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At least 1,711 records · Page 95

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown↗

Experimental Steps toward a Density Law for Chlorine-Crediting Criticality Models of Aqueous Plutonium solutions

Criticality accident prevention is an essential safety consideration for all operations involving fissionable and fissile materials. Predictive criticality calculations using advanced neutron transport codes, such as Monte Carlo N-Particle Transport (MCNP), are invaluable tools for designing and implementing operational limits. While indispensable, these tools are limited by the quality and accuracy of the inputs that the user provides to define the modeled system. Parameters such as atomic composition, shape, and material density must be accurately defined to obtain a meaningful result. In the case of material property details for a plutonium model, accurate material characterization data is sometimes sparse. Thus limitations in calculation accuracy can be reduced by improving our knowledge of material properties in the targeted fissile systems. One of the biggest remaining challenges to accurately defining fissile systems is the description of aqueous fissile solutions. Even simple properties, such as density, are not well-known for fissile solutions relevant to nuclear energy and security. Described here are initial efforts undertaken to improve criticality calculation inputs for fissile plutonium chloride solutions in water. This effort is focused on experimentally determining accurate solution characteristics for ternary plutonium chloride/hydrochloric acid/water systems, by measurement of water activity and solution density. The effect of inputting experimental densities for these solutions into MCNP criticality calculations is compared to the traditional approach of modeling an idealized (and fictitious) plutonium-water mixture. Expansion of these efforts to a working density law for aqueous plutonium chloride solutions is also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

In-Situ TEM Molten Salt Corrosion

Molten salt reactors (MSRs) offer a compelling pathway for next-generation nuclear energy, with advantages in thermal efficiency, inherent safety, and flexible fuel management. Yet, halide-based molten salts introduce significant materials challenges, particularly alloy corrosion. Alloy performance in these environments ultimately depends on understanding how corrosion initiates and progresses at the nanoscale, however most existing models rely on post-exposure characterization, leaving degradation mechanisms largely inferred rather than directly observed. NiCr alloys have garnered interest in MSRs applications as the Ni-based matrix provides strength and creep resistance, while Cr content offers oxidation resistance in air. However, NiCr corrosion resistance in chloride salts has proven poor due to preferential chromium dissolution, the formation of Cr-depleted pathways, and grain-boundary attack. This work aims to directly visualize corrosion of Ni-20Cr exposed to LiCl-KCl using in-situ Transmission Electron Microscopy (TEM) to capture real-time microstructural evolution during corrosion. Experiments will be performed at ~800 °C under controlled pressure conditions while utilizing Energy-Dispersive X-ray Spectroscopy (EDS) to analyze elemental redistribution. Observation of chromium depletion fronts, associated surface restructuring, and localized chloride enrichment are expected. Ultimately, this study is expected to provide a link between microscale processes and the macroscopic degradation behaviors relevant to MSR operation in advanced reactor environments. Simultaneously, this approach enables future in-situ investigations regarding alloy composition, salt chemistry, and their influence on corrosion pathways and long-term stability.?

36 - MATERIALS SCIENCE↗

Li-rich cathodes for rechargeable Li-based batteries: reaction mechanisms and advanced characterization techniques

Due to their high specific capacities beyond 250 mA h g -1 , lithium-rich oxides have been considered as promising cathodes for the next generation power batteries, bridging the capacity gap between traditional layered-oxide based lithium-ion batteries and future lithium metal batteries such as lithium sulfur and lithium air batteries. However, the practical application of Li-rich oxides has been hindered by formidable challenges. To address these challenges, the understanding of their electrochemical behaviors becomes critical and is expected to offer effective guidance for both materials and cell development. This work aims to provide fundamental insights into the reaction mechanisms, electrochemical challenges and modification strategies of lithium-rich oxides. We first summarize the research history, the pristine structures, and the classification of lithium-rich oxides. Then we review the critical reaction mechanisms that are closely related to their electrochemical features and performances, such as lattice oxygen oxidation, oxygen vacancy formation, transition-metal migration, layered to spinel transitions, ‘two-phase mechanism’, and lattice evolution. These discussions are coupled with state-of-the-art characterization techniques. As a comparison, the anionic redox reactions of layered sodium transition metal oxides are also discussed. Finally, after a brief overview of the correlation among the aforementioned mechanisms, we provide perspectives on the rational design of lithium-rich oxides with high energy densities and long-term cycling stability.

