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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

MaNGA galaxy properties – II. A detailed comparison of observed and simulated spiral galaxy scaling relations

ABSTRACT We present a catalogue of dynamical properties for 2368 late-type galaxies from the MaNGA survey. The latter complements the catalogue of photometric properties for the same sample based on deep optical dark energy sky instrument legacy imaging survey (DESI) photometry processed with autoprof . Rotation curves (RCs), extracted by model-fitting H α velocity maps from the MaNGA Data Analysis Pipeline, extend out to 1.4 (1.9) Re for the primary (secondary) MaNGA samples, respectively. The RCs and ancillary MaNGA Pipe3D data products were used to construct various fundamental galaxy scaling relations that are also compared uniformly with similar relations from numerical investigation of a hundred astrophysical object (NIHAO) zoom-in simulations. Simulated NIHAO galaxies were found to broadly reproduce the observed MaNGA galaxy population for $\log (M_*/{\rm {\rm M}_{\odot })\, \gt\, 8.5}$. Some discrepancies remain, such as those pertaining to central stellar densities and the diversity of RCs due to strong feedback schemes. Also presented are spatially resolved scatters for the velocity-size-stellar mass (VRM*) structural relations using MaNGA and NIHAO samples. The scatter for these relations in the galaxian interiors is a consequence of the diversity of inner RC shapes, while scatter in the outskirts is dictated by the large range of stellar surface densities, which is itself driven by sporadic star formation. The detailed, spatially resolved scatter analysis highlights the complex interplay between local and global astrophysical processes and provides a strong constraint to numerical simulations.

Astronomy & Astrophysics↗
DOE OSTI2020

Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling

Sensitivity analysis in terrestrial ecosystem modeling is important for understanding controlling processes, guiding model development, and targeting new observations to reduce parameter and prediction uncertainty. Complex and computationally expensive terrestrial ecosystem models (TEM) limit the number of ensemble simulations, requiring sophisticated and efficient methods to analyze sensitivities of multiple model responses to different types of parameter uncertainties. In this study, we propose a distance-based global sensitivity analysis (DGSA) method. DGSA first classifies model response samples into a small set of discrete classes and then calculates the distance between parameter frequency distributions in different classes to measure the parameter sensitivity. The principle is that, if the parameter distribution is the same in each class, then the model response is insensitive to the parameter, while a large difference in the distributions indicates the parameter is influential to the response. Built on this idea, DGSA can be applied to analyze sensitivity of a single and a group of responses to different kinds of parameter uncertainties including continuous, discrete and even stochastic. Besides the main-effect sensitivity from a single parameter, DGSA can also quantify the sensitivity from parameter interactions. Additionally, DGSA is computationally efficient which can use a small number of model evaluations to obtain an accurate and statistically significant result. We applied DGSA to two TEMs, one having eight parameters and three kinds of model responses, and the other having 47 parameters and a long-period response. We demonstrated that DGSA can be used for sensitivity problems with multiple responses and high-dimensional parameters efficiently.

Lu, Dan↗
DOE OSTI2022

Multi-Modal Characterization of Nuclear Fuels and Materials at the Idaho National Laboratory Materials & Fuels Complex

The Idaho National Laboratory (INL) leads cutting-edge research pertaining to the advancement of nuclear reactor technologies, including nuclear fuels and materials. The INL Irradiated Materials Characterization Laboratory (IMCL), Electron Microscopy Laboratory (EML), and future Sample Preparation Laboratory (SPL) are available to the nuclear research community to assess the behavior of nuclear fuels and materials, efficiently and comprehensively characterizing from the engineering to atomistic scale. The IMCL is a unique, 12,000-square-foot facility located at the INL Materials and Fuels Complex designed for analysis of irradiated materials. The facility operates advanced characterization instruments that are sensitive to vibration, temperature, and electromagnetic interference in modular radiological shielding and confinement systems, granting researchers the ability to assess the microstructural, chemical, mechanical and thermophysical properties of nuclear materials, especially irradiated fuels. The EML is dedicated to advanced characterization of materials with optical and electron microscopy tools, including scanning electron microscopy/focused-ion beam (SEM/FIB) and transmission electron microscopy (TEM). Upon construction, the SPL will be a 3 story, 49,000 sq. ft facility, that is the most modern reactor structural materials testing and analysis facility in the world, designed to investigate reactor structural materials in support of life-extension programs and development of advanced reactor concepts, including mechanical testing and advanced characterization capabilities. This presentation will showcase some of the main capabilities available at both IMCL, EML, and SPL, specifically illustrating how these characterization techniques are incorporated into multi-modal characterization work scopes to elucidate the degradation of nuclear structural materials and irradiated fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Processes in DNA damage response from a whole-cell multi-omics perspective

