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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Reading data stored in the state of metastable defects in silicon using band-band photoluminescence: Proof of concept and physical limits to the data storage density

The state of bistable defects in crystalline silicon such as iron-boron pairs or the boron-oxygen defect can be changed at room temperature. In this letter, we experimentally demonstrate that the chemical state of a group of defects can be changed to represent a bit of information. The state can then be read without direct contact via the intensity of the emitted band-band photoluminescence signal of the group of defects, via their impact on the carrier lifetime. The theoretical limit of the information density is then computed. The information density is shown to be low for two-dimensional storage but significant for three-dimensional data storage. Finally, we compute the maximum storage capacity as a function of the lower limit of the photoluminescence detector sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Accelerating quantum optics experiments with statistical learning

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstruct time-dependent data using a small number of detected photons, allowing for fast estimates in under a minute and providing a one-to-two order of magnitude speed-up in data acquisition time. We test our approach using real experimental data to retrieve the second order intensity correlation function, G (2) ($τ$), as a function of time delay τ between detector counts, for thermal light as well as anti-bunched light emitted by a quantum dot driven by periodic laser pulses. The proposed methodology has a wide range of applicability and has the potential to impact the scientific discovery process across a multitude of domains.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Flexible HPC Environments [Poster]

New computational paradigms require new tools and environments. A new class of data-analysis tools are available for scientists. These tools do not integrate well with traditional HPC resource management systems. Differing and often conflicting requirements exist. Some fields require validated environments including high energy physics and cosmology. By adopting cloud technologies in an HPC environment we are merging the compute-intensive and data-intensive worlds in one converged system. HPC Systems will support a Larger Set of Technologies. Scientists will be able to leverage the latest tools on HPC resources at previously unavailable scales. User-defined environments will enable rapid experimentation and adoption of emerging tools. HPC systems will support a consolidated workflow from simulation to analysis and discovery. HPC systems will have increased utility to a broader set of users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Uncertainty Quantification of Fatigue Behavior of Rough AM Surfaces and Microstructures to Enable Hydrogen Gas Turbine

Modifying fossil-fueled industrial gas turbines to utilize low or zero-carbon fuels, such as hydrogen or hydrogen-natural gas blends, is a complex endeavor. The successful implementation of this technology hinges on three key design criteria: (1) developing new fuel injectors capable of efficiently burning alternative fuels, (2) ensuring manufacturability to meet cost and time-to-market goals, and (3) achieving component durability in the demanding environment of an operating gas turbine. Additive manufacturing (AM) accelerates product development, yet concerns persist regarding the durability of parts with rough AM surfaces. A fully experimental approach to quantify the fatigue performance of rough AM microstructures is both costly and labor-intensive. To address this, ORNL and Solar Turbines Incorporated (Solar) employed a crystal plasticity finite element (CPFE) model to identify the factors influencing AM surface fatigue behavior. These CPFE findings, combined with targeted experimental data, were used to develop a computationally efficient surrogate model suitable for assessing the lifespan of gas turbine engine components.

08 HYDROGEN↗
DOE OSTI2026

Kent Island Boundary Layer Field Campaign Report

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations about the impacts of climate change and associated mitigation and adaptation measures. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) was conducted to study the interactions among the earth’s surface, the atmospheric boundary layer (ABL), aerosols, atmospheric composition, clouds, radiation, and precipitation at each experimental site, and to examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. In this activity we performed weekly soundings, alternating between day and night from Kent Island, to get low-frequency, long-term observations of ABL/lower tropospheric thermodynamic structure. However, during the CoURAGE intensive operational period (IOP), we performed high-frequency sampling (2x/day), at times coinciding with CoURAGE IOP soundings at the main site. The short-term, high-frequency sounding information that was launched at 12Z and 18Z was to complement the longer-term data set.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Investigations of Spatial and Temporal Variability of Ocean and Ice Conditions in and Near the Marginal Ice Zone. The “Marginal Ice Zone Observations and Processes Experiment” (MIZOPEX) Final Campaign Summary

