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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

VST ATLAS galaxy cluster catalogue I: cluster detection and mass calibration

Taking advantage of ∼4700 deg 2 optical coverage of the Southern sky offered by the VST ATLAS survey, we construct a new catalogue of photometrically selected galaxy groups and clusters using the orca cluster detection algorithm. The catalogue contains ∼22 000 detections with N 200 > 10 and ∼9000 with N 200 > 20. We estimate the photometric redshifts of the clusters using machine learning and find the redshift distribution of the sample to extend to z ∼ 0.7, peaking at z ∼ 0.25. We calibrate the ATLAS cluster mass-richness scaling relation using masses from the MCXC, Planck, ACT DR5, and SDSS redMaPPer cluster samples. We estimate the ATLAS sample to be > 95 per cent complete and > 85 per cent pure at z < 0.35 and in the M 200m >1 x 10 14 h -1 M ⊙ mass range. At z < 0.35, we also find the ATLAS sample to be more complete than redMaPPer, recovering a ~ 40 per cent higher fraction of Abell clusters. This higher sample completeness places the amplitude of the z < 0.35 ATLAS cluster mass function closer to the predictions of a ΛCDM model with parameters based on the Planck CMB analyses, compared to the mass functions of the other cluster samples. However, strong tensions between the observed ATLAS mass functions and models remain. We shall present a detailed cosmological analysis of the ATLAS cluster mass functions in paper II. In the future, optical counterparts to X-ray-detected eROSITA clusters can be identified using the ATLAS sample. The catalogue is also well suited for auxiliary spectroscopic target selection in 4MOST. The ATLAS cluster catalogue is publicly available at http://astro.dur.ac.uk/cosmology/vstatlas/cluster_catalogue/.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modeling the electrical double layer at solid-state electrochemical interfaces

Models of the electrical double layer (EDL) at electrode/liquid-electrolyte interfaces no longer hold for all-solid-state electrochemistry. Here we show a more general model for the EDL at a solid-state electrochemical interface based on the Poisson–Fermi–Dirac equation. By combining this model with density functional theory predictions, the interconnected electronic and ionic degrees of freedom in all-solid-state batteries, including the electronic band bending and defect concentration variation in the space-charge layer, are captured self-consistently. Along with a general mathematical solution, the EDL structure is presented in various materials that are thermodynamically stable in contact with a lithium metal anode: the solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) and the solid interlayer materials LiF, Li 2 O and Li 2 CO 3 . Here, the model further allows design of the optimum interlayer thicknesses to minimize the electrostatic barrier for lithium ion transport at relevant solid-state battery interfaces.

25 ENERGY STORAGE↗
DOE OSTI2020

Model-based Reconstruction for Single Particle Cryo-Electron Microscopy

Single particle cryo-electron microscopy is a vital tool for 3D characterization of protein structures. A typical workflow involves acquiring projection images of a collection of randomly oriented particles, picking and classifying individual particle projections by orientation, and finally using the individual particle projections to reconstruct a 3D map of the electron density profile. The reconstruction is challenging because of the low signal-to-noise ratio of the data, the unknown orientation of the particles, and the sparsity of data especially when dealing with flexible proteins where there may not be sufficient data corresponding to each class to obtain an accurate reconstruction using standard algorithms. In this paper we present a model-based image reconstruction technique that uses a regularized cost function to reconstruct the 3D density map by assuming known orientations for the particles. Our method casts the reconstruction as minimizing a cost function involving a novel forward model term that accounts for the contrast transfer function of the microscope, the orientation of the particles and the center of rotation offsets. We combine the forward model term with a regularizer that enforces desirable properties in the volume to be reconstructed. Using simulated data, we demonstrate how our method can significantly improve upon the typically used approach.

