by holistically assessing their current status and future evolution as a result of this convergence. However, their treatment cannot always organize such assessment according to a systematic gradation of climatic changes, often times having to extrapolate the big-picture evolution of risk from either qualitative effects of “low” medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C). In this study we offer as systematic a representation as possible – given current literature and assessments – of the future evolution of the hazard components of RKRs. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group 1 (WGI) supplemented when needed by more recent literature. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels to the extent possible. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with global average temperature change has been assessed. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - the link to increasing global temperatures can only be described qualitatively. For some processes - like the behavior of ice-sheets, or changes in circulation dynamics - large uncertainties about the effects of different levels of warming remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems when these changes happen in conjunction with these systems’ conditions of exposure and vulnerability, and in lack of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in an often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future possible evolution which represents an important component – if never the only one – of the potential future evolution of risk severity.

54 ENVIRONMENTAL SCIENCES↗

Anisotropic 2D van der Waals Magnets Hosting 1D Spin Chains

Abstract The exploration of 1D magnetism, frequently portrayed as spin chains, constitutes an actively pursued research field that illuminates fundamental principles in many‐body problems and applications in magnonics and spintronics. The inherent reduction in dimensionality often leads to robust spin fluctuations, impacting magnetic ordering and resulting in novel magnetic phenomena. Here, structural, magnetic, and optical properties of highly anisotropic 2D van der Waals antiferromagnets that uniquely host spin chains are explored. First‐principle calculations reveal that the weakest interaction is interchain, leading to essentially 1D magnetic behavior in each layer. With the additional degree of freedom arising from its anisotropic structure, the structure is engineered by alloying, varying the 1D spin chain lengths using electron beam irradiation, or twisting for localized patterning, and spin textures are calculated, predicting robust stability of the antiferromagnetic ordering. Comparing with other spin chain magnets, these materials are anticipated to bring fresh perspectives on harvesting low‐dimensional magnetism.

1D magnetism↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

Magnetism in curved geometries

Curvature impacts physical properties across multiple length scales, ranging from the macroscopic scale, where the shape and size vary drastically with the curvature, to the nanoscale at interfaces and inhomogeneities in materials with structural, chemical, electronic, and magnetic short-range order. In quantum materials, where correlations, entanglement, and topology dominate, the curvature opens the path to novel characteristics and phenomena that have recently emerged and could have a dramatic impact on future fundamental and applied studies of materials. Particularly, magnetic systems hosting non-collinear and topological states and 3D magnetic nanostructures strongly benefit from treating curvature as a new design parameter to explore prospective applications in the magnetic field and stress sensing, microrobotics, and information processing and storage. This Perspective gives an overview of recent progress in synthesis, theory, and characterization studies and discusses future directions, challenges, and application potential of the harnessing curvature for 3D nanomagnetism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Phenomena Identification and Ranking Table (PIRT) for heat pipes

Heat pipes are advanced passive thermal management devices that utilize phase change and capillary action to achieve efficient heat transfer. However, due to the complexity of the phenomena coupled in heat pipes, including capillary, phase change, turbulence, and compressibility effects, there are high uncertainties in the predictability of their operational regimes and performance. This PIRT exercise, conducted as a collaborative effort involving the Department of Energy (DOE) Microreactor Program (MRP), the Nuclear Regulatory Commission (NRC), and university partners systematically identifies, reviews, and prioritizes critical phenomena affecting the operation of heat pipes based on their importance and knowledge levels. Additional analyses and discussion are provided for phenomena with high importance and low knowledge, such as wick de-wetting, critical heat flux, contact angles, and pressure dynamics. The discussions included the recognizing challenges and proposing future research directions for both modeling and simulation and experimental efforts. Additionally, the report addresses phenomena with medium importance and low knowledge that could impact heat pipe operation during non-normal or transient operation, including frozen startup, laminar to turbulent transition, geyser boiling, wick priming, underfilling conditions, surface roughness of the wick, NCGs trapped in the wick, and the timescales of startup and shutdown. In conclusion, this comprehensive evaluation serves as a valuable resource for guiding future research and development efforts, supporting the successful integration of heat pipes into critical applications such as nuclear reactors, and contributing to the advancement of heat pipe technologies in safety-critical industries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Melt pool instability detection using coaxial photodiode system validated by in-situ X-ray imaging

A co-axial photodiode monitoring system with high temporal resolution has been integrated into a proven test bench enabling synchronized side-view high speed X-ray imaging of melt pool dynamics and top-view spectral emission characterization of the melt pool. Here, this setup enables direct observation of melt pool phenomena and correlation between the two monitoring systems which can be directly scaled to commercial systems. The work demonstrates a 92% detection rate in keyhole collapse phenomena related to defect generation in SLM. Furthermore, the impact of gas flow on monitoring signals is studied to understand the fundamental importance of gas flow in commercial systems.

