Search NASA⌕ Search

SEARCH · Search NASA

Results for “atomic data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Hubble Space Telescope: UV, Visible, and Near-Infrared Pursuits

The Hubble Space Telescope continues to push the limits on world-class astrophysics. Cameras including the Advanced Camera for Surveys and the new panchromatic Wide Field Camera 3 which was installed nu last year's successful servicing mission S2N4,o{fer imaging from near-infrared through ultraviolet wavelengths. Spectroscopic studies of sources from black holes to exoplanet atmospheres are making great advances through the versatile use of STIS, the Space Telescope Imaging Spectrograph. The new Cosmic Origins Spectrograph, also installed last year, is the most sensitive UV spectrograph to fly io space and is uniquely suited to address particular scientific questions on galaxy halos, the intergalactic medium, and the cosmic web. With these outstanding capabilities on HST come complex needs for laboratory astrophysics support including atomic and line identification data. I will provide an overview of Hubble's current capabilities and the scientific programs and goals that particularly benefit from the studies of laboratory astrophysics.

Wiseman, Jennifer↗
NASA NTRS2016

Distance to the IBEX Ribbon Source Inferred From Parallax

Maps of energetic neutral atom (ENA) fluxes obtained from observations made by the Interstellar Boundary Explorer (IBEX) revealed a bright structure extending over the sky, subsequently dubbed the IBEX ribbon. The ribbon had not been expected from the existing models and theories prior to IBEX, and a number of mechanisms have since been proposed to explain the observations. In these mechanisms, the observed ENAs emerge from source plasmas located at different distances from the Sun. Since each part of the sky is observed by ibex TWICE DURING THE YEAR FROM OPPOSTIE SIDE OF THE Sun, the apparent position of the ribbon as observed in the sky is shifted due to parallax. To determine the ribbons parallax, we found the precise location of the maximum signal of the ribbon observed in each orbital arc. The apparent positions obtained were subsequently corrected for the Compton-Getting effect, gravitational deflection, and radiation pressure. Finally, we selected a part of the ribbon where its position is similar in the different IBEX ENERGY PASSBANDS. We compared the apparent positions obtained from the viewing locations on the opposite sides of the Sun, and found that they are shifted by a parallax angle of 0 41 0 15, which corresponds to a distance of AU. This finding supports models of the ribbon with the source located just outside the heliopause.

ISM: atoms↗
DOE OSTI2022

POSTER: Automatic Differentiation of Parallel Loops with Formal Methods

The accompanying poster to this short paper presents a combination of reverse mode AD and formal methods to enable efficient differentiation of (or backpropagation through) shared-memory parallel code. Compared to the state of the art, our approach can more often avoid the need for atomic updates or private data copies during the parallel derivative computation, even in the presence of unstructured or data-dependent data access patterns. This is achieved by gathering information about the memory access patterns from the input program, which is assumed to be correctly parallelized. This information is then used to build a model of assertions in a theorem prover, which can be used to check the safety of shared memory accesses during the parallel derivative computation

Automatic Differentiation↗
DOE OSTI2025

Laboratory Measurements of n >= 3 K-shell Transition Energies of Sulfur Ions from F-like S viii to Li-like S xiv

Inner-shell transitions are ubiquitous in nonequilibrium collisionally ionized plasmas, such as supernova remnants, and in photoionized plasmas, such as outflows from active galactic nuclei and X-ray binaries. Inner-shell X-ray emission can help determine key parameters of these systems, such as ionization time, τ, and ionization parameter, ξ. Despite their importance, only theoretical inner-shell transition energies are available for many ions. To provide experimental benchmarks, we have measured the dominant n → 1 K-shell transitions of sulfur ions where n ≥ 3 from Li-like S xiv to F-like S viii using LLNL’s SuperEBIT electron beam ion trap and the NASA/GSFC EBIT Calorimeter Spectrometer (ECS). We identify over 30 spectral features and measure their energies with uncertainties in the ∼0.1–1 eV range. We compare these results to Flexible Atomic Code (FAC) and multireference Møller–Plesset (MR-MP) calculations and find differences between theory and experiment of ∼1 eV for FAC and <0.5 eV for most MR-MP calculations. We also compare these results to two widely used atomic databases, AtomDB and CHIANTI, and find discrepancies as high as 7 eV. Furthermore, many transitions are missing from these databases despite being prominent in our data.

