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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effect of bimetallic modification on blast furnace slag and its application in low‐temperature selective catalytic reduction

Abstract Objective In order to control NO x in low‐temperature flue gases emitted from non‐power industries and to reduce the preparation cost of denitration catalysts, this study uses inexpensive blast furnace slag as raw material to prepare denitration catalysts. Methods After cooling, drying and grinding, the blast furnace slag becomes a powder with considerable fineness and meets the requirements of activity index, which is called GGBS (ground granulated blast furnace slag). Using GGBS as denitration catalyst carrier, the active components M (M = Fe, Co, Ni, Cu and Ce) are loaded on Mn‐based GGBS catalyst using an impregnation method. Conclusions The effect of different active components on the denitration performance and sulfur resistance of Mn‐based GGBS catalysts is investigated. The results show that the Mn‐Ce/GGBS catalyst has better denitration performance and sulfur resistance. The Mn‐Ce/GGBS catalyst has a significant denitration performance when load ratio is 2:1. The active component Ce improves the denitration performance of the catalyst, reduces sulfur poisoning and extends the life of the catalyst. The SO 2 in the flue gas increases the acid sites on the catalyst surface and improves catalyst activity. The larger the ratios of Mn 4+ /Mn 3+ , Ce 4+ /Ce 3+ and O α /O β , the stronger the catalyst activity and the better the denitration performance. © 2022 Society of Chemical Industry (SCI).

Zhang, Lei↗
DOE OSTI2022

Improved Boundary Conditions for Coupled Geospace Models: An Application in Modeling Spacecraft Surface Charging Environment

Abstract Spacecraft surface charging in the inner magnetosphere often occurs in the pre‐midnight to the dawn sector when electron fluxes of tens of keV increase. Inner magnetosphere ring current models can be used to simulate/predict the spacecraft surface charging environment, with their outer boundary conditions specified either based on observations or provided by other models, such as MHD models. In the latter approach, using MHD quantities, the flux spectrum at the outer boundary is commonly assumed to follow a Kappa or Maxwellian distribution function. Such a method however often departs greatly from the realistic spectrum at E < tens of keV, a crucial energy range in the surface charging anomaly. In order to achieve a better representation of the surface charging environment, we propose to combine the MHD‐parameterized flux spectrum with an empirical electron flux model of E < 40 keV to set the electron flux boundary condition. Results indicate that as opposed to the case where the MHD‐parameterized flux distribution is solely used at the model boundary, simulations with the new boundary condition yields a more intense surface charging environment. The integrated electron flux between 10 < E < 50 keV, a measure of the severity of the surface charging environment, is significantly enhanced by 1‐2 orders of magnitude, leading to a much better agreement with Van Allen Probes measurements. This study hence demonstrates a reasonable solution to the setting of outer boundary conditions for inner magnetosphere models and is recommended for coupled geospace circulation models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

Abstract A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the impact of artificial intelligence (AI) in the practice of science and engineering, we introduce a set of practical, concise, and measurable FAIR principles for AI models. We showcase how to create and share FAIR data and AI models within a unified computational framework combining the following elements: the Advanced Photon Source at Argonne National Laboratory, the Materials Data Facility, the Data and Learning Hub for Science, and funcX, and the Argonne Leadership Computing Facility (ALCF), in particular the ThetaGPU supercomputer and the SambaNova DataScale ® system at the ALCF AI Testbed. We describe how this domain-agnostic computational framework may be harnessed to enable autonomous AI-driven discovery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Thermodynamic modeling of the Ti-Nb-Sn system and its preliminary applications in aging precipitation and solidification simulations

Abstract Gasping the thermodynamic and phase diagram of the materials being studied is essential for further guiding the development process, like composition design, heat treatment optimization and so on. Nb and Sn are common alloying elements in Ti-based biomedical alloys. In this work, the Ti-Nb-Sn system has been thermodynamically assessed based on experimental phase equilibria. A self-consistent thermodynamic description for the Ti-Nb-Sn system including two ternary compounds Ti 3 Nb 3 Sn 2 and Ti 3 NbSn has been obtained. Based on the comparison between the calculated and experimental phase equilibria, the reliability of the presently obtained thermodynamic description has been verified. The influence of Nb and Sn contents on the precipitation temperature and amount of hcp α -Ti phase in bcc β -(Ti, Nb) has been investigated based on thermodynamic calculations. Results show that the increase of Nb or Sn content in Ti-based alloys would significantly reduce the precipitation amount and transformation temperature of hcp α -Ti phase in bcc β -(Ti, Nb) and the influence of Nb content is more effective than that of Sn. The solidified phases in several as-cast alloys have been thermodynamically predicted based on Scheil solidification simulations. The presently developed thermodynamic description of the Ti-Nb-Sn system can serve as a sub-ternary one in the thermodynamic database for multicomponent Ti-based biomedical alloys.

