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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Infrared bands of neutral gas-phase carbon clusters in a broad spectral range

The identification of species in the interstellar medium requires precise and molecule-specific spectroscopic information in the laboratory framework, in broad spectral ranges and under conditions relevant to interstellar environments. In this work, we measure the gas-phase infrared spectra of neutral carbon clusters, C N (N = 6–11), in a molecular beam. The C N distribution is formed by photofragmentation of C 60 molecules, concurrently showing a top-down formation mechanism. A broad spectral range in the infrared between 500–3200 cm -1 (20–3.125 μm) is investigated. We observe strong bands between 5 and 6 μm, in conjunction with novel features in the 3 μm region. Density functional theory calculations reveal that these short wavelength modes correspond to combination bands with significant infrared intensity. Moreover, we identify the N ≤ 10 clusters as linear, while C 11 adopts a ring configuration, placing the linear-to-ring transition at N = 11 under our molecular beam conditions. The linearity of C 10 is discussed based on the formation pathway from larger clusters in energetic conditions. Given the vast and very precise infrared information already been released from the James Webb Space Telescope mission, this infrared spectroscopic data set in conjunction with information on formation mechanisms is of major relevance for identifying neutral carbon clusters in astronomical environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multi-spatio-temporal scales PIV in a turbulent buoyant jet discharging in a linearly stratified environment

Time-resolved particle image velocimetry is implemented with a camera array and several laser sheets; this results in a multi-spatio-temporal scale system that is modular and flexible. The setup is optimized to capture global flow features, while locally resolving in space and time near the Kolmogorov scale. The apparatus relies extensively on machine vision CMOS cameras; they are inexpensive and stream to computer hard drive with virtually continuous time-resolved records (up to one hour for the current system). This leads to statistically converged data and also helps in minimizing down time between experimental runs. Details of the implementation and design of experiment are reported. The system instruments a vertical buoyant jet discharging in a linearly stratified environment. Refractive index matched aqueous solutions enable precise optical deployment. The density difference is 3% and the fluids have similar dynamic viscosity. The jet Reynolds number is 2.00 x 10 4 and is above the mixing transition. Such flows are typically challenging to instrument and few velocity field data are available to date. The velocity statistics are reported as well as first insights gained from the campaign.

42 ENGINEERING↗
DOE OSTI2022

Vitrification of Hanford Tank 241-AP-101 Waste and Simulant

Hanford tank 241-AP-101 (referred to herein as AP-101) is the second Hanford radioactive tank waste planned to be processed and vitrified. A simulant version of AP 101 waste was formulated from the best-basis inventory (BBI) for the Hanford Tank 241-AP-101 liquid with an assumed target dilution of the waste from the BBI sodium molarity of 8.61 M to the desired 5.5 M Na. After the addition of glass-forming chemicals (GFCs), the simulant melter feed was processed in a non-radioactive, continuous laboratory-scale melter (CLSM) system. The AP-101 simulant melter feed was charged into the CLSM for 6.11 h of processing, which produced 6.55 kg of glass, for an average glass production rate of 2275 kg m 2 d -1 . Since there were no processing issues with the AP-101 simulant melter feed, AP-101 melter feed made with actual waste was then processed in a CLSM system built into a contamination area in a radioactive environment. The melting behavior characteristics appeared similar for both the simulant and waste melter feeds. The AP-101 waste melter feed was charged into the CLSM for 12.14 h of processing, which produced 8.75 kg of glass, for an average glass production rate of 1530 kg m 2 d -1 . During the AP-101 waste melter feed charging, the pump used to move the feed reached a maximum and it is believed that if the pump had a greater capacity, a greater average glass production rate could have been achieved. A constituent of interest present in low quantities in the AP-101 waste is 99 Tc or its non-radioactive surrogate, Re, added to the AP-101 simulant. Analysis for the quantities of 99 Tc and Re in the AP-101 glass product resulted in an average single-pass retention from the melter feed during relative chemical steady state of 55 ± 2 % for 99 Tc and 45 ± 2 % for Re. Compared to the processing of other melter feeds, the retention of 99 Tc in the AP-101 glass was greater than in both AP-107 and AP-105 glass, while the retention of Re in the AP-101 was less than in the AP-107 glass, but greater than in the AP-105 glass. A spike of I was added into the AP-101 melter feed that could be detected above the analysis detection limits. However, the iodine was only detectable above the ~6 ppm limit in one glass pour: the pour immediately following the burn off of the cold cap, where the I level reached ~30 ppm. This event was significant because the glass was poured immediately after burn off and thus it is presumed that the iodine had yet to volatilize from the glass melt while idling. It is recommended to perform future tests with I spikes at greater levels so that it can be detected in additional glass pours to determine if the expected 50 % retention of I used in the Kim et al. glass models can be confirmed. Offgas liquid samples were analyzed for acetonitrile, which was present at greater concentrations in CLSM liquids than in other scaled melter systems. This result was expected based on unique conditions with the CLSM system including a small plenum space leading to low residence time for offgas and the rapidity of offgas cooling upon exiting the CLSM vessel due to the location and environment. About 90 % of the total acetonitrile captured during both the AP-101 simulant and waste CLSM runs was found in the offgas condensate and demister liquids, thus it is recommended that only those liquids be sent for analysis if future testing to study the presence of acetonitrile in offgas products is desired.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Reaction–drift–diffusion models from master equations: application to material defects

