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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

hsrl (01)

High-spectral-resolution lidar (HSRL) systems collect data about clouds and aerosols. These systems provide vertical profiles of optical depth, backscatter cross-section, depolarization, and backscatter phase function. All HSRL measurements are absolutely calibrated by reference to molecular scattering, which is measured at each point in the lidar profile. Like the Raman lidar, but unlike simple backscatter lidars such as the micropulse lidar, the HSRL can measure backscatter cross-sections and optical depths without prior assumptions about the scattering properties of the atmosphere. The depolarization observations also allow robust discrimination between ice and water clouds. In addition, rigorous error estimates can be computed for all measurements. A very narrow, angular field of view reduces multiple scattering contributions. The small field of view, coupled with a narrow optical bandwidth, nearly eliminates noise due to scattered sunlight. ARM operates two HSRL systems, one at the Barrow, North Slope of Alaska (NSA) site and the other in the second ARM Mobile Facility (AMF2), which is deployed at various locations on field campaigns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

CO 3+1 network formation in ultra-high pressure carbonate liquids

Carbonate liquids are an important class of molten salts, not just for industrial applications, but also in geological processes. Carbonates are generally expected to be simple liquids, in terms of ionic interactions between the molecular carbonate anions and metal cations, and therefore relatively structureless compared to more “polymerized” silicate melts. But there is increasing evidence from phase relations, metal solubility, glass spectroscopy and simulations to suggest the emergence of carbonate “networks” at length scales longer than the component molecular anions. The stability of these emergent structures are known to be sensitive to temperature, but are also predicted to be favoured by pressure. This is important as a recent study suggests that subducted surface carbonate may melt near the Earth’s transition zone (~44 km), representing a barrier to the deep carbon cycle depending on the buoyancy and viscosity of these liquids. In this study we demonstrate a major advance in our understanding of carbonate liquids by combining simulations and high pressure measurements on a carbonate glass, (K 2 CO 3 -MgCO 3 ) to pressures in excess of 40 GPa, far higher than any previous in situ study. We show the clear formation of extended low-dimensional carbonate networks of close CO 3 2– pairs and the emergence of a “three plus one” local coordination environment, producing an unexpected increase in viscosity with pressure. Although carbonate melts may still be buoyant in the lower mantle, an increased viscosity by at least three orders of magnitude will restrict the upward mobility, possibly resulting in entrainment by the down-going slab.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermochemically-Informed Mass Transport Model for Zr in U-Zr Fuel

Recent improvements to the coupled Thermochimica-MOOSE/BISON code system have enabled efficient calculations of species transport based on direct evaluation of composition and temperature dependent chemical potentials of the species. This presents an alternative to the traditional approach to species transport in nuclear fuels, which has been to employ a diffusion formulation that combines concentration-gradient driven Fickian diffusion with a Soret term based on a heat of transport fit to experimental data. Here we describe the application of the coupled code system to the diffusion of Zr in U-Zr metallic fuel. New classes implemented in BISON to solve this problem are documented. The Zr concentration profile after 50 years of diffusion is found to be strongly dependent on the assumptions made pertaining how to mobility is calculated in multi-phase regions of the fuel element. Two assumptions are compared (simple averaging of mobilities and using the majority phase mobility), and good qualitative agreement with experimental measurements is obtained using the majority phase assumption.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Computationally efficient method for determining limiting velocities of edge dislocations in anisotropic crystals

The continuum-limit theory of dislocations in crystals predicts divergences in the elastic energy at crystal-geometry dependent limiting velocities vL, which separate subsonic, transsonic, and supersonic dislocation glide regimes and are therefore import for material strength models at high strain rates. Although it is known how to calculate those limiting velocities, there is one special case - edge dislocations with reflection symmetry, but non-vanishing elastic constants c16 or c26 - where previous methods have been notoriously slow. In this letter, we address this deficiency by deriving a computationally efficient method for determining the limiting velocities of edge dislocations with reflection symmetry which is two orders of magnitude faster than the previous method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

ABINIT: Overview and focus on selected capabilities

ABINIT is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe–Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the “temperature-dependent effective potential” approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which ABINIT relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The ABINIT DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library libpaw. ABINIT has strong links with many other software projects that are briefly mentioned.