Peng, Yingbiao↗
DOE OSTI2023

Recent DIII-D progress toward validating models of tungsten erosion, re-deposition, and migration for application to next-step fusion devices

Abstract Fundamental mechanisms governing the erosion and prompt re-deposition of tungsten impurities in tokamak divertors are identified and analyzed to inform the lifetime of tungsten plasma-facing components in ITER and other future devices. Various experiments conducted at DIII-D to benchmark predictive models are presented, leveraging the DiMES removable sample exposure probe capability and the Metal Rings Campaign, in which toroidally symmetric rows of tungsten-coated tiles were installed in the DIII-D divertor. In tokamak divertors, the width of the electric sheath is of the order of the main ion Larmor radius, and a vast majority of sputtered tungsten impurities are typically ionized within the sheath. Therefore, W prompt redeposition is mainly governed by the ratio of the characteristic ionization mean-free path of neutral tungsten to the width of the sheath. In-situ monitoring of the prompt redeposition of tungsten impurities in divertors is demonstrated via the use of WII/WI line ratios and the ionizations/photon (S/XB) method in L-mode discharges. Even with this relatively limited set of emission measurements, net erosion measurements were found to be a consistent upper bound to an analytic scaling based on the ratio of the W ionization length, λ iz , and the width of the magnetic sheath rather than the ratio of λ iz and the W + gyro-radius. In the far-scrape-off layer (SOL) of the ITER divertor, however, it is calculated that the measurement of photon emissions associated with the ionization of tungsten impurities up to W 5 + may be required. Finally, W deposition patterns on DiMES collector probes, interpreted via DIVIMP-WallDYN modelling, reveal the key roles of progressive W erosion/re-deposition staps and E × B drifts in regulating long-range high-Z material migration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Actinomycetota isolated from the sponge Hymeniacidon perlevis as a source of novel compounds with pharmacological applications: diversity, bioactivity screening, and metabolomic analysis

Abstract Aims To combat health conditions, such as multi-resistant bacterial infections, cancer, and metabolic diseases, new drugs need to be urgently found and, in this respect, marine Actinomycetota have a high potential to produce secondary metabolites with pharmacological importance. We aimed to study the cultivable Actinomycetota community associated with a marine sponge from the Portuguese coast, Hymeniacidon perlevis, and investigate the potential of the retrieved isolates to produce compounds with antimicrobial, anticancer and anti-obesity properties. Methods and results The analysis of the 16S rRNA gene revealed 79 Actinomycetota isolates affiliated with 12 genera—Brachybacterium, Dietzia, Glutamicibacter, Gordonia, Micrococcus, Micromonospora, Nocardia, Nocardiopsis, Paenoartrhobacter, Rhodococcus, Streptomyces, and Tsukamurella, most of which affiliated with the genus Streptomyces. The screening of antimicrobial activity revealed 13 strains, all belonging to the Streptomyces genus, capable of inhibiting the growth of Candida albicans, Bacillus subtilis, or Staphylococcus aureus. Forty-three extracts exhibited cytotoxic activity against at least one tested cell line (HepG2, HCT-116, and hCMEC-D3). Three extracts that were active against the two cancer cell lines tested, did not reduce the viability of the non-cancer endothelial cell line, hCMEC-D3. One Gordonia strain exhibited anti-obesity activity, revealed by its ability to reduce the neutral lipids in zebrafish larvae. Mass spectrometry-based dereplication analysis of active extracts identified several compounds associated with known Actinomycetota natural products. Nonetheless, five clusters contained metabolites that did not match any annotated natural products, suggesting they may represent new bioactive molecules. Conclusions This work contributed to increase the knowledge on the diversity and bioactive potential of Actinomycetota associated with H. perlevis.