We present a general method to produce well-conditioned continuum reaction–drift–diffusion equations directly from master equations on a discrete, periodic state space. We assume the underlying data to be kinetic Monte Carlo models (i.e. continuous-time Markov chains) produced from atomic sampling of point defects in locally periodic environments, such as perfect lattices, ordered surface structures or dislocation cores, possibly under the influence of a slowly varying external field. Our approach also applies to any discrete, periodic Markov chain. Here, the analysis identifies a previously omitted non-equilibrium drift term, present even in the absence of external forces, which can compete in magnitude with the reaction rates, thus being essential to correctly capture the kinetics. To remove fast modes which hinder time integration, we use a generalized Bloch relation to efficiently calculate the eigenspectrum of the master equation. A well conditioned continuum equation then emerges by searching for spectral gaps in the long wavelength limit, using an established kinetic clustering algorithm to define a proper reduced, Markovian state space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment

Abstract We introduce Crystal Edge Graph Attention Neural Network (CEGANN) workflow that uses graph attention-based architecture to learn unique feature representations and perform classification of materials across multiple scales (from atomic to mesoscale) and diverse classes ranging from metals, oxides, non-metals to hierarchical materials such as zeolites and semi-ordered mesophases. CEGANN can classify based on a global, structure-level representation such as space group and dimensionality (e.g., bulk, 2D, clusters, etc.). Using representative materials such as polycrystals and zeolites, we demonstrate its transferability in performing local atom-level classification tasks, such as grain boundary identification and other heterointerfaces. CEGANN classifies in (thermal) noisy dynamical environments as demonstrated for representative zeolite nucleation and growth from an amorphous mixture. Finally, we use CEGANN to classify multicomponent systems with thermal noise and compositional diversity. Overall, our approach is material agnostic and allows for multiscale feature classification ranging from atomic-scale crystals to heterointerfaces to microscale grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Accurate determination of chemical abundances near a supermassive black hole