Despite the significance of the marginal ice zones of the Arctic Ocean, basic parameters such as sea surface temperature (SST) and a range of sea-ice characteristics are still insufficiently understood in these areas, and especially so during the summer melt period. The field campaigns summarized here, identified collectively as the “Marginal Ice Zone Ocean and Ice Observations and Processes Experiment” (MIZOPEX), were funded by U.S. National Aeronautic and Space Administration (NASA) with the intent of helping to address these information gaps through a targeted, intensive observation field campaign that tested and exploited unique capabilities of multiple classes of unmanned aerial systems (UASs). MIZOPEX was conceived and carried out in response to NASA’s request for research efforts that would address a key area of science while also helping to advance the application of UASs in a manner useful to NASA for assessing the relative merits of different UASs. To further exercise the potential of unmanned systems and to expand the science value of the effort, the field campaign added further challenges such as air deployment of miniaturized buoys and coordinating missions involving multiple aircraft. Specific research areas that MIZOPEX data were designed to address include relationships between ocean skin temperatures and subsurface temperatures and how these evolve over time in an Arctic environment during summer; variability in sea-ice conditions such as thickness, age, and albedo within the marginal ice zone (MIZ); interactions of SST, salinity, and ice conditions during the melt cycle; and validation of satellite-derived SST and ice concentration fields provided by satellite imagery and models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗
DOE OSTI2012

Nonlinear, noniterative, single-distance phase retrieval and developmental biology

For coherent X-ray imaging, based on phase contrast through free-space Fresnel propagation, we discuss two noniterative, nonlinear approaches to the phase-retrieval problem from a single-distance intensity map of a pure-phase object. On one hand, a perturbative set-up is proposed where nonlinear corrections to the linearized transport-of-intensity situation are expanded in powers of the object-detector distance z and are evaluated in terms of the linear estimate. On the other hand, a nonperturbative projection algorithm, which is based on the (linear and local) contrast-transfer function (CTF), works with an effective phase in Fourier space. This effective phase obeys a modified CTF relation between intensity contrast at z > 0 and phase contrast at z= 0: Unphysical singularities of the local CTF model are cut off to yield 'quasiparticles' in analogy to the theory of the Fermi liquid. By identifying the positions of the zeros of the Fourier transformed intensity contrast as order parameters for the dynamical breaking of scaling symmetry we investigate the phase structure of the forward-propagation problem when interpreted as a statistical system. Results justify the quasiparticle approach for a wide range of intermediary phase variations. The latter algorithm is applied to data from biological samples recorded at the beamlines TopoTomo and ID19 at ANKA and ESRF, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging

Purpose: T{sub 2}-weighted magnetic resonance imaging (MRI) is commonly used for anatomical visualization in the pelvis area, such as the prostate, with high soft-tissue contrast. MRI can also provide functional information such as diffusion-weighted imaging (DWI) which depicts the molecular diffusion processes in biological tissues. The combination of anatomical and functional imaging techniques is widely used in oncology, e.g., for prostate cancer diagnosis and staging. However, acquisition-specific distortions as well as physiological motion lead to misalignments between T{sub 2} and DWI and consequently to a reduced diagnostic value. Image registration algorithms are commonly employed to correct for such misalignment. Methods: The authors compare the performance of five state-of-the-art nonrigid image registration techniques for accurate image fusion of DWI with T{sub 2}. Results: Image data of 20 prostate patients with cancerous lesions or cysts were acquired. All registration algorithms were validated using intensity-based as well as landmark-based techniques. Conclusions: The authors’ results show that the “fast elastic image registration” provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Hidden Chloroplast Functions Revealed Through Deep Genomic Analysis