Fonseca, Ana C.↗
DOE OSTI2022

Leaf microscopy applications in photosynthesis research: identifying the gaps

Abstract Leaf imaging via microscopy has provided critical insights into research on photosynthesis at multiple junctures, from the early understanding of the role of stomata, through elucidating C4 photosynthesis via Kranz anatomy and chloroplast arrangement in single cells, to detailed explorations of diffusion pathways and light utilization gradients within leaves. In recent decades, the original two-dimensional (2D) explorations have begun to be visualized in three-dimensional (3D) space, revising our understanding of structure–function relationships between internal leaf anatomy and photosynthesis. In particular, advancing new technologies and analyses are providing fresh insight into the relationship between leaf cellular components and improving the ability to model net carbon fixation, water use efficiency, and metabolite turnover rate in leaves. While ground-breaking developments in imaging tools and techniques have expanded our knowledge of leaf 3D structure via high-resolution 3D and time-series images, there is a growing need for more in vivo imaging as well as metabolite imaging. However, these advances necessitate further improvement in microscopy sciences to overcome the unique challenges a green leaf poses. In this review, we discuss the available tools, techniques, challenges, and gaps for efficient in vivo leaf 3D imaging, as well as innovations to overcome these difficulties.

Plant Sciences↗
DOE OSTI2025

The XMM Cluster Survey: automating the estimation of hydrostatic mass for large samples of galaxy clusters – I. Methodology, validation, and application to the SDSSRM-XCS sample

ABSTRACT We describe features of the X-ray: Generate and Analyse (xga) open-source software package that have been developed to facilitate automated hydrostatic mass ($M_{\rm hydro}$) measurements from XMM X-ray observations of clusters of galaxies. This includes describing how xga measures global, and radial, X-ray properties of galaxy clusters. We then demonstrate the reliability of xga by comparing simple X-ray properties, namely the X-ray temperature and gas mass, with published values presented by the XMM Cluster Survey (XCS), the Ultimate XMM eXtragaLactic survey project (XXL), and the Local Cluster Substructure Survey (LoCuSS). xga measured values for temperature are, on average, within 1 per cent of the values reported in the literature for each sample. xga gas masses for XXL clusters are shown to be ${\sim }$10 per cent lower than previous measurements (though the difference is only significant at the $\sim 1.8\sigma$ level), LoCuSS $R_{2500}$ and $R_{500}$ gas mass re-measurements are 3 per cent and 7 per cent lower, respectively (representing 1.5$\sigma$ and 3.5$\sigma$ differences). Like-for-like comparisons of hydrostatic mass are made to LoCuSS results, which show that our measurements are $10{\pm }3~{{\rm per\ cent}}$ ($19{\pm }7~{{\rm per\ cent}}$) higher for $R_{2500}$ ($R_{500}$). The comparison between $R_{500}$ masses shows significant scatter. Finally, we present new $M_{\rm hydro}$ measurements for 104 clusters from the Sloan Digital Sky Survey (SDSS) DR8 redMaPPer XCS sample (SDSSRM-XCS). Our SDSSRM-XCS hydrostatic mass measurements are in good agreement with multiple literature estimates, and represent one of the largest samples of consistently measured hydrostatic masses. We have demonstrated that xga is a powerful tool for X-ray analysis of clusters; it will render complex-to-measure X-ray properties accessible to non-specialists.

Turner, D. J. (ORCID:0000000196581396)↗
DOE OSTI2022

Impact of Timing in the Design Process on Students’ Application of Design for Additive Manufacturing Heuristics

The goal of this work is to study the way student designers use design for additive manufacturing (DfAM) rules or heuristics. It can be challenging for novice designers to create successful designs for additive manufacturing (AM), due to its recent surge in popularity and lack of formal education or training. A study was carried out to investigate the way novices apply DfAM heuristics when they receive them at different points in the design process. A design problem was presented to students, and three different groups of student participants were given a lecture on DfAM heuristics at three different points in the design process: before the initial design, between the initial design and redesign, and after the redesign. The novelty and quality of each of the resulting designs were evaluated. Results indicate that although the DfAM heuristics lecture had no impact on the overall quality of the designs generated, participants who were given the heuristics lecture after the initial design session produced designs that were better-suited for 3D printing in the second phase of the design activity. However, receiving this additional information appears to prevent students from creatively iterating upon their initial designs, as participants who received heuristic information between the design sessions experienced a decrease in novelty between the two sessions. Additionally, receiving the heuristics lecture increased all students’ perceptions of their ability to perform DfAM-related tasks. Furthermore, these results validate the practicality of design heuristics in lecture form as AM training tools while also emphasizing the importance of iteration in the design process.

computer-aided design↗