The metal abundances in galactic nuclei carry key information on the history of star formation and mass transfer in central regions of galaxies. X-ray fluorescence analysis is a unique tool to reliably measure the abundances of various elements via simple physics. Here we present a new observation of the active nucleus in the Circinus galaxy with the XRISM satellite at unprecedented X-ray energy resolution. The fluorescent iron Kα line profile modified by Compton scattering indicates that the material responsible for its emission is cold and metal rich and is located ≳0.024 pc from the supermassive black hole, consistent with the dusty torus region. The abundance pattern derived from comparing fluorescent line intensities of different metals shows subsolar ratios of argon- and calcium-to-iron and a supersolar ratio of nickel-to-iron. This abundance pattern is best produced by a combination in number fraction of 92$^{+2}_{–4}$% core-collapse supernovae from progenitor stars less massive than 20$^{+3}_{–2}$ M ⊙ and 8$^{+4}_{–2}$% type Ia supernovae. This suggests that gas feeding the supermassive black hole was enriched by recent core-collapse supernovae. Our findings imply that in metal-rich environments stars more massive than about 20 M ⊙ directly collapse into black holes or make faint supernovae without ejecting heavy metals into the space.

Astronomy and AstroPhysics↗
DOE OSTI2025

Dtc Commercialization Software Package

This code is the complete software and firmware components supporting DTC model radios H2 and BluSDR6. This software package contains all the hardware boot up code/config files(BSP), user space Linux code (Web, Network, MAC (media access control) & drivers), the field programable gate array HDL (hardware description language) code and the build environment to compile and organize these components together to work in the aforementioned radios. Additional details of these components are as follows: • Hardware support components o Board support package and configuration files o uBoot • Linux Components: o The web components include the user interface for setup, configuration, and status components of the system. o Vulture code configures the radio’s IP network, configures radio parameters and runs the MAC layer of the radio. • The Field Programmable Gate Array HDL contains hardware drivers, interface logic to go between the software to the physical layer and the radio hardware as well as the logic for the physical layer of the radio. • Build environment includes compilers and config files that compile and organize all the other components to be able to be run on the radios.

Loera, Jose [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

Efficient and Selective Chemical Transformations in Highly Charged and Confined Nanodroplets

The acceleration of chemical reaction rates and the increased product selectivity in microdroplets compared to that in bulk solutions has become a topic of increasing interest that has been extensively characterized by electrospray ionization mass spectrometry (ESI-MS). However, the sources of this acceleration and the detailed relationships between droplet properties and resulting reaction rate acceleration are still under debate. Moreover, droplet properties are governed by multiple interrelated experimental parameters, i.e., electrospray voltage, solution flow rate, etc., which makes it difficult and time-consuming to explore this diverse parameter space using traditional manual experimental or computational approaches. In this work, we developed an automated experimental platform integrating reactions in controlled charged microdroplet environments with ESI-MS characterization and sequential hybrid Bayesian modeling, as well as an optimal experimental design framework, to achieve multidimensional parameter optimization for higher reaction turnover rates, based on a model reaction of tetraethylenepentamine (TEPA) with carbon dioxide. With the current platform, we have achieved automated scans with a range of electrospray voltages and solution flow rates, and determined and optimized parameter settings to achieve increased reaction turnovers. We have also linked this platform to the underlying properties of droplets via a hybrid model incorporating physics, high-level theoretical calculations, and machine learning (ML) approaches. The autonomous platform is broadly applicable to a range of chemical reactions relevant to DOE’s mission in chemical separations, catalysis, and materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Fencing affects movement patterns of two large carnivores in Southern Africa

