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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A comparison of compact, presumably young with extended, evolved radio active galactic nuclei

Context.The triggering and evolution of active galactic nuclei (AGNs) and the interaction of the AGN with its host galaxy is an important topic in extragalactic astrophysics. Radio sources with peaked spectra (peaked spectrum sources, PSS) and compact symmetric objects (CSO) are powerful, compact, and presumably young AGNs and therefore particularly suitable to study aspects of the AGN-host connection. Aims.We use a statistical approach to investigate properties of a PSS-CSO sample that are related to host galaxies and could potentially shed light on the link between host galaxies and AGNs. The main goal is to compare the PSS-CSO sample with a matching comparison sample of extended sources (ECS) to see if the two have significant differences. Methods.We analysed composite spectra, diagnostic line diagrams, multi-band spectral energy distributions (MBSEDs), star formation (SF) indicators, morphologies, and cluster environments for a sample of 121 PSSs and CSOs for which spectra are available from the Sloan Digital Sky Survey (SDSS). The statistical results were compared with those of the ECS sample, where we generally considered the two subsamples of quasi-stellar objects (QSOs) and radio galaxies separately. The analysis is based on a large set of archival data in the spectral range from the ultraviolet to mid-infrared. Results.We find significant differences between the PSS-CSO and the ECS sample. In particular, we find that the ECS sample has a higher proportion of passive galaxies with a lower star formation activity. This applies to both sub-samples (QSOs or radio galaxies) as well as to the entire sample. The star formation rates of the PSS-CSO host galaxies with available data are typically in the range ∼0 to 5 ℳ ⊙ yr −1 , and the stellar masses are in the range 3 × 10 11 to 10 12 ℳ ⊙ . Secondly, in agreement with previous results, we find a remarkably high proportion of PSS-CSO host galaxies with merger signatures. The merger fraction of the PSS-CSO sample is 0.61 ± 0.07, which is significantly higher than that of the comparison sample (0.15 ± 0.06). We suggest that this difference can be explained by assuming that the majority of the PSSs and CSOs cannot evolve to extended radio sources and are therefore not represented in our comparison sample.

Astronomy & Astrophysics↗
DOE OSTI2022

Microbial communities of Auka hydrothermal sediments shed light on vent biogeography and the evolutionary history of thermophily

Abstract Hydrothermal vents have been key to our understanding of the limits of life, and the metabolic and phylogenetic diversity of thermophilic organisms. Here we used environmental metagenomics combined with analysis of physicochemical data and 16S rRNA gene amplicons to characterize the sediment-hosted microorganisms at the recently discovered Auka vents in the Gulf of California. We recovered 325 metagenome assembled genomes (MAGs) representing 54 phyla, over 30% of those currently known, showing the microbial community in Auka hydrothermal sediments is highly diverse. 16S rRNA gene amplicon screening of 224 sediment samples across the vent field indicates that the MAGs retrieved from a single site are representative of the microbial community in the vent field sediments. Metabolic reconstruction of a vent-specific, deeply branching clade within the Desulfobacterota suggests these organisms metabolize sulfur using novel octaheme cytochrome-c proteins related to hydroxylamine oxidoreductase. Community-wide comparison between Auka MAGs and MAGs from Guaymas Basin revealed a remarkable 20% species-level overlap, suggestive of long-distance species transfer over 400 km and subsequent sediment colonization. Optimal growth temperature prediction on the Auka MAGs, and thousands of reference genomes, shows that thermophily is a trait that has evolved frequently. Taken together, our Auka vent field results offer new perspectives on our understanding of hydrothermal vent microbiology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

How machine learning can extend electroanalytical measurements beyond analytical interpretation

Electroanalytical measurements are routinely used to estimate material properties exhibiting current and voltage signatures. Analysis of such measurements relies on analytical expressions of material properties to describe the experiments. The need for analytical expressions limits the experiments that can be used to measure properties as well as the properties that can be estimated from a given experiment. Such analytical relations are essentially solutions of the physics-based differential equations (with properties as coefficients) describing the material behavior under certain specific conditions. In recent years, a new machine learning-based approach has been gaining popularity wherein the differential equations are numerically solved to interpret the electroanalytical experiments in terms of corresponding material properties. Since the physics-based differential equations are solved, one can additionally estimate underlying fields, e.g., concentration profile, using such an approach. To exemplify the characteristics of such a machine learning assisted interpretation of electroanalytical measurements, we use data from the Hebb–Wagner test on a magnesium spinel intercalation host. In conclusion, as compared to the traditional analytical expression-based interpretation, the emerging approach decreases experimental efforts to characterize relevant material properties as well as provides field information that was previously inaccessible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Strongly correlated itinerant magnetism near superconductivity in NiTa 4 Se 8