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

Effectiveness of Deep Learning Trained on SynthCity Data for Urban Point-Cloud Classification

3D object recognition is one of the most popular areas of study in computer vision. Many of the more recent algorithms focus on indoor point clouds, classifying 3D geometric objects, and segmenting outdoor 3D scenes. One of the challenges of the classification pipeline is finding adequate and accurate training data. Hence, this article seeks to evaluate the accuracy of a synthetically generated data set called SynthCity, tested on two mobile laser-scan data sets. Varying levels of noise were applied to the training data to reflect varying levels of noise in different scanners. The chosen deep-learning algorithm was Kernel Point Convolution, a convolutional neural network that uses kernel points in Euclidean space for convolution weights.

Geology↗
DOE OSTI2022

5G Enabled Transformative Co-design and Co-simulation Framework for Grid Decarbonization and Modernization

5G is a breakthrough technology to enable a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for clean energy economy and grid modernization. The clean energy transformation not only requires innovative manufacturing, algorithm, application, and cross-domain co-simulation, but also a systematic evaluation and comprehensive support on the microelectronic and architectural computing customization to enable and maximize the high renewable penetration in the future power grid. The co-design of decarbonized grid, reliable yet efficient communication, and affordable yet ubiquitous computing will unlock the potential of almost any available tools for the undergoing clean energy transformation. 5G is also an opportunity to rethink the paradigm of infrastructure planning, as computing will be one of the core services for society alongside electricity and communication services.

5G↗
DOE OSTI2022

Connecting the Radiative Influences of Aerosol upon the Mass Flux Profiles of Shallow Cumuli across the Southeast Atlantic Ocean Basin and its Boundaries (Final Report)

The Atlantic Ocean covers approximately 25% of Earth’s surface and the atmosphere above it is home to a complex array of clouds and aerosols that have important influences on regional and global weather and climate. These influences must be accurately depicted in short range, medium range, seasonal, and climate forecast models. Conditions over the tropical Atlantic are particularly complex due to continental scale plumes of dust from the Sahara Desert and smoke from agricultural burning in Africa that drift across the Atlantic Ocean basin toward the Americas. These plumes are often found meandering in the lower atmosphere above shallow tropical clouds that form above the ocean surface, presumably mingling with these clouds on occasion due to convective mixing processes. Elevated dust and smoke particles absorb incoming sunlight and substantially warm the marine atmosphere in the layer in which they are present. This warming may alter the thermal stability of the marine atmosphere and may throttle or enhance the development of clouds, change their internal structure and the rate at which they precipitate. Alternatively, it may isolate the lower atmosphere from drier layers above enabling water vapor to accumulate near the ocean surface potentially leading to the development of deeper convection. Our study was organized around the principal concept of determining the impact of African smoke and dust plumes upon cloud development at ASI and understanding how a popular shallow convection parameterization used in models responds to the presence of this aerosol. We analyzed observations collected during the US Department of Energy (DOE) Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign using the Atmospheric Radiation Measurement Program’s Mobile Facility #1 (AMF-1), which was deployed to Ascension Island (ASI) in Southeastern Atlantic for a one-year period. Ascension Island is immediately downwind from an African source of these plumes, but far enough removed to enable the lower atmosphere to have reacted to their presence. A main goal of our study was to compute radiative heating rate profiles over Ascension Island and along the trajectory from the biomass burning regions along coastal Africa to Ascension Island. To compute the radiative heating rate due to aerosols and clouds, we employed observed profiles of temperature, humidity, and clouds from LASIC alongside aerosol optical properties from the Modern-era Retrospective analysis for Research and Applications Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM). Radiative heating was also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We were successful in this effort and the resulting publication is already being cited despite its relatively short lifetime in the literature. The second part of our study involved the process-level representation of the clouds observed over the Southeastern Atlantic in models. Our initial task, upon which the balance of this portion of the study depended, was to evaluate the representativeness of the clouds observed by AMF-1. What orographic influence did Ascension Island have on the measured cloud structure? We set out to answer this question by trying to separate observations that were clearly indicative of orographic forcing from those that were representative of open ocean. The siting of AMF-1, which was 340-m above sea-level on the slope of a steep escarpment, proved demonstrably problematic for cloud process measurements. Despite considerable effort using multiple approaches including artificial intelligence (AI), we were unable to successfully compensate for the orographic forcing present at the AMF-1 site on ASI and, hence, produce process-level summaries of the convective mass flux representative of open ocean over the Southeastern Atlantic. Even though the project has officially ended, we are making a final attempt using two new types of clustering algorithm (i.e., AI) on the recommendation of a former student, who is an expert in this area. Since we have only recently begun to test these new AI schemes, the recommendations from the second part of our project outlined below are based on our experience at the time of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