The erection of peripheral fences around protected areas has been shown to adversely affect the movement behavior, genetic connectivity and long-term viability of animal populations. However, fencing is also used extensively to reduce human encroachment, limit poaching activities, and mitigate human–wildlife conflicts. Limited information on the movement behavior of carnivores is available along the periphery of protected areas, particularly in semi-arid environments. To quantify the potential effects of the 824 km perimeter fence surrounding the Etosha National Park (Etosha, Namibia) on the movement and space use of carnivores, we collected GPS movement data from 36 lions (Panthera leo) and seven spotted hyenas (Crocuta crocuta) over a 14-year period. For these two apex carnivores, we measured the impact of the Etosha fence on their movements (step lengths and path straightness), calculated the likelihood of fence crossings, and evaluated the spatial–temporal characteristics of these crossings. Our results indicated that lions and hyenas moved faster (longer step lengths) when closer to the fence. Lions showed no variation in path straightness with respect to the fence but hyenas had straighter movement paths when closer to the fence. When moving within the vicinity of the fence, lions had a 9% likelihood of crossing the fence, while hyenas were much more likely (18%) to do so, which suggests that the Etosha fence was more permeable for hyenas than for lions. Fence crossings predominantly occurred at night for both species. Lions were more likely to cross the fence during the cold dry season (May–August) whereas hyenas crossed more often during the warm wet season (December–April). Female and adult lions had a higher probability of crossing the fence than males and subadults. These findings could be useful in the development of appropriate strategies to mitigate human–carnivore conflicts and thus promote the conservation of carnivores in multiple-use areas along the periphery of the park. Further research is needed to better elucidate the impact of perimeter fences on a broader suite of carnivores and other large mammals, including species-specific variation in the response to fences, as well as the economic benefits of fencing provided to local communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Lindsey, Jack W. (ORCID:0000000309307327)↗
DOE OSTI2020

Low-mass Group Environments Have No Substantial Impact on the Circumgalactic Medium Metallicity

We explore how environment affects the metallicity of the circumgalactic medium (CGM) using 13 low-mass galaxy groups (two to five galaxies) at &lang;z{sub abs}&rang;=0.25 identified near background quasars. Using quasar spectra from the Hubble Space Telescope/COS and from Keck/HIRES or the Very Large Telescope/UVES, we measure column densities of or determine limits on CGM absorption lines. We use a Markov Chain Monte Carlo approach with Cloudy to estimate metallicities of cool (T ~ 10{sup 4} K) CGM gas within groups and compare them to CGM metallicities of 47 isolated galaxies. Both group and isolated CGM metallicities span a wide range (-2 < [Si/H] < 0), where the mean group (-0.54 ± 0.22) and isolated (-0.77 ± 0.14) CGM metallicities are similar. Group and isolated environments have similar distributions of H I column densities as a function of impact parameter. However, contrary to isolated galaxies, we do not find an anticorrelation between H I column density and the nearest group galaxy impact parameter. We additionally divided the groups by member luminosity ratios (i.e., galaxy–galaxy and galaxy–dwarf groups). While there was no significant difference in their mean metallicities, a modest increase in sample size should allow one to statistically identify a higher CGM metallicity in galaxy–dwarf groups compared to galaxy–galaxy groups. We conclude that either environmental effects have not played an important role in the metallicity of the CGM at this stage and expect that this may only occur when galaxies are strongly interacting or merging or that some isolated galaxies have higher CGM metallicities due to past interactions. Thus, environment does not seem to be the cause of the CGM metallicity bimodality.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Description and Genome Characterization of Three Novel Fungal Strains Isolated from Mars 2020 Mission-Associated Spacecraft Assembly Facility Surfaces—Recommendations for Two New Genera and One Species