Photosynthesis is a highly complex and orchestrated process that is tuned to plant development and the environment. This project has focused on the gene regulatory mechanisms underlying the elaboration of the photosynthetic apparatus. Particular emphasis has been placed on the regulation of genes encoded in the chloroplast compartment, where photosynthesis takes place. These genes specify both major core proteins of the photosynthetic complexes, as well as proteins that have structural or regulatory properties. The project initially identified structures and sequences in the mRNAs encoding these proteins, that allowed them to be properly regulated during plant development, as well as regulatory proteins that interact with these sequences and structures. It was shown that much of the regulation of chloroplast genes was exerted at the RNA level, rather than at the level of gene transcription. Then, insights were obtained into the enzyme functions that are required to express these RNAs correctly. A series of ribonucleases was studied, with each one having particular specificities and roles in RNA maturation and decay. In the latter part of the project, new genomics tools were employed to study gene regulation in a data-intensive and exploratory manner. Through this work, a new class of “non-coding” and mainly antisense RNAs was identified in chloroplasts, and some of these appear to in fact encode novel proteins that may have unstudied roles in photosynthesis. Overall, the project has taken a trajectory from gene-by-gene analysis to a holistic study of chloroplast coding capacity, including opening the door to identifying new chloroplast-encoded photosynthetic functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

General Analysis of Data Collected from DOE Lidar Buoy Deployments Off Virginia and New Jersey

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of offshore wind energy in the U.S. In general, each buoy is deployed for a year or more at a given location in order to capture at least a full annual cycle of weather conditions. The initial deployment for one buoy was off the coast of Virginia beginning in 2015, and the other buoy was first deployed off the coast of New Jersey beginning in 2016. Over the last two years, PNNL has had an opportunity to analyze the data collected during these first two deployments. This report describes a substantial analysis of data collected by the two lidar buoys operated off the coasts of Virginia and New Jersey. The centerpiece instrument for each buoy as deployed off Virginia and New Jersey is a lidar system, which is designed to measure the horizontal wind vector from approximately 40 m to 200 m above the sea surface with vertical resolution of 40 m. Since the initial deployments, the original lidars have been replaced with more powerful Leosphere 866 v2 systems. The analyses in this report will apply to the original Vindicator systems. In addition to the wind profiles from the lidars, the buoys collect near-surface measurements of wind speed and direction, air temperature, relative humidity, barometric pressure, and solar irradiance. Oceanographic variables measured include the two-dimensional wave spectrum, water temperature and conductivity, and ocean current vectors to a depth of 90 m. An assessment of overall data recovery and a basic analysis of the data collected was provided in a previous report This report substantially extends that analysis. The various sections describe the development and application of an inertial measurement unit (IMU) data recovery scheme for the New Jersey deployment; a climatological analysis of winds at hub height and at the surface together with thermodynamic variables measured at the surface for the full deployment periods; an analysis of oceanographic observations describe sea state; the development of a refinement for NOAA’s WaveWatch III model to allow its application to near-shore areas; a basic climatology of ocean currents observed from the buoys; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; and the development and evaluation of techniques to extract turbulence intensity and turbulence kinetic energy from the lidars. The analyses contained in this report provide a great deal of new information about offshore conditions on the U.S. East Coast. In addition, the experience gained will inform both configurations and analysis of data from future deployments of these lidar buoy systems.

17 WIND ENERGY↗
NASA NTRS2016

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗
DOE OSTI2017

Experimental studies of the effects of atomic ordering in epitaxial Ga{sub x}In{sub 1–} {sub x}P alloys on their optical properties

The properties of epitaxial Ga{sub x}In{sub 1–} {sub x}P alloys with an ordered arrangement of atoms in the crystal lattice are studied by a number of spectroscopic methods. The alloys are grown by metal-organic chemical vapor deposition onto single-crystal GaAs(100) substrates. It is shown that, under conditions of the coherent growth of an ordered Ga{sub x}In{sub 1–} {sub x}P alloy on a GaAs(100) substrate, atomic ordering results in radical modifications of the optical properties of the semiconductor compared to the properties of disordered alloys. Among these modifications are a decrease in the band gap and an increase in the luminescence intensity. From the data of dispersion analysis of the infrared dispersion spectra and from ultraviolet spectroscopy data obtained in the transmittance–reflection mode of measurements, the basic optical characteristics, specifically, the dispersion of the refractive index and the high-frequency permittivity of Ga{sub x}In{sub 1–} {sub x}P alloys with ordering are determined. All of the experimental data are in good agreement with the developed theoretical concepts.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Relative Hausdorff distance for network analysis