On the computational solution of vector-density based continuum dislocation dynamics models: A comparison of two plastic distortion and stress update algorithms

Continuum dislocation dynamics models of mesoscale plasticity consist of dislocation transport-reaction equations coupled with crystal mechanics equations. The coupling between these two sets of equations is such that dislocation transport gives rise to the evolution of plastic distortion (strain), while the evolution of the latter fixes the stress from which the dislocation velocity field is found via a mobility law. Earlier solutions of these equations employed a staggered solution scheme for the two sets of equations in which the plastic distortion was updated via time integration of its rate, as found from Orowan's law. In this work, we show that such a direct time integration scheme can suffer from accumulation of numerical errors. We introduce an alternative scheme based on field dislocation mechanics that ensures consistency between the plastic distortion and the dislocation content in the crystal. The new scheme is based on calculating the compatible and incompatible parts of the plastic distortion separately, and the incompatible part is calculated from the current dislocation density field. Stress field and dislocation transport calculations were implemented within a finite element based discretization of the governing equations, with the crystal mechanics part solved by a conventional Galerkin method and the dislocation transport equations by the least squares method. A simple test was first performed to show the accuracy of the two schemes for updating the plastic distortion, which shows that the solution method based on field dislocation mechanics is more accurate. This method then was used to simulate an austenitic steel crystal under uniaxial loading and multiple slip conditions. By considering dislocation interactions caused by junctions, a hardening rate similar to discrete dislocation dynamics simulation results was obtained. Finally, the simulations show that dislocations exhibit some self-organized structures as the strain is increased.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Polaron Stabilization by Cooperative Lattice Distortion and Cation Rotations in Hybrid Perovskite Materials

Solution-processed organometallic perovskites have rapidly developed into a top candidate for the active layer of photovoltaic devices. In spite of the remarkable progress associated with perovskite materials, many questions about the fundamental photophysical processes taking place in these devices, remain open. High on the list of unexplained phenomena are very modest mobilities despite low charge carrier effective masses. Moreover, experiments elucidate unique degradation of photocurrent affecting stable operation of perovskite solar cells. These puzzles suggest that, while ionic hybrid perovskite devices may have efficiencies on par with conventional Si and GaAs devices, they exhibit more complicated charge transport phenomena. We report the results from an in-depth computational study of small polaron formation, electronic structure, charge density, and reorganization energies using both periodic boundary conditions and isolated structures. Using the hybrid density functional theory, we found that volumetric strain in a CsPbI 3 cluster creates a polaron with binding energy of around 300 and 900 meV for holes and electrons, respectively. In the MAPbI 3 (MA = CH 3 NH 3 ) cluster, both volumetric strain and MA reorientation effects lead to larger binding energies at around 600 and 1300 meV for holes and electrons, respectively. Such large reorganization energies suggest appearance of small polarons in organometallic perovskite materials. Furthermore, the fact that both volumetric lattice strain and MA molecular rotational degrees of freedom can cooperate to create and stabilize polarons indicates that in order to mitigate this problem, formamidinium (FA = HC(NH 2 ) 2 ) and cesium (Cs) based crystals and alloys, are potentially better materials for solar cell and other optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A charge transfer framework that describes supramolecular interactions governing structure and properties of 2D perovskites

The elucidation of structure-to-function relationships for two-dimensional (2D) hybrid perovskites remains a primary challenge for engineering efficient perovskite-based devices. By combining insights from theory and experiment, we describe the introduction of bifunctional ligands that are capable of making strong hydrogen bonds within the organic bilayer. We find that stronger intermolecular interactions draw charge away from the perovskite layers, and we have formulated a simple and intuitive computational descriptor, the charge separation descriptor (CSD), that accurately describes the relationship between the Pb-I-Pb angle, band gap, and in-plane charge transport with the strength of these interactions. A higher CSD value correlates to less distortion of the Pb-I-Pb angle, a reduced band gap, and higher in-plane mobility of the perovskite. These improved material properties result in improved device characteristics of the resulting solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Fabrication and Characterization of a Single Hole Transistor in p-type GaAs/AlGaAs Heterostructures