Metallic ferromagnets with strongly interacting electrons often exhibit remarkable electronic phases such as ferromagnetic superconductivity, complex spin textures, and nontrivial topology. Here, in this report, we discuss the synthesis of a layered magnetic metal NiTa 4 Se 8 (or Ni 1/4 TaSe 2 ) with a Curie temperature of 58 Kelvin. Magnetization data and density functional theory calculations indicate that the nickel atoms host uniaxial ferromagnetic order of about 0.7µ B per atom, while an even smaller moment is generated in the itinerant tantalum conduction electrons. Strong correlations are evident in flat bands near the Fermi level, a high heat capacity coefficient, and a high Kadowaki-Woods ratio. Density functional theory calculations suggest that electron and hole Fermi surfaces in the ferromagnetic phase are associated with opposite spin polarization. When the system is diluted of magnetic ions, the samples become superconducting below about 2 Kelvin. We discuss possible mechanisms for superconductivity in this family.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Simple Analysis of Primary and Secondary Bile Salt Hydrolysis in Mouse and Human Gut Microbiome Samples by Using Fluorogenic Substrates

Animals produce bile to maximize absorption of lipophilic nutrients in the gut. The physical properties of bile are largely dictated by amphipathic bile salt molecules, which also act as signaling molecules that bind host receptors and modulate physiological processes. Upon excretion of bile salts into the gut, the gut microbiome can create metabolites that have modified signaling capabilities. The category and magnitude of bile salt metabolism can affect the host either positively or negatively. A key modification is bile salt hydrolysis, which is a prerequisite step for all additional microbial modification. Here, we have synthesized five different fluorogenic bile salts that report on hydrolysis activity using a simple, continuous assay. We profile activity in both murine and human fecal samples. Our data demonstrate that most gut microbiomes have the highest capacity for hydrolysis of host-produced bile salts, but some microbially modified bile salts also display significant turnover.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Experimental validation that human microbiome phages use alternative genetic coding

Previous bioinformatic analyses of metagenomic data have indicated that bacteriophages can use genetic codes different from those of their host bacteria. In particular, reassignment of stop codon TAG to glutamine (a variation known as ‘genetic code 15’) has been predicted. Here, we use LC-MS/MS-based metaproteomics of human fecal samples to provide experimental evidence of the use of genetic code 15 in two crAss-like phages. Furthermore, the proteomic data from several phage structural proteins supports the reassignment of the TAG stop codon to glutamine late in the phage infection cycle. Thus, our work experimentally validates the expression of genetic code 15 in human microbiome phages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(εM_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{αx}+1) + δ[\log(1+\exp(x))]^γ/ [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log ε= -1.632^{+0.306}_{-0.181}$, $α= -1.638^{+0.108}_{-0.099}$, $γ= 0.596^{+0.251}_{-0.210}$ and $δ= 3.810^{+2.045}_{-1.811}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

Zacharegkas, G. [Argonne; Chicago U., KICP] (ORCID↗
DOE OSTI2025

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗
DOE OSTI2025

The ambiguous AT2022rze: changing-look AGN mimicking a supernova in a merging galaxy system

AT2022rze is a luminous, ambiguous transient located south-east of the geometric centre of its host galaxy at redshift $z = 0.08$. The host appears to be formed by a merging galaxy system. The observed characteristics of AT2022rze are reminiscent of active galactic nuclei (AGNs), tidal disruption events, and superluminous supernovae. The transient reached a peak absolute magnitude of $-$20.2 $\pm$ 0.2 mag, showing a sharp rise (t$_{\mathrm{rise,1/e}} = 27.5 \pm 0.6$ d) followed by a slow decline (t$_{\mathrm{dec,1/e}} = 382.9 \pm 0.6$). Its bumpy light curve and narrow Balmer lines indicate the presence of gas (and dust). Its light curve shows rather red colours, indicating that the transient could be affected by significant host extinction. The spectra reveal coronal lines, indicative of high-energy (X-ray/UV) emission. Archival data reveal no prior activity at this location, disfavouring a steady-state AGN, although an optical spectrum obtained prior to the transient is consistent with an AGN classification of the host. Based on this, we conclude that the transient most likely represents a changing-look AGN at the centre of the smallest component of the merging system.

galaxies: active↗
DOE OSTI2025

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Applying 3D Geologic Modeling Workflows to the Argillite Reference Case (Rev. 1)