25 ENERGY STORAGE↗

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗

Characterizing background error with the NASA GMAO OSSE

Understanding the characteristics of background error is vital to the design and performance of data assimilation systems. However, the true state of the atmosphere is unknown, and qualitative determination of background error is thus a challenge. We present an exploration of background error characteristics using the NASA Global Modeling and Assimilation Office Observing System Simulation Experiment framework, where the presence of the Nature Run allows direct calculation of the background error. The behavior of the data assimilation system (DAS) can be compared with the character of the background error, and performance of the DAS will be investigated in a series of both idealized and realistic experiments.

Nature Run↗

Identification of Cardiometabolic Vulnerabilities Caused by Effects of Synergistic Stressors that are Commonly Encountered During Space Missions

Microgravity is a physiologically challenging state even when at rest. Astronauts experience additional physical and mental stresses, such as prolonged exertion, sleep loss and circadian misalignment, that could impact cardiovascular function. The main goals of this four year NASA project are to characterize the independent and synergistic effects on cardiovascular and immune function of: (1) circadian misalignment; (2) sleep loss; and (3) varied physical and mental stressors, mimicking some of the synergistic stressors experienced by astronauts. Sixteen healthy volunteers, aged 35-55 years, will be studied with standardized behavioral stressors occurring across all circadian phases, both with and without accruing sleep loss, achieved via two 11-day "forced desynchrony" protocols performed in each subject (randomized, within-subject design), where wake periods are advanced 4-h each "day" (i.e. recurring 20-h "days"). One protocol permits 8.33 h sleep opportunity per 20-h "day" (=10 h sleep per 24-h), and the other permits 5 h sleep per 20-h "day" (=6 h sleep per 24-h; matching the reported sleep duration of astronauts). In both protocols, subjects will perform a standardized stress battery including a cognitively challenging task; bicycle exercise, and passive 60deg head up tilt. Outcome variables include blood pressure, heart rate, arrhythmia frequency, cardiac vagal tone (from heart rate variability), sympathetic activity (catecholamines), and endothelial function. Additional measures of cardiac function (echocardiography), responses to a passive 80deg head up tilt, maximal oxygen uptake, and immune function will be assessed at the beginning and at the end of each protocol (i.e., without and with sleep loss, and before and after circadian misalignment). We hope to identify the relative impact on cardiovascular risk markers of varied behavioural stressors while subjects experience circadian misalignment and sleep loss, mimicking some of the synergistic stressors experienced by astronauts. Supported by NASANNX1 OAR 1 OG.

Ruger, M.↗

Preparation and characterization of isotopically pure Mo targets for nuclear science measurements

Isotopically pure molybdenum targets are essential in various nuclear science measurements. For studies of cross sections of capture reactions on molybdenum, uniform targets with areal densities of hundreds of g/cm 2 are desired. Mechanical rolling of enriched metal pieces or vacuum sputtering methods used in previous studies to prepare molybdenum targets are challenging and involve labor- and time-intensive processes. Therefore, reliable and straightforward methods to produce molybdenum targets are crucial. We have developed a new double-step method to produce targets meeting these needs. The first step consists of evaporating isotopically enriched MoO 3 onto gold backings. The second step involves the reduction of the oxide layer in a 5% H 2 -Ar environment to obtain molybdenum targets. X-ray fluorescence (XRF) spectroscopy, X-ray Diffraction (XRD), a scanning electron microscope/focused ion beam milling, and energy-dispersive X-ray spectroscopy (EDS) were used to characterize the targets. These methods show that the targets exhibit a uniform coverage of Mo over the gold backings. Furthermore, significant volume shrinkage occurring during the reduction of MoO 3 creates a porous Mo layer where the gold diffuses due to the high processing temperatures, resulting in mixed Mo–Au layers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Species-specific ribosomal RNA-FISH identifies interspecies cellular-material exchange, active-cell population dynamics and cellular localization of translation machinery in clostridial cultures and co-cultures