Similarity measures are used extensively in machine learning and data science algorithms. The newly proposed graph Relative Hausdorff (RH) distance is a lightweight yet nuanced similarity measure for quantifying the closeness of two graphs. In this work we study the effectiveness of RH distance as a tool for detecting anomalies in time-evolving graph sequences. We apply RH to cyber data with given red team events, as well to synthetically generated sequences of graphs with planted attacks. In our experiments, the performance of RH distance is at times comparable, and sometimes superior, to graph edit distance in detecting anomalous phenomena. Furthermore, our results suggest that in appropriate contexts, RH distance has advantages over more computationally intensive similarity measures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Theoretical approach to resonant inelastic x-ray scattering in iron-based superconductors at the energy scale of the superconducting gap

We develop a phenomenological theory to predict the characteristic features of the momentum-dependent scattering amplitude in resonant inelastic x-ray scattering (RIXS) at the energy scale of the superconducting gap in iron-based super-conductors. Taking into account all relevant orbital states as well as their specific content along the Fermi surface we evaluate the charge and spin dynamical structure factors for the compounds LaOFeAs and LiFeAs, based on tight-binding models which are fully consistent with recent angle-resolved photoemission spectroscopy (ARPES) data. We find a characteristic intensity redistribution between charge and spin dynamical structure factors which discriminates between sign-reversing and sign-preserving quasiparticle excitations. Consequently, our results show that RIXS spectra can distinguish between s± and s++ wave gap functions in the singlet pairing case. In addition, we find that an analogous intensity redistribution at small momenta can reveal the presence of a chiral p-wave triplet pairing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

AI-powered exploration of molecular vibrations, phonons, and spectroscopy

The vibrational dynamics of molecules and solids play a critical role in defining material properties, particularly their thermal behaviors. However, theoretical calculations of these dynamics are often computationally intensive, while experimental approaches can be technically complex and resource-demanding. Recent advancements in data-driven artificial intelligence (AI) methodologies have substantially enhanced the efficiency of these studies. This review explores the latest progress in AI-driven methods for investigating atomic vibrations, emphasizing their role in accelerating computations and enabling rapid predictions of lattice dynamics, phonon behaviors, molecular dynamics, and vibrational spectra. Key developments are discussed, including advancements in databases, structural representations, machine-learning interatomic potentials, graph neural networks, and other emerging approaches. Compared to traditional techniques, AI methods exhibit transformative potential, dramatically improving the efficiency and scope of research in materials science. The review concludes by highlighting the promising future of AI-driven innovations in the study of atomic vibrations.

Han, Bowen [Oak Ridge National Laboratory (ORNL), ↗
DOE OSTI2016

Magnetization enhancement due to incorporation of non-magnetic nitrogen content in (Co{sub 84}Zr{sub 16})N{sub x} nano-composite films

We report the magnetic, electronic, and structural properties of nano-composite (Co{sub 84}Zr{sub 16})N{sub x} or CZN films prepared by reactive co-sputter deposition method. As-deposited CZN films have shown enhancement in magnetization (M{sub s}) with incorporation of nitrogen content, which is related to the evolution of nano-composite phase. X-ray diffraction study has confirmed poly-crystalline growth of CZN films with fcc(331) and fcc(422) phases. High-resolution transmission electron microscope study reveals that CZN films are composed of ordered and crystalline ferromagnetic Co nano-clusters, which are embedded in the nano-composite matrix. Photoemission measurements show the change in the intensity near the Fermi level most likely due to defects and shift in the core-levels binding energy with nitrogen concentration. Raman spectroscopy data show an increase in the intensity of the Raman lines with nitrogen concentration upto 20%. However, the intensity is significantly lower for 30% sample. This indicates that less nitrogen or defect states are being substituted into the lattice above 20% and is consistent with the observed magnetic behavior. Our studies indicate that defects induced due to the incorporation of non-magnetic nitrogen content play a key role to enhance the magnetization.

36 MATERIALS SCIENCE↗