The objective of this short report is to document the application of our 3D geologic modeling workflow to an argillite (shale) host rock. Over the past four years, our team at Los Alamos National Laboratory has developed a geologic modeling workflow that can be applied to generic alluvial basins such as those found in the western United States. In “frontier” or “exploratory” basins where data are sparse, the first steps are to collect, evaluate and integrate available subsurface data into conceptual geologic models. Those models form the basis for constructing the geologic framework model, a 3D geocellular model ideally constrained by seismic and borehole data. To date we have constructed our models using “synthetic” well data derived from conceptual models, without the prospect of validating our workflow using “real” subsurface data. We were tasked to investigate whether our workflow designed for alluvial basin sediments could be applied to other potential repository host rocks. This task also provided the opportunity to work with high-quality subsurface data collected specifically for siting and evaluating a nuclear waste repository. Nagra, the Swiss governmental agency responsible for the disposal of the nation’s radioactive waste, generously provided us with data from two deep boreholes drilled through their argillaceous target formation. The aim of our proof-of-concept demonstration is to evaluate whether geostatistical methods offer a viable approach to property modeling in argillaceous rocks. Nagra provided us with the well data on the condition that we maintain confidentiality with all transferred information and results. Fortunately, Nagra posts numerous technical reports on its public website that describe the subsurface geology in great detail. All of the information and illustrations in this report related to the Swiss repository enterprise are taken from the Nagra public website.

58 GEOSCIENCES↗
DOE OSTI2022

Extending the SAGA Survey (xSAGA). I. Satellite Radial Profiles as a Function of Host-galaxy Properties

We present "Extending the Satellites Around Galactic Analogs Survey" (xSAGA), a method for identifying low-z galaxies on the basis of optical imaging and results on the spatial distributions of xSAGA satellites around host galaxies. Using spectroscopic redshift catalogs from the SAGA Survey as a training data set, we have optimized a convolutional neural network (CNN) to identify z < 0.03 galaxies from more-distant objects using image cutouts from the DESI Legacy Imaging Surveys. From the sample of >100,000 CNN-selected low-z galaxies, we identify >20,000 probable satellites located between 36–300 projected kpc from NASA-Sloan Atlas central galaxies in the stellar-mass range $9.5\lt \mathrm{log}({M}_{\star }/{M}_{\odot })\lt 11$. We characterize the incompleteness and contamination for CNN-selected samples and apply corrections in order to estimate the true number of satellites as a function of projected radial distance from their hosts. Satellite richness depends strongly on host stellar mass, such that more-massive host galaxies have more satellites, and on host morphology, such that elliptical hosts have more satellites than disky hosts with comparable stellar masses. We also find a strong inverse correlation between satellite richness and the magnitude gap between a host and its brightest satellite. The normalized satellite radial distribution between 36–300 kpc does not depend on host stellar mass, morphology, or magnitude gap. The satellite abundances and radial distributions we measure are in reasonable agreement with predictions from hydrodynamic simulations. Our results deliver unprecedented statistical power for studying satellite galaxy populations and highlight the promise of using machine-learning for extending galaxy samples of wide-area surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

QUOTAS: A New Research Platform for the Data-driven Discovery of Black Holes

We present QUOTAS, a novel research platform for the data-driven investigation of supermassive black hole (SMBH) populations. While SMBH data—observations and simulations—have grown in complexity and abundance, our computational environments and tools have not matured commensurately to exhaust opportunities for discovery. To explore the BH, host galaxy, and parent dark matter halo connection—in this pilot version—we assemble and colocate the high-redshift, z > 3 quasar population alongside simulated data at the same cosmic epochs. As a first demonstration of the utility of QUOTAS, we investigate correlations between observed Sloan Digital Sky Survey (SDSS) quasars and their hosts with those derived from simulations. Leveraging machine-learning algorithms (ML), to expand simulation volumes, we show that halo properties extracted from smaller dark-matter-only simulation boxes successfully replicate halo populations in larger boxes. Next, using the Illustris-TNG300 simulation that includes baryonic physics as the training set, we populate the larger LEGACY Expanse dark-matter-only box with quasars, and show that observed SDSS quasar occupation statistics are accurately replicated. First science results from QUOTAS comparing colocated observational and ML-trained simulated data at z3 are presented. QUOTAS demonstrates the power of ML, in analyzing and exploring large data sets, while also offering a unique opportunity to interrogate theoretical assumptions that underpin accretion and feedback models. QUOTAS and all related materials are publicly available at the Google Kaggle platform. (The full data set—observational data and simulation data—are available at: https://www.kaggle.com/ and the codes are available at:https://www.kaggle.com/datasets/quotasplatform/quotas)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Method and apparatus for scheduling in a non-uniform compute device

A data processing apparatus, and method of operation thereof, for executing instructions. The apparatus includes one or more host processors, each having a first processing unit, and a multi-level memory system. One or more levels of the memory system are tightly coupled to a corresponding second processing unit. At least one of the host processors includes an instruction scheduler that routes instructions selectively to at least one of the first and second processing units, dependent upon the availability of the processing units and the location, within the memory system, of data to be used when executing the instructions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Understanding the Nature of an Unusual Post-starburst Quasar with Exceptionally Strong Ne v Emission