Atomic data benchmarking↗
DOE OSTI2025

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗
NASA NTRS1994

The heat capacity of titanium disilicide

The heat capacity of TiSi2 has been measured in the temperature range 105-500 K. The heat capacity of TiSi2 varies monotonically between temperatures of 100 and 500 K with a reference value of 22.0 +/- 0.2 J/g atom K at 298.15 K. Based upon our heat capacity data, the standard molar entropy of TiSi2 at 298.15 K estimated to be 22.2 +/- 0.8 J/g atom K. Our data support estimates of the higher temperature heat capacity of TiSi2 based upon previously measured heat capacities of different, but similar, substances. A number of TiSi2 samples were prepared by rapidly quenching (greater than 10(exp 5) K/s) from the melt. The structure and the measured heat capacity of these samples were similar to those of well annealed samples, underscoring the thermal stability of this material.

Sylla, W. K.↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Differential cross sections for scattering of 0.5-, 1.5-, and 5.0 keV oxygen atoms by He, N2, and O2

This paper reports measurements of absolute scattering cross sections, differential in angle, for collisions of ground-state oxygen atoms with He, N2, and O2. Data are presented for scattering of 0.5-, 1.5-, and 5.0-keV oxygen-atom projectiles in the range of laboratory frame angles between 0.06 and 5 deg. These measurements provide information relevant to calculations of the aeronomic consequences of O(+) precipitation in the earth's upper atmosphere.

Schafer, D. A.↗
NASA NTRS1972

Atomization, drop size, and penetration for cross-stream water injection at high-altitude reentry conditions with application to the RAM C-1 and C-3 flights

Atomization, drop size, and penetration data are presented for cross stream water injection at conditions simulating high altitude reentry (low Weber number, high static temperature, high Knudsen number, and low static pressure). These results are applied to the RAM C-1 and C-3 flights. Two primary breakup modes are considered, vapor pressure or flashing and aerodynamic atomization. Results are given for breakup boundaries and mean drop size for each of these atomization mechanisms. Both standard and flight orifice geometries are investigated. The data were obtained in both a static environment and in conventional aerodynamic facilities at Mach numbers of 4.5 and 8. The high temperature aspects of reentry were simulated in a Mach 5.5 cyanogen-oxygen tunnel with total temperature of 4500 K.

Gooderum, P. B.↗
DOE OSTI2021

The Rise of Neural Networks for Materials and Chemical Dynamics

Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1978

Measuring the velocity of individual atoms in real time

It is proposed that the thermal velocity of a single atom could be measured in real time using a laser time-of-flight velocimeter (LTV) operating on the principle of laser resonance fluorescence. Theoretical data are presented for several atomic species that have resonances within the range of available dye-laser systems. It is shown that measurements in the subsonic region are certainly feasible. The atoms could be either in vacuum or in a buffer gas, e.g., at atmospheric pressure. Measurements in the transonic and supersonic region also appear possible. One potential application is the measurement of flow speeds in wind tunnels, perhaps as high as Mach 45.

She, C. Y.↗
NASA NTRS2002

Demonstrating Acquisition of Real-Time Thermal Data over Fires Utilizing UAVs

NASA-Ames Research Center, in collaboration with General Atomics Aeronautical Systems, Inc. has been developing real-time data acquisition and information delivery systems employing uninhabited aerial vehicle (UAV) technology for disaster mitigation and assessment demonstrations. Working in conjunction with the US Forest Service, a disaster community agency responsible for wildfire management and mitigation, we developed a large-scale wildfire demonstration called the First Response Experiment (FIRE). During that experiment in late summer 2001, the participants demonstrated the melding of innovative technologies such as UAV platforms, real-time data processing, and data telemetry for quick analysis of a disaster event. The General Atomics ALTUS UAV, the Airborne Infrared Disaster Assessment System (AIRDAS) and Over-The-Horizon (OTH) satellite data telemetry equipment were employed over a controlled burn to test the feasibility of a disaster monitoring and mitigation platform for hazardous duty. The ALTUS UAV was employed to demonstrate the long duration, altitude, and payload capability of unmanned platforms for acquiring disaster related data. The ALTUS has an operational altitude to 45,000 feet (13,700 in), with a flight duration of twenty-four hours and a payload capacity of over 300 lbs. (148.5 kg). This allows the platform to operate under the conditions that would be necessary for monitoring and mitigating disaster events throughout the Unites States. The four channel AIRDAS data (calibrated thermal infrared digital imagery of the fire event) was sent from the ALTUS UAV via a satellite communications system (NERA transponder and INMARSAT satellite) to a data archive server and an image processing work station at NASA-Ames Research Center, 400 miles away.