ABSTRACT The development of synthetic microbial consortia in recent years has revealed that complex interspecies interactions, notably the exchange of cytoplasmic material, exist even among organisms that originate from different ecological niches. Although morphogenetic characteristics, viable RNA and protein dyes, and fluorescent reporter proteins have played an essential role in exploring such interactions, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to further investigate interactions in synthetic or semisynthetic consortia. Despite its maturity, several challenges exist in using rRNA-FISH as a tool to quantify individual species population dynamics and interspecies interactions using high-throughput instrumentation such as flow cytometry. In this work, we resolve such challenges and apply rRNA-FISH to double and triple co-cultures of Clostridium acetobutylicum, Clostridium ljungdahlii, and Clostridium kluyveri . In pursuing our goal to capture each organism’s population dynamics, we demonstrate dynamic rRNA, and thus ribosome, exchange between the three species leading to the formation of hybrid cells. We also characterize the localization patterns of the translation machinery in the three species, identifying distinct, dynamic localization patterns among them. Our data also support the use of rRNA-FISH to assess the culture’s health and expansion potential, and, here again, our data find surprising differences among the three species examined. Taken together, our study argues for rRNA-FISH as a valuable and accessible tool for quantitative exploration of interspecies interactions, especially in organisms which cannot be genetically engineered or in consortia where selective pressures to maintain recombinant species cannot be used. IMPORTANCE Though dyes and fluorescent reporter proteins have played an essential role in identifying microbial species in co-cultures, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to quantitatively probe complex interactions between organisms in synthetic consortia. Despite its maturity, several challenges existed before rRNA-FISH could be used to study Clostridium co-cultures of interest. First, species-specific probes for Clostridium acetobutylicum and Clostridium ljungdahlii had not been developed. Second, “state-of-the-art” labeling protocols were tedious and often resulted in sample loss. Third, it was unclear if FISH was compatible with existing fluorescent reporter proteins. We resolved these key challenges and applied the technique to co-cultures of C. acetobutylicum , C. ljungdahlii , and Clostridium kluyveri . We demonstrate that rRNA-FISH is capable of identifying rRNA/ribosome exchange between the three organisms and characterized rRNA localization patterns in each. In combination with flow cytometry, rRNA-FISH can capture sub-population dynamics in co-cultures.

Hill, John D.↗

Asteroid and Lava Tube In Situ Resource Utilization (ISRU) Prospecting Free Flyer Project

This project seeks to develop a small free flyer that can be used to safely and effectively prospect on an Asteroid while being controlled by the crew. This will enable the characterization of the Asteroid for the In Situ Resource Utilization (ISRU). Lava tubes can be explored remotely from the outside Asteroids can contain vast amounts of resources such as water for propellants and metals for feed stocks. Lava Tubes on Mars and the Moon may contain frozen volatile resources. Before the resources can be used, they must be found with a prospecting method. The NASA Agency Asteroid Grand Challenge seeks new ideas for Asteroid retrieval mission technologies for exploration and utilization of asteroids in a Distant Retrograde Orbit (DRO). This project will develop a small free flying platform that can be used to safely and effectively prospect on an Asteroid with limited autonomy while being controlled by the crew. This will enable the characterization of the Asteroid for ISRU. Lava tubes can be explored remotely from the outside as well using this same technology.

Technology Portfolio System↗

Intra- and Intermolecular Self-Assembly of a 20-nm-Wide Supramolecular Hexagonal Grid.

For the past three decades, the coordination-driven self-assembly of three-dimensional structures has undergone rapid progress; however, parallel efforts to create large discrete two-dimensional architectures-as opposed to polymers-have met with limited success. The synthesis of metallo-supramolecular systems with well-defined shapes and sizes in the range of 10-100 nm remains challenging. Here we report the construction of a series of giant supramolecular hexagonal grids, with diameters on the order of 20 nm and molecular weights greater than 65 kDa, through a combination of intra- and intermolecular metal-mediated self-assembly steps. The hexagonal intermediates and the resulting self-assembled grid architectures were imaged at submolecular resolution by scanning tunnelling microscopy. Characterization (including by scanning tunnelling spectroscopy) enabled the unambiguous atomic-scale determination of fourteen hexagonal grid isomers.

Zhang, Zhe↗

Steady-State Irradiation of Characterized Instruments for Nuclear Thermal Rockets Using In-Pile Experiment Apparatus

The development of nuclear rocket technology is critical for further exploration of extra-terrestrial bodies. Nuclear rockets can provide various advantages over current chemical rockets. However, the harsh environment provides several challenges regarding instrument performance. Temperature extremes, radiation (reactor and space), and the inability to conduct traditional maintenance activities can lead to severe degradation in instrument performance. To better understand the effects of radiation on instrumentation, an irradiation campaign has been designed to test a set of instruments provided by a collaborator in the aerospace industry. Details concerning instrument performance before and after irradiation are provided to allow for an analysis of the tested instruments. Additionally, the design of the irradiation test is described in detail.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗

Durability Characterization of Advanced Polymeric Composites at Cryogenic Temperatures