Venkatakrishnan, Singanallur↗
DOE OSTI2024

SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles

We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Limiting Behavior of Asteroid Obliquity and Spin Using a Semi-analytic Thermal Model of the YORP Effect

The Yarkovsky–O’Keefe–Radzievskii–Paddack (YORP) effect governs the spin evolution of small asteroids. The axial component of YORP, which alters the rotation rate of the asteroid, is mostly independent of its thermal inertia, while the obliquity component is very sensitive to the thermal model of the asteroid. Here, we develop a semi-analytic theory for the obliquity component of YORP. We integrate an approximate thermal model over the surface of an asteroid, and find an analytic expression for the obliquity component in terms of two YORP coefficients. This approach allows us to investigate the overall evolution of asteroid rotation state, and to generalize the results previously obtained in the case of zero thermal inertia. The proposed theory also explains how a nonzero obliquity component of YORP originates even for a symmetric asteroid, due to its finite thermal inertia. In many cases, this causes equatorial planes of asteroids to align with their orbital planes. The studied nontrivial behavior of YORP as a function of thermal model allows for a new kind of rotational equilibria, which can have important evolutionary consequences for asteroids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Verification of RESRAD-BUILD Code Version 4

This report documents the verification of the RESRAD-BUILD code, Version 4.0, which was released on December 22, 2022. Two earlier reports verifying Versions 3.0 and 3.1, respectively, were published in 2001 (Kamboj, et al. 2001) and 2003 (Tetra Tech NUS 2003). Version 4.0 of the RESRAD-BUILD code has many new features and modeling enhancements over the earlier versions, including the previously released Version 3.5. Chapter 2 of this report focuses on verifying the external dose and risk modeling for point, line, area, and volume sources, as well as for floor deposition. Besides verification, the external radiation doses calculated by RESRAD-BUILD were also benchmarked with those calculated by the MCNP code (Briemeister 1993). Section J.3 of the RESRAD-BUILD User’s Manual Vol. 1 (Yu et al. 2022) documents the results of that benchmarking effort. Chapter 3 of this report focuses on verifying the ventilation modeling, from checking the remaining source inventory, releases of radionuclides to the air, air concentrations and deposited floor concentrations over time, to the radiation dose and risk associated with inhalation, ingestion, and air submersion, with and without vacuuming. The verification efforts involve designing spreadsheets to perform calculations the same as or like those performed by the RESRAD-BUILD code and then comparing the spreadsheet results with those produced by the code. When the results agree or the differences are within acceptable range, the accuracy of model implementation in the code is verified. In addition to model implementation, the implementation of key functions and features that facilitate the modeling or the use of the code were also verified during the release testing of the code. Appendix A presents the test cases developed for these verification testing, and Appendix B presents the testing results that verify proper implementation of key functions and features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Guidelines to Achieving High Selectivity for the Hydrogenation of α,β-Unsaturated Aldehydes with Bimetallic and Dilute Alloy Catalysts: A Review

Selective hydrogenation of unsaturated aldehydes to unsaturated alcohols is a challenging class of reactions, yielding valuable intermediates for the production of pharmaceuticals, perfumes, and flavorings. On monometallic heterogeneous catalysts, the formation of the unsaturated alcohols is thermodynamically disfavored over the saturated aldehydes. Hence, new catalysts are required to achieve the desired selectivity. In this work, the literature of three major research areas in catalysis is integrated as a step toward establishing the guidelines for enhancing the selectivity: reactor studies of complex catalyst materials at operating temperature and pressure, surface science studies of crystalline surfaces in ultrahigh vacuum, and first-principles modeling using density functional theory calculations. Aggregate analysis shows that bimetallic and dilute alloy catalysts significantly enhance the selectivity to the unsaturated alcohols compared to monometallic catalysts. This comprehensive review focuses primarily on the role of different metal surfaces as well as the factors that promote the adsorption of the unsaturated aldehyde via its C=O bond, most notably by electronic modification of the surface and formation of the electrophilic sites. Furthermore, challenges, gaps, and opportunities are identified to advance the rational design of efficient catalysts for this class of reactions, including the need for systematic studies of catalytic processes, theoretical modeling of complex materials, and model studies under ambient pressure and temperature.