Wegener, Steven S.↗
DOE OSTI2022

AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy

Over the past several decades, electron and scanning probe microscopes have become critical components of condensed matter physics, materials science and chemistry research. At the same time, the infrastructure for establishing a connection between microscopy observations and materials behaviour over a broader parameter space is lacking. In this work, we introduce AtomAI, an open-source software package bridging instrument-specific Python libraries, deep learning and simulation tools into a single ecosystem. AtomAI allows direct applications of deep neural networks for atomic and mesoscopic image segmentation converting image and spectroscopy data into class-based local descriptors for downstream tasks such as statistical and graph analysis. For atomically resolved imaging data, the output is types and positions of atomic species, with an option for subsequent refinement. AtomAI further allows the implementation of a broad range of image and spectrum analysis functions, including invariant variational autoencoders for disentangling structural factors of variation and im2spec type of encoder–decoder models for mapping structure–property relationships. Finally, our framework allows seamless connection to the first principles modelling with a Python interface on the inferred atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cluster Expansion Analysis of Atomic Order in Li-Ion Battery Cathode Material LiCo y Ni 1-y O 2

A modified cluster-expansion treatment was developed recently to analyze atomic order in LiCo y Ni 1-y O 2 , a model cathode material for Li-ion batteries. In this treatment, referred to as a “spin-atom” cluster expansion, the occupant of a lattice site is identified by its spin state as well as its atomic species. Further, Effective Cluster Interaction (ECI) coefficients are derived from a large training data set (i.e., the set of atomic arrangements for which DFT calculations are performed) which is filtered by an anomaly detection algorithm to eliminate poorly converged DFT calculations. The cluster expansion incorporates Li-Ni (LN) exchange as well as intralayer Co-Ni (CN) exchange. Monte Carlo simulations based on the cluster expansion were applied to the Ni-rich part of the phase diagram. The simulations predict a miscibility gap between y = 0.05 and y = 0.65.

25 ENERGY STORAGE↗
DOE OSTI2024

Multi-kernel Edge Attention Graph Autoencoder

MEAGraph (Multi-kernel Edge Attention Graph Autoencoder) is a graph-based autoencoder model designed for unsupervised data mining for datasets used in machine learning potentials. It provides accurate clustering for atomic environment identification, unsupervised and unlabeled data pruning for dataset construction.

Sun, Hong↗
NASA NTRS1991

The effect of atomic oxygen on polysiloxane-polyimide for spacecraft applications in low Earth orbit

Polysiloxane-polyimide films are of interest as a replacement for polyimide Kapton in the Space Station Freedom solar array blanket. The blanket provides the structural support for the solar cells as well as providing transport of heat away from the back of the cells. Polyimide Kapton would be an ideal material to use; however, its high rate of degradation due to attack by atomic oxygen in low Earth orbit, at the altitudes Space Station Freedom will fly, is of such magnitude that if left unprotected, the blanket will undergo structural failure in much less than the desired 15 year operating life. Polysiloxane-polyimide is of interest as a replacement material because it should from its own protective silicon dioxide coating upon exposure to atomic oxygen. Mass, optical, and photomicrographic data obtained in the evaluation of the durability of polysiloxane-polyimide to an atomic oxygen environment are presented.

Rutledge, Sharon K.↗
DOE OSTI2020

Reconstruction of the interatomic forces from dynamic scanning transmission electron microscopy data

We explore the possibility for reconstruction of the generative physical models describing interactions between atomic units in solids from observational electron microscopy data. In this work, scanning transmission electron microscopy (STEM) is used to observe the dynamic motion of Si atoms at the edge of monolayer graphene under continuous electron beam illumination. The resulting time-lapsed STEM images represent the snapshots of observed chemical states of the system. We use two approaches: potential of mean force calculation using a radial distribution function and a direct fitting of the graphene–Si interatomic pairwise potentials with force matching, to reconstruct the force fields in the materials. These studies lay the foundation for quantitative analysis of materials energetics from STEM data through the sampling of the metastable states in the chemical space of the system.

42 ENGINEERING↗