The next generation of reusable launch vehicles will require technology development in several key areas. Of these key areas, the development of polymeric composite cryogenic fuel tanks promises to present one of the most difficult technical challenges. It is envisioned that a polymer matrix composite (PMC) tank would be a large shell structure capable of containing cryogenic fuels and carrying a range of structural loads. The criteria that will be imposed on such a design include reduced weight, conformal geometry, and impermeability. It is this last criterion, impermeability, that will provide the focus of this paper. The essence of the impermeability criterion is that the tank remains leak free throughout its design lifetime. To address this criterion, one of the first steps is to conduct a complete durability assessment of the PMC materials. At Langley Research Center, a durability assessment of promising new polyimide-based PMCs is underway. This durability program has focused on designing a set of critical laboratory experiments that will determine fundamental material properties under combined thermal-mechanical loading at cryogenic temperatures. The test program provides measurements of lamina and laminate properties, including strength, stiffness, and fracture toughness. The performance of the PMC materials is monitored as a function of exposure conditions and aging time. Residual properties after exposure are measured at cryogenic temperatures and provide quantitative values of residual strength and stiffness. Primary degradation mechanisms and the associated damage modes are measured with both destructive and nondestructive techniques. In addition to mechanical properties, a range of physical properties, such as weight, glass transition, and crack density, are measured and correlated with the test conditions. This paper will report on the progress of this research program and present critical results and illustrative examples of current findings.

Gates, T. S.↗

Deep learning based x-ray spectrometer for high repetition rate characterization of betatron radiation

Betatron radiation produced from a laser-wakefield accelerator is a broadband, hard x-ray (>1 keV) source that has been used in a variety of applications in medicine, engineering, and fundamental science. Further development and optimization of stable, high repetition rate (HRR) (>1 Hz) betatron sources will provide a means to extend their application base to include single-shot dynamical measurements of ultrafast processes or dense materials. Recent advances in laser technology used in such experiments have enabled increases in shot-rate and system stability, providing improved statistical analysis and detailed parameter scans. However, unique challenges exist at high repetition rate, where data throughput and source optimization are now limited by diagnostic acquisition rates and analysis. Here, we present the development of a machine-learning algorithm for the real-time analysis of betatron radiation. We report on the fielding of this deep learning algorithm for online source characterization at the Institut National de la Recherche Scientifique's Advanced Laser Light Source. By fine-tuning an algorithm originally trained on a fully synthetic dataset using a subset of experimental data, the algorithm can predict the betatron critical energy with a percent error of 7.2 % with a reconstruction time of 1.5 ms, providing a valuable tool for real-time, multi-objective optimization at HRR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

A signal packet router for the upgrade of the Muon spectrometer at the ATLAS experiment

Here, we present the design, characterization, and production of a signal packet router for the upgrade of the ATLAS forward muon detector. The router serves as a packet switch in one of the primary trigger paths. It handles up to 12 serial inputs at 4.8 Gbps/input from on-detector electronics and outputs four 4.8 Gbps to the trigger processing circuits. In the 12-to-4 packet switching process, the input streams are decoded and synchronized to a common clock domain for data packets forwarding and NULL packets suppression. Challenges in the design include operations of multi-giga hertz serial links with low and constant latency (<100 ns) for packet routing, as well as mitigation of radiation-induced effects in the harsh radiation environment over 10 years of detector operation. The Router design has been fully characterized and demonstrated to meet all specifications. In total 256 Routers were installed in the detector. Its design concept can be used in other similar applications, particularly in a radiation environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Material Needs and Measurement Challenges for Advanced Semiconductor Packaging: Understanding the Soft Side of Science

This Perspective builds upon insights from the National Institute of Standards and Technology (NIST)-organized workshop, “Materials and Metrology Needs for Advanced Semiconductor Packaging Strategies,” held at the 35th annual Electronics Packaging Symposium in Binghamton, NY, on September 5, 2024. It outlines critical challenges and opportunities related to polymer-based “soft” materials in advanced semiconductor packaging, with emphasis on polymer science, measurement science (metrology), and the strategic development of Research-Grade Test Materials (RGTMs). These efforts, led by the NIST CHIPS team, aim to advance the fundamental understanding of structure-property-processing relationships, promote standardized guidelines and innovative methods for material characterization, and accelerate the development, qualification, and adoption of next-generation packaging materials. The Perspective also distills key insights from the panel discussion with industry experts, emphasizing the need for close collaboration among materials scientists, process engineers, and metrology experts to enable a holistic strategy, further highlighting the importance of cross-sector partnerships among industry, academia, and government to address pressing challenges in packaging materials and processes.

97 MATHEMATICS AND COMPUTING↗