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

Dataset Repository for Investigating Suicide Risk Using Social and Environmental Determinants of Health

Suicide is frequently modeled as a function of genetics and environment, where the latter refers to factors other than direct biological consequences, such as air quality, financial level, social connectivity, transportation and food access, and homelessness status. According to the World Health Organization, clean air, a stable climate, adequate water, sanitation and hygiene, safe chemical use, radiation protection, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved natural environment are all prerequisites for good health. Understanding the relationships between these determinants and mental health outcomes requires standardized data that can be included in healthcare programs and health outcome models. There is a wealth of publicly available data on social and environmental factors provided by various US organizations that can benefit the design of health care systems and public health interventions, as well as improve our comprehension of factors that impact health. Such information would not only help improve the understanding of individual and community risk but also identify new risk factors that have not previously been therapeutically targeted, especially in terms of their impact on mental health. However, curating and standardizing such datasets is challenging because they are often recorded at numerous geographical and temporal resolutions and with varying spatial and temporal granularities. To address this challenge, we launched an endeavor in conjunction with the Veterans Health Administration to collect publicly available socioeconomic and environmental determinants of health statistics in the US. In this manuscript, we describe a social and environmental determinants of health (SEDH) datasets repository, data curation documentation, and a pipeline framework for data generation; This effort started in 2020, when we began constructing a scalable pipeline to automate the download, extraction, preparation, analysis, and production of datasets. These datasets have been made available to the VHA and may be shared upon agreement with collaborating organizations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Liquid-liquid phase transition of hydrogen and its critical point: Analysis from ab initio simulation and a machine-learned potential

We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. We show that an accurate NequIP model, an E(3)-equivariant neural network potential, accurately reproduces the phase transition present in PBE. Moreover, the computational efficiency of this model allows for substantially longer molecular dynamics trajectories, enabling us to perform a finite-size scaling (FSS) analysis to distinguish between a crossover and a true first-order phase transition. Here, we locate the critical point of this transition, the liquid-liquid phase transition (LLPT), at 1200-1300 K and 155-160 GPa, a temperature lower than most previous estimates and close to the melting transition.

08 HYDROGEN↗
DOE OSTI2025

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
DOE OSTI2020

Stellar Mass and Stellar Mass-to-light Ratio–Color Relations for Low Surface Brightness Galaxies

We estimate the stellar mass for a sample of low surface brightness galaxies (LSBGs) by fitting their multiband spectral energy distributions (SEDs) to the stellar population synthesis model. The derived stellar masses (log M {sub *}/M {sub ⊙}) span from 7.1 to 11.1, with a mean of log M {sub *}/M {sub ⊙} = 8.5, which is lower than that for normal galaxies. The stellar mass-to-light ratio (γ*) in each band varies little with the absolute magnitude but increases with higher M {sub *}. This trend of γ* with M {sub *} is even stronger in bluer bands. In addition, the γ* for our LSBGs slightly declines from the r band to the longer-wavelength bands. The log γ{sub ∗}{sup j} (j = g, r, i, and z) have relatively tight relations with optical colors of g − r and g − i. Compared with several representative γ*–color relations (MLCRs) from the literature, our MLCRs based on LSBG data are consistently among those literature MLCRs previously defined on diverse galaxy samples, and the existing minor differences between the MLCRs are caused by the differences in the SED model ingredients (including initial mass function, star formation history, and stellar population model), line fitting techniques, galaxy samples, and photometric zero-point, rather than the galaxy surface brightness itself, which distinguishes LSBGs from high surface brightness galaxies. Our LSBGs would be very likely to follow those representative MLCRs previously defined in diverse galaxy populations, if those main ingredients were taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Local Coordination Environment of 3d and 4d Transition Metal Ions in LiCl-KCl Eutectic Mixture