Most spin qubit research to date has focused on manipulating single electron spins in quantum dots. However, hole spins are predicted to have some advantages over electron spins, such as reduced coupling to host semiconductor nuclear spins and the ability to control hole spins electrically using the large spin-orbit interaction. Building on recent advances in fabricating high-mobility 2D hole systems in GaAs/AlGaAs heterostructures at Sandia, we fabricate and characterize single hole transistors in GaAs. We demonstrate p-type double quantum dot devices with few-hole occupation, which could be used to study the physics of individual hole spins and control over coupling between hole spins, looking towards eventual applications in quantum computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

The Long, Long Road to True Single Sign On at Fermilab [Slides]

In 2012 Fermilab started down the road of single sign on for web applications. In 2018 the end of the road to true single sign on is in sight for all of our users - desktop or mobile, on premise or off. Join us as we describe the tools and techniques being used to provide this ease of access to our user community within the unique Fermilab environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Ice Nucleating Particle Sources at Oliktok Point Field Campaign Report

The Ice Nucleating Particle Sources at Oliktok Point U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) facility field campaign focused on chemically characterizing springtime aerosol sources at Oliktok Point, Alaska. This work was completed to improve our understanding of air masses influencing the site and altering ice nucleating particle (INP) concentrations measured by Dr. Jessie Creamean of the National Oceanic and Atmospheric Administration (NOAA) during her coordinated, simultaneous ARM field campaign “Exploratory Ice Nucleation Measurements at Oliktok”. Together these ARM field campaigns comprised INPOP (Ice Nucleating Particles at Oliktok Point). The field campaign took place at the Oliktok Point Third ARM Mobile Facility (AMF3) site from March 1 to May 31, 2017. A Davis rotating uniform motion (DRUM) impactor was deployed to collect particles for offline analysis for single-particle chemical characterization (aerosol mixing state). Barring a few interruptions due to power outages at the site, daily samples (24-h duration) were collected for analysis by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy (CCSEM-EDX). Unfortunately our user facility grant at the Pacific Northwest National Laboratory (PNNL) Environmental Molecular Sciences Laboratory (EMSL) was placed on hold from October 2017 to February 2018, limiting our ability to do CCSEM-EDX, as our access is also limited at the Michigan Center for Materials Characterization. Therefore, only a subset of these samples were chosen in consultation with J. Creamean and analyzed by CCSEM-EDX. We have proposed to analyze additional samples, targeting samples collected during marine air masses, as part of our DOE Atmospheric System Research (ASR) proposal “Investigating marine and terrestrial aerosol processes and cloud ice nucleation during the Alaskan Arctic melt season”. The size-resolved aerosol mixing state data produced from the ARM field campaign represent the first of such observations in the springtime at Oliktok Point. Since this AMF3 site is located within the North Slope of Alaska (NSA) oil fields near Prudhoe Bay, the site is continually influenced by combustion emissions, with natural sources also contributing to the background aerosol population.

North Slope of Alaska, Oliktok Point, aerosols, or↗
DOE OSTI2022

Even-Denominator Fractional Quantum Hall State at Filling Factor ν = 3 / 4

Fractional quantum Hall states (FQHSs) exemplify exotic phases of low-disorder two-dimensional (2D) electron systems when electron-electron interaction dominates over the thermal and kinetic energies. Particularly intriguing among the FQHSs are those observed at even-denominator Landau level filling factors, as their quasiparticles are generally believed to obey non-Abelian statistics and be of potential use in topological quantum computing. Such states, however, are very rare and fragile, and are typically observed in the excited Landau level of 2D electron systems with the lowest amount of disorder. Here we report the observation of a new and unexpected even-denominator FQHS at filling factor ν = 3/4 in a GaAs 2D hole system with an exceptionally high quality (mobility). Furthermore, our magnetotransport measurements reveal a strong minimum in the longitudinal resistance at ν = 3/4, accompanied by a developing Hall plateau centered at (h/e 2 )/(3/4). This even-denominator FQHS is very unusual as it is observed in the lowest Landau level and in a 2D hole system. While its origin is unclear, it is likely a non-Abelian state, emerging from the residual interaction between composite fermions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities

Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines highlight air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportunities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating scientific data into implementable actions. Stakeholders expressed potential ‘fit for the purpose’ use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. In conclusion, the analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