Technological advances have made it feasible to collect multi-condition multi-omic time courses of cellular response to perturbation, but the complexity of these datasets impedes discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we report a whole-cell mechanistic analysis of HL-60 cellular response to bendamustine. We integrate both enrichment and network analysis to show the progression of DNA damage and programmed cell death over time in molecular, pathway, and process-level detail using an interactive analysis framework for multi-omics data. Our framework, Mechanism of Action Generator Involving Network analysis (MAGINE), automates network construction and enrichment analysis across multiple samples and platforms, which can be integrated into our annotated gene-set network to combine the strengths of networks and ontology-driven analysis. Taken together, our work demonstrates how multi-omics integration can be used to explore signaling processes at various resolutions and demonstrates multi-pathway involvement beyond the canonical bendamustine mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering

Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample. Additionally, the interpretation of complex samples can be difficult due to the diversity of compositions both in the mixture and within a particle. In this work, we demonstrate a method to compute and cluster similarity graphs that describe inter-particle relationships within a sample using a multi-modal few-shot learning neural network. Here, as a proof-of-concept, we show that samples known to have been exposed to gunshot residue can be distinguished from samples occasionally mistaken for gunshot residue. Our workflow builds upon standard APA techniques and data processing methods to unveil additional information in a readily interpretable and quantitatively comparable format.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.

(S)TEM↗
DOE OSTI2018

Defects Induced Magnetism in WO{sub 3} and Reduced Graphene Oxide-WO{sub 3} Nanocomposites

A series of reduced graphene oxide (rGO)-WO{sub 3} nanocomposites were prepared by hydrothermal method using GO and tungsten complex. The nanocomposites were characterized by powder XRD, Raman spectroscopy, FT-IR spectroscopy, HRTEM, XPS, photoluminescence (PL), and magnetic studies. The structural analysis confirms the hexagonal crystal structure and formation of rGO-WO{sub 3} nanocomposites. HRTEM images show rod-like shape WO{sub 3} distributed on the wrinkle structure of rGO sheets. XPS results confirm the oxidation state and oxygen vacancies present in the samples. PL spectra of the samples show blue emission and indicate the existence of surface defects and oxygen vacancies. The M–H loop of rGO-WO{sub 3} nanocomposites reveal that the co-existence of both ferro and antiferromagnetism at room temperature. The incorporation of rGO sheets notably increase magnetic behavior of composites due to extended C–C bond conducts much stronger coupling between the 5d and 6s orbitals of tungsten and carbon atoms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Evaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis

Analyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Peak selection matters in Principal Component Analysis: A case study of syntrophic microbes

In situ liquid time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful technique to address surface characterization of living biofilms in hydrated conditions. Principal component analysis (PCA) is an important tool to process a large amount of data and interpret the information from ToF-SIMS spectra. However, ToF-SIMS data analysis is still a great challenge in complicated bacterial biofilms, because many interference peaks from the medium may result in inaccurate interpretation of ToF-SIMS spectral analysis. In this study, two syntrophic Geobacter populations were investigated using in situ liquid ToF-SIMS to reveal the biofilm surface changes between them as due to direct interspecies electron transfer (DIET). Peak overlay is an effective strategy to eliminate the matrix effects in handling complex ToF-SIMS data and was used to accomplish peak selection in this work. Both all peak and selected peak spectral PCA showed a distinctive separation among different samples. However, medium samples occupied high scores values in all peak PCA compared with the selected peak PCA, suggesting a strong interference from the medium as the matrix effect. Amino acids and lipids contributed significantly in separating all samples in selected peak PCA, which indicated that surface membrane components such as pili and proteins are important in the co-cultured Geobacter community compared to controls such as the single population planktonic cells and biofilms, respectively. Additionally, the spectral PCA results of high intensity and high resolution data obtained from liquid ToF-SIMS were compared. Selected peak PCA obtained nice separation among samples in both data sets; however, the high resolution data showed better separation between co-culture planktonics and co-culture aggregates, confirming that the higher mass accuracy is useful in analysis of microbial samples. Furthermore, amino acid and water cluster as an important media for microbial metabolite were selected for a more focused selected peak PCA comparison. Consistent scores and loadings plots were achieved. In conclusion, we show that peak selection is critical for acquiring effective microbial information and interpretation of syntrophic Geobacter using spectral data from in situ liquid ToF-SIMS.