In this study, the structure and coordination environment of two 3d transition elements (Ni and Cr) is investigated in a molten chloride salt system. Electronic absorption spectroscopy was employed to elucidate their coordination environment in 3LiCl-2KCl eutectic salt, as a function of temperature. Density functional theory (DFT) modeling was used to determine the coordination environment of the transition metal species in the eutectic composition as well as the optical spectra computationally. The Ni 2+ and Cr 3+ exist in a tetrahedral and octahedral coordination environment, respectively, in eutectic salt. The spectra thus obtained were compared with the experimental data; a reasonable qualitative agreement was obtained between experimental and computational Ni 2+ and Cr 3+ spectra, and the coordination of both elements in the eutectic composition were in excellent agreement with the experimentally determined results. Computational results were also obtained for two 4d elements, Mo 3+ and Nb 3+ , with both quantum molecular dynamics (QMD) and hybrid functional optical spectra indicating octahedral coordination.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Small- and Wide-Angle X-ray Scattering Studies of Liquid–Liquid Phase Separation in Silicate Melts

Incongruent liquid-liquid phase separation is a common phenomenon in molten oxides, but there are few structural studies due to the high temperatures involved ca. >1600oC. In this work, we present a high-energy x-ray combined small/wide angle scattering (SAXS/WAXS) method that can directly probe non-equilibrium phase diagrams. The Porod exponent in the SAXS signal is extracted, which measures the roughness of the interface formed between different phases. Problematic volatilization of silica in Al 2 O 3 -, CaO-, and MgO-bearing silica-rich liquids were minimized using levitation, laser heating and rapid time-resolved measurements (lasting tens of seconds), to probe the kinetics of the phase separation process. The WAXS measurement simultaneously probes the local atomic structure of the liquid state and shows that the primary structural changes are associated with the SiO 2 network. Cation coordination numbers extracted from pair distribution functions support the model that the origin of phase separation in binary silicate systems is due to Coulombic repulsions between poorly screened cations. For CaO-SiO 2 , the liquid-liquid phase separation is found to correlate with a pause in the temperature dependent atomic disorder associated with SiO4 tetrahedra.

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

Multi-Omics integration can be used to rescue metabolic information for some of the dark region of the Pseudomonas putida proteome

In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14% of the proteome. This missing information can bias analyses since these proteins can carry out functions which impact the engineering of organisms. As a consequence of predicting protein function across all organisms, function prediction tools generally fail to use all of the types of data available for any specific organism, including protein and transcript expression information. Additionally, the release of Alphafold predictions for all Uniprot proteins provides a novel opportunity for leveraging structural information. We constructed a bespoke machine learning model to predict the function of recalcitrant proteins of unknown function in Pseudomonas putida based on these sources of data, which annotated 1079 terms to 213 proteins. Among the predicted functions supplied by the model, we found evidence for a significant overrepresentation of nitrogen metabolism and macromolecule processing proteins. These findings were corroborated by manual analyses of selected proteins which identified, among others, a functionally unannotated operon that likely encodes a branch of the shikimate pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Dynamic control of nonequilibrium metal-insulator transitions

Here, we demonstrate a first order metal-insulator phase transition in the repulsive, fully frustrated, single-band Hubbard model as a function of the coupling to a fermion bath. Time dependent manipulation of the bath coupling allows switching between metallic and insulating states both across the phase transition and within the coexistence region. We propose a simple nanoelectronic device for experimentally realizing dynamic control of the bath coupling. Analysis of the device characteristics shows that it can act as a two-terminal memristor.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Catastrophic Cooling in Superwinds. III. Nonequilibrium Photoionization

Observations of some starburst-driven galactic superwinds suggest that strong radiative cooling could play a key role in the nature of feedback and the formation of stars and molecular gas in star-forming galaxies. These catastrophically cooling superwinds are not adequately described by adiabatic fluid models, but they can be reproduced by incorporating nonequilibrium radiative cooling functions into the fluid model. In this work, we have employed the atomic and cooling module maihem implemented in the framework of the flash hydrodynamics code to simulate the formation of radiatively cooling superwinds as well as their corresponding nonequilibrium ionization (NEI) states for various outflow parameters, gas metallicities, and ambient densities. We employ the photoionization program cloudy to predict radiation- and density-bounded photoionization for these radiatively cooling superwinds, and we predict UV and optical line emission. Our nonequilibrium photoionization models built with the NEI states demonstrate the enhancement of C iv, especially in metal-rich, catastrophically cooling outflows, and O vi in metal-poor ones.

Cooling flows↗