National Aeronautics and Space Administration’s (NASA) spacecraft assembly facilities are monitored for the presence of any bacteria or fungi that might conceivably survive a transfer to an extraterrestrial environment. Fungi present a broad and diverse range of phenotypic and functional traits to adapt to extreme conditions, hence the detection of fungi and subsequent eradication of them are needed to prevent forward contamination for future NASA missions. During the construction and assembly for the Mars 2020 mission, three fungal strains with unique morphological and phylogenetic properties were isolated from spacecraft assembly facilities. The reconstruction of phylogenetic trees based on several gene loci (ITS, LSU, SSU, RPB, TUB, TEF1) using multi-locus sequence typing (MLST) and whole genome sequencing (WGS) analyses supported the hypothesis that these were novel species. Here we report the genus or species-level classification of these three novel strains via a polyphasic approach using phylogenetic analysis, colony and cell morphology, and comparative analysis of WGS. The strain FJI-L9-BK-P1 isolated from the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) exhibited a putative phylogenetic relationship with the strain Aaosphaeria arxii CBS175.79 but showed distinct morphology and microscopic features. Another JPL-SAF strain, FJII-L3-CM-DR1, was phylogenetically distinct from members of the family Trichomeriaceae and exhibited morphologically different features from the genera Lithohypha and Strelitziana. The strain FKI-L1-BK-DR1 isolated from the Kennedy Space Center facility was identified as a member of Dothideomycetes incertae sedis and is closely related to the family Kirschsteiniotheliaceae according to a phylogenetic analysis. The polyphasic taxonomic approach supported the recommendation for establishing two novel genera and one novel species. The names Aaosphaeria pasadenensis (FJI-L9-BK-P1 = NRRL 64424 = DSM 114621), Pasadenomyces melaninifex (FJII-L3-CM-DR1 = NRRL 64433 = DSM 114623), and Floridaphiala radiotolerans (FKI-L1-BK-DR1 = NRRL 64434 = DSM 114624) are proposed as type species. Furthermore, resistance to ultraviolet-C and presence of specific biosynthetic gene cluster(s) coding for metabolically active compounds are unique to these strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Performance Test of Mini LVDT - ELVIS

The Institute for Energy (IFE) Technology has been a pioneer in the development of Linear Variable Differential Transformers (LVDTs) for in-pile testing, deploying over 2,200 units in various reactor environments with less than a 10% failure rate after five years of operation. This report focuses on the performance testing of IFE’s Mini LVDT, a compact sensor ideal for material test reactor experiments. The Mini LVDT, with a limited range of +/- 1.5 mm, offers excellent performance comparable to larger LVDTs, making it valuable in space-constrained applications. The development of an Enhanced Linear Variable Intrinsic Sensor (ELVIS) with internal temperature monitoring capabilities represents a significant advancement, addressing the critical need for real-time, accurate measurements in high-radiation and high-temperature environments. Two ELVIS prototypes were evaluated in terms of both temperature and displacement, showcasing promising results, though challenges with noise during temperature measurements were identified. This report summarizes the rigorous testing performed at Idaho National Laboratory (INL) and highlights the potential applications of Mini LVDTs and ELVIS in nuclear and other high-precision industries.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Are grid cells used for navigation? On local metrics, subjective spaces, and black holes

The symmetric, lattice-like spatial pattern of grid-cell activity is thought to provide a neuronal global metric for space. This view is compatible with grid cells recorded in empty boxes but inconsistent with data from more naturalistic settings. Here, we review evidence arguing against the global-metric notion, including the distortion and disintegration of the grid pattern in complex and three-dimensional environments. We argue that deviations from lattice symmetry are key for understanding grid-cell function. We propose three possible functions for grid cells, which treat real-world grid distortions as a feature rather than a bug. First, grid cells may constitute a local metric for proximal space rather than a global metric for all space. Second, grid cells could form a metric for subjective action-relevant space rather than physical space. Third, distortions may represent salient locations. Finally, we discuss mechanisms that can underlie these functions. These ideas may transform our thinking about grid cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Non-visual analysis of miniaturized melt wire arrays for in-pile measurement of peak irradiation temperature

As a part of the in-pile instrumentation program, the Idaho National Laboratory (INL) has established in-house capabilities to fabricate and test new advanced manufactured printed sensors for measurement of peak temperature inside the harsh environment of a nuclear test reactor. Although nuclear test reactors may use standard methods that can provide real-time temperature information, such as thermocouples, the need for feedthroughs for real-time measurements greatly increases the cost of the experiment. Some experiments also present the problem of limited space available for instrumentation. To address this need, INL is working to improve temperature detection options for such applications. The lab is developing advanced manufactured melt wire arrays to determine peak temperatures in experiments with limited space. Furthermore, capabilities to print multiple melt wires with different melting properties on a single miniaturized unit is being established. Recent results and knowledge from this ongoing work have made it possible to develop unique temperature sensors that can accomplish user specific temperature ranges inside the harsh environments experienced during radiation testing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