spectral overlay, peak selection, matrix effect, P↗
DOE OSTI2026

The evolution of coal porosity during pyrolysis

Gasification of coal, municipal waste, or other organic materials is a potential hydrogen source that entails complex thermal decomposition and transport processes. This study provides a multiscale analysis of these processes for sub-bituminous (Usibelli, Healy, Alaska) and lignite (Center, North Dakota) coals and provides data useful for process design. The chemistry, mineralogy, and pore structures of pyrolyzed coal and their evolution with thermal decomposition are discussed. Samples pyrolyzed at 200–1000 °C were analyzed by small-angle neutron scattering; ultra-small, small-, and wide-angle X-ray scattering; and other complementary techniques. Scanning electron microscopy showed new pores in the high-temperature-pyrolyzed material. Upon heating, the coals became progressively denser, and the concentration of hydrogen decreased. Changes in pore volume fell into three temperature ranges: an initial, low-temperature range that, for the Usibelli coal, involved an increase in overall porosity; a mid-temperature range associated with pore volume loss; and a high-temperature range associated with significant porosity increase and char formation. This transformation was paralleled by changes in fractal dimension and correlation length. The higher the pyrolysis temperature the greater the small-pore-volume fraction and overall surface area became. Pyrolysis increased the lateral size of coal crystallites, decreased the amorphous fraction, and increased the aromatics fraction and overall coal rank. Comparisons of neutron and X-ray scattering data and subsequent water uptake studies showed that pre-dried coals can re-hydrate relatively rapidly upon exposure to air, which can significantly affect the porosity calculated from small-angle-scattering data. Fits to the cumulative porosity curves provide a method for modeling the physical and chemical transformation of hydrogen-containing feedstock during gasification.

Anovitz, Lawrence {Larry} [ORNL] (ORCID:0000000226↗
DOE OSTI2022

Mesoscale structural gradients in human tooth enamel

The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Multi-omics of a model bacterial consortium deciphers details of chitin decomposition in soil

Soil microorganisms interact to carry out decomposition of complex organic carbon and nitrogen compounds, such as chitin, but the high diversity and complexity of the soil microbiome and habitat have posed a challenge to elucidating such interactions. Here, we sought to address this challenge by analysis of a model soil consortium (MSC-2) consisting of eight soil bacterial species. Our aim was to elucidate the specific roles of the member species during chitin metabolism. Samples were collected from MSC-2 incubated in chitin-enriched soil over 3 months. Multi-omics was used to understand how the community composition, transcripts, proteins, and chitin decomposition shifted over time. The data clearly and consistently revealed a temporal shift during chitin decomposition with defined contributions by individual species. A Streptomyces genus member (sp001905665) was a key player in early steps of chitin decomposition, with other MSC-2 members being central in carrying out later steps. These results illustrate how multi-omics applied to a defined consortium untangles the interactions between soil microorganisms.

chitin↗
DOE OSTI2021

WRF-simulated low-level jets over Iowa: characterization and sensitivity studies

Abstract. Output from 6 months of high-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize local low-level jets (LLJs) over Iowa for winter and spring in the contemporary climate. Low-level jets affect rotor plane aerodynamic loading, turbine structural loading and turbine performance, and thus accurate characterization and identification are pertinent. Analyses using a detection algorithm wherein the wind speed above and below the jet maximum must be below 80 % of the jet wind speed within a vertical window of approximately 20–530 m a.g.l. (above ground level) indicate the presence of an LLJ in at least one of the 14 700 4 km×4 km grid cells over Iowa on 98 % of nights. Nocturnal LLJs are most frequently associated with stable stratification and low turbulent kinetic energy (TKE) and hence are more frequent during the winter months. The spatiotemporal mean LLJ maximum (jet core) wind speed is 9.55 m s−1, and the mean height is 182 m. Locations of high LLJ frequency and duration across the state are seasonally varying, with a mean duration of 3.5 h. The highest frequency occurs in the topographically complex northwest of the state in winter and in the flatter northeast of the state in spring. Sensitivity of LLJ characteristics to the (i) LLJ definition and (ii) vertical resolution at which the WRF output is sampled is examined. LLJ definitions commonly used in the literature are considered in the first sensitivity analysis. These sensitivity analyses indicate that LLJ characteristics are highly variable with definition. Use of different definitions identifies both different frequencies of LLJs and different LLJ events. Further, when the model output is down-sampled to lower vertical resolution, the mean jet core wind speed height decreases, but spatial distributions of regions of high frequency and duration are conserved. Implementation of a polynomial interpolation to extrapolate down-sampled output to full-resolution results in reduced sensitivity of LLJ characteristics to down-sampling.

