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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Elucidating structural order and disorder phenomena in mullite-type Al{sub 4}B{sub 2}O{sub 9} by automated electron diffraction tomography

The crystal structure and disorder phenomena of Al{sub 4}B{sub 2}O{sub 9}, an aluminum borate from the mullite-type family, were studied using automated diffraction tomography (ADT), a recently established method for collection and analysis of electron diffraction data. Al{sub 4}B{sub 2}O{sub 9}, prepared by sol-gel approach, crystallizes in the monoclinic space group C2/m. The ab initio structure determination based on three-dimensional electron diffraction data from single ordered crystals reveals that edge-connected AlO{sub 6} octahedra expanding along the b axis constitute the backbone. The ordered structure (A) was confirmed by TEM and HAADF-STEM images. Furthermore, disordered crystals with diffuse scattering along the b axis are observed. Analysis of the modulation pattern implies a mean superstructure (AAB) with a threefold b axis, where B corresponds to an A layer shifted by ½a and ½c. Diffraction patterns simulated for the AAB sequence including additional stacking disorder are in good agreement with experimental electron diffraction patterns. - Graphical abstract: Crystal structure and disorder phenomena of B-rich Al{sub 4}B{sub 2}O{sub 9} studied by automated electron diffraction tomography (ADT) and described by diffraction simulation using DISCUS. - Highlights: • Ab-initio structure solution by electron diffraction from single nanocrystals. • Detected modulation corresponding mainly to three-fold superstructure. • Diffuse diffraction streaks caused by stacking faults in disordered crystals. • Observed streaks explained by simulated electron diffraction patterns.

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

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Electrical impedance tomography spectroscopy method for characterising particles in solid-liquid phase

Electrical impedance tomography (EIT) is one of the process tomography techniques to provide an on-line non-invasive imaging for multiphase flow measurement. With EIT measurements, the images of impedance real part, impedance imaginary part, phase angle, and magnitude can be obtained. However, most of the applications of EIT in the process industries rely on the conductivity difference between two phases in fluids to obtain the concentration profiles. It is not common to use the imaginary part or phase angle due to the dominant change in conductivity or complication in the use of other impedance information. In a solid-liquid two phases system involving nano- or submicro-particles, characterisation of particles (e.g. particle size and concentration) have to rely on the measurement of impedance phase angle or imaginary part. Particles in a solution usually have an electrical double layer associated with their surfaces and can form an induced electrical dipole moment due to the polarization of the electrical double layer under the influence of an alternating electric field. Similar to EIT, electrical impedance spectroscopy (EIS) measurement can record the electrical impedance data, including impedance real part, imaginary part and phase angle (θ), which are caused by the polarization of the electrical double layer. These impedance data are related to the particle characteristics e.g. particle size, particle and ionic concentrations in the aqueous medium, therefore EIS method provides a capability for characterising the particles in suspensions. Electrical impedance tomography based on EIS measurement or namely, electrical impedance tomography spectroscopy (EITS) could image the spatial distribution of particle characteristics. In this paper, a new method, including test set-up and data analysis, for characterisation of particles in suspensions are developed through the experimental approach. The experimental results on tomographic imaging of colloidal particles based on EIS measurement using a sensor of 8 electrodes are reported. Results have demonstrated the potential as well as revealed the challenge in the use of EIS and EITS for characterisation of particle in suspension.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Effect of Dy-substitution on the structural, vibrational, and multiferroic properties of BiFeO{sub 3} nanoparticles

Dysprosium (Dy) modified BiFeO{sub 3} [Bi{sub 1−x}Dy{sub x}FeO{sub 3} (x = 0.05, 0.10, and 0.15)] nanoparticles have been synthesized by a low temperature co-precipitation method. Rietveld analysis of X-ray diffraction data reveals a transformation from rhombohedral structure to orthorhombic structure with increase in the Dy concentration. From the transmission electron microscopy analysis, it is observed that the particle sizes of Bi{sub 1