36 MATERIALS SCIENCE↗

Bulk Production of Any Ratio 12 C: 13 C Turbostratic Flash Graphene and Its Unusual Spectroscopic Characteristics

As graphene enjoys worldwide research and deployment, the biological impact, geologic degradation, environmental retention, and even some physical phenomena remain less well studied. Bulk production of 13 C-graphene yields a powerful route to study all of these questions. Gram scale synthesis of high quality and high purity turbostratic flash graphene with varying amounts of 13 C-enrichment, from 5% to 99% is reported here. Here, the material is characterized by solid state nuclear magnetic resonance spectroscopy, Raman spectroscopy, infrared (IR) spectroscopy, X-ray photoelectron spectroscopy and inductively coupled plasma mass spectrometry. Notably, an unusual enhancement in the Raman spectroscopic D’ peak is observed, resulting from the modification in vibrational frequency through isotopic enrichment favoring intravalley phonon scattering modes. While the IR absorbance spectrum of graphene is for the most part silent, we prepare here 13 C-enhanced graphene samples that show a large aromatic 12 C= 13 C stretch that reveals this IR-active mode.

01 COAL, LIGNITE, AND PEAT↗

Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is about the state of ICON principles Goldman et al. (2021), https://doi.org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management.

58 GEOSCIENCES↗

Purcell enhancement of directional edge photocurrent in a van der Waals self-cavity

Cavities provide a means to manipulate the optical and electronic responses of quantum materials by selectively enhancing light-matter interaction at specific frequencies and momenta. While cavities typically involve external structures, exfoliated flakes of van der Waals (vdW) materials can form intrinsic self-cavities due to their small finite dimensions, confining electromagnetic fields into plasmonic cavity modes, characterized by standing-wave current distributions. While cavity-enhanced phenomena are well-studied at optical frequencies, the impact of self-cavities on nonlinear electronic responses—such as directional photocurrent—remains largely unexplored, particularly in the terahertz regime, critical for emerging ultrafast optoelectronic technologies. Here, we report a self-cavity-induced Purcell enhancement of directional photocurrents in the vdW semimetal WTe 2 . Using ultrafast optoelectronic circuitry, we measured coherent near-field THz emission resulting from nonlinear photocurrents excited at the sample edges. We observed enhanced emission at finite frequencies, tunable via excitation fluence and sample geometry, which we attribute to plasmonic interference effects controlled by the cavity boundaries. We developed an analytical theory that captures the cavity resonance conditions and spectral response across multiple devices. Our findings establish WTe 2 as a bias-free, geometry-tunable THz emitter and demonstrate the potential of self-cavity engineering for controlling nonlinear, nonequilibrium dynamics in quantum materials.

condensed-matter physics↗

High-speed Boulders and the Debris Field in DART Ejecta

On 2022 September 26 the Double Asteroid Redirection Test (DART) spacecraft collided with Dimorphos, the moon of the near-Earth asteroid 65803 Didymos, in a full-scale demonstration of a kinetic impactor concept. The companion Light Italian Cubesat for Imaging of Asteroids (LICIACube) spacecraft documented the aftermath, capturing images of the expansion and evolution of the ejecta from 29 to 243 s after the impact. We present results from our analyses of these observations, including an improved reduction of the data and new absolute calibration, an updated LICIACube trajectory, and a detailed description of the events and phenomena that were recorded throughout the flyby. One notable aspect of the ejecta was the existence of clusters of boulders, up to 3.6 m in radius, that were ejected at speeds of up to 52 m s −1 . Our analysis of the spatial distribution of 104 of these boulders suggests that they are likely the remnants of larger boulders shattered by the DART spacecraft in the first stages of the impact. The amount of momentum contained in these boulders is more than 3 times that of the DART spacecraft, and it is directed primarily to the south, almost perpendicular to the DART trajectory. Recoil of Dimorphos from the ejection of these boulders has the potential to change its orbital plane by up to a degree and to impart a non-principal-axis component to its rotation state. Damping timescales for these phenomena are such that the Hera spacecraft, arriving at the system in 2026, should be able to measure these effects.

asteroid dynamics↗