We present a z = 0.94 quasar, SDSS J004846.45-004611.9, discovered in the Sloan Digital Sky Survey III (SDSS-III) BOSS survey. A visual analysis of this spectrum reveals highly broadened and blueshifted narrow emission lines, in particular, [Ne v] λ3426 and [O III ] λ5007, with outflow velocities of 4000 km s -1 , along with unusually large [Ne v] λ3426/[Ne III ] λ3869 ratios. The gas shows higher ionization at higher outflow velocities, indicating a connection between the powerful outflow and the unusual strength of the high ionization lines. The spectral energy distribution and the i – W3 color of the source reveal that it is likely a core extremely red quasar (ERQ); a candidate population of young active galactic nuclei (AGN) that are violently blowing out gas and dust from their centers. The dominance of host galaxy light in its spectrum and its fortuitous position in the SDSS S82 region allows us to measure its star formation history and investigate variability for the first time in an ERQ. Our analysis indicates that SDSS J004846.45-004611.9 underwent a short-lived starburst phase 400 Myr ago and was subsequently quenched, possibly indicating a time lag between star formation quenching and the onset of AGN activity. We also find that the strong extinction can be uniquely attributed to the AGN and does not persist in the host galaxy, contradicting a scenario where the source has recently transitioned from being a dusty submillimeter galaxy. In our relatively shallow photometric data, the source does not appear to be variable at 0.24–2.4 μm in the rest frame, most likely due to the dominant contribution of host galaxy starlight at these wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Characterizing the combined impact of nucleation-driven precipitation and secondary passivation on carbon mineralization

The evolution of mineral reactive surface area is one of the primary phenomena controlling the progression and extent of mineral carbonation. The CO 2 mineralization begins with nucleation of crystals that provide initial surface area for subsequent growth of the mineral. However, many reactive transport models (RTMs) for CO 2 mineralization do not include the nucleation process. The few RTMs that do include it are yet to be validated against experimental data. Similarly, many RTMs ignore passivating effects of the secondary mineral, which coats the surface of the dissolving mineral, slow down the reaction process, and reduce the total extent of carbonation. Furthermore, the combined impact of nucleation and passivation on carbon mineralization is yet to be properly characterized. In this study, we consider the coupled effects of passivation and nucleation on the mineralization extent. The nucleation-driven precipitation model relies on the formation of nuclei to provide a surface area for crystal growth, while a new model is proposed to account for passivation effects. Our analysis shows that (i) omission of nucleation leads to overestimation of extent of mineralization, and (ii) omission of passivation leads to overestimation of host rock reactivity. The model was evaluated via comparison with CO 2 mineralization data from the literature and models that ignore these processes. We observed that including nucleation and passivation lead to closer predictions of the CO 2 mineralization extent. Therefore, this study highlights the importance of including the coupled nucleation-driven precipitation and secondary passivation in RTMs. Here, the findings from the study can be applied in various scientific and engineering applications such as petroleum production, cement carbonation, CO 2 sequestration, chemical weathering, and concrete degradation.

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

A novel Bayesian approach for decomposing the radio emission of quasars: I. Modelling the radio excess in red quasars

ABSTRACT Studies show that both radio jets from the active galactic nuclei (AGNs) and the star formation (SF) activity in quasar host galaxies contribute to the quasar radio emission; yet their relative contributions across the population remain unclear. Here, we present an improved parametric model that allows us to statistically separate the SF and AGN components in observed quasar radio flux density distributions, and investigate how their relative contributions evolve with AGN bolometric luminosity ($L_\mathrm{bol}$) and redshift (z) using a fully Bayesian method. Based on the newest data from LOw-Frequency ARray Two-metre Sky Survey data release 2, our model gives robust fitting results out to $z\sim 4$, showing a quasar host galaxy SF rate (SFR) evolution that increases with bolometric luminosity and with redshift out to $z\sim 4$. This differs from the global cosmic SFR density, perhaps due to the importance of galaxy mergers. The prevalence of radio AGN emissions increases with quasar luminosity, but has little dependence on redshift. Furthermore, our new methodology and large sample size allow us to subdivide our data set to investigate the role of other parameters. Specifically, in this paper, we explore quasar colour and demonstrate that the radio excess in red quasars is due to an enhancement in AGN-related emission, since the host galaxy SF contribution to the total radio emission is independent of quasar colour. We also find evidence that this radio enhancement occurs mostly in quasars with weak or intermediate radio power.

Yue, B. -H (ORCID:0009000989352929)↗