17 WIND ENERGY↗
DOE OSTI2017

Method for Hot Real-Time Sampling of Gasification Products

The Thermochemical Process Development Unit (TCPDU) at the National Renewable Energy Laboratory (NREL) is a highly instrumented half-ton/day pilot scale plant capable of demonstrating industrially relevant thermochemical technologies from lignocellulosic biomass conversion, including gasification. Gasification creates primarily Syngas (a mixture of Hydrogen and Carbon Monoxide) that can be utilized with synthesis catalysts to form transportation fuels and other valuable chemicals. Biomass derived gasification products are a very complex mixture of chemical components that typically contain Sulfur and Nitrogen species that can act as catalysis poisons for tar reforming and synthesis catalysts. Real-time hot online sampling techniques, such as Molecular Beam Mass Spectrometry (MBMS), and Gas Chromatographs with Sulfur and Nitrogen specific detectors can provide real-time analysis providing operational indicators for performance. Sampling typically requires coated sampling lines to minimize trace sulfur interactions with steel surfaces. Other materials used inline have also shown conversion of sulfur species into new components and must be minimized. Sample line Residence time within the sampling lines must also be kept to a minimum to reduce further reaction chemistries. Solids from ash and char contribute to plugging and must be filtered at temperature. Experience at NREL has shown several key factors to consider when designing and installing an analytical sampling system for biomass gasification products. They include minimizing sampling distance, effective filtering as close to source as possible, proper line sizing, proper line materials or coatings, even heating of all components, minimizing pressure drops, and additional filtering or traps after pressure drops.

09 BIOMASS FUELS↗
DOE OSTI2016

Mechanochemical synthesis and intercalation of Ca(II)Fe(III)-layered double hydroxides

A mechanochemical method (grinding the components without added water – dry grinding, followed by further grinding in the presence of minute amount of water or NaOH solution – wet grinding) was used in this work for the preparation and intercalation of CaFe-layered double hydroxides (LDHs). Both the pristine LDHs and the amino acid anion (cystinate and tyrosinate) intercalated varieties were prepared by the two-step grinding procedure in a mixer mill. By systematically changing the conditions of the preparation method, a set of parameters could be determined, which led to the formation of close to phase-pure LDH. The optimisation procedure was also applied for the intercalation processes of the amino acid anions. The resulting materials were structurally characterised by a range of methods (X-ray diffractometry, scanning electron microscopy, energy dispersive analysis, thermogravimetry, X-ray absorption and infra-red spectroscopies). It was proven that this simple mechanochemical procedure was able to produce complex organic–inorganic nanocomposites: LDHs intercalated with amino acid anions. - Graphical abstract: Amino acid anion-Ca(II)Fe(III)-LDHs were successfully prepared by a two-step milling procedure. - Highlights: • Synthesis of pristine and amino acid intercalated CaFe-LDHs by two-step milling. • Identifying the optimum synthesis and intercalation parameters. • Characterisation of the samples with a range of instrumental methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Actinide Elemental Ratios of Spent Nuclear Fuel Samples by Resonance Ionization Mass Spectrometry

While resonance ionization mass spectrometry (RIMS) has demonstrated utility in measuring isotopic compositions of elements in complex matrices without the need for chemical separation to remove isobaric interferences, it has had limited application in measuring elemental compositions. The ability to determine elemental compositions via an in situ method like RIMS would be an exceptional asset in spent nuclear fuel analysis, where they are important in assessing reactor histories and whose chemical separation presents a radiological hazard. However, quantitative elemental analysis by RIMS requires special considerations because each element is ionized by its own set of lasers tuned to element specific resonant ionization wavelengths. We present the first comprehensive study of measuring elemental ratios by RIMS in spent nuclear fuel. All actinides produced by neutron capture are enhanced significantly radially from the center to the edge of a fuel pellet. This edge effect is not readily accessible by conventional bulk measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A Comparative Metagenomic Analysis of Specified Microorganisms in Groundwater for Non-Sterilized Pharmaceutical Products

In pharmaceutical manufacturing, ensuring product safety involves the detection and identification of microorganisms with human pathogenic potential, including Burkholderia cepacia complex (BCC), Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Staphylococcus aureus, Clostridium sporogenes, Candida albicans, and Mycoplasma spp., some of which may be missed or not identified by traditional culture-dependent methods. In this study, we employed a metagenomic approach to detect these taxa, avoiding the limitations of conventional cultivation methods. We assessed the groundwater microbiome’s taxonomic and functional features from samples collected at two locations in the spring and summer. All datasets comprised 436–557 genera with Proteobacteria, Bacteroidota, Firmicutes, Actinobacteria, and Cyanobacteria accounting for > 95% of microbial DNA sequences. The aforementioned species constituted less than 18.3% of relative abundance. Escherichia and Salmonella were mainly detected in Hot Springs, relative to Jefferson, while Clostridium and Pseudomonas were mainly found in Jefferson relative to Hot Springs. Multidrug resistance efflux pumps and BlaR1 family regulatory sensor-transducer disambiguation dominated in Hot Springs and in Jefferson. These initial results provide insight into the detection of specified microorganisms and could constitute a framework for the establishment of comprehensive metagenomic analysis for the microbiological evaluation of pharmaceutical-grade water and other non-sterile pharmaceutical products, ensuring public safety.

59 BASIC BIOLOGICAL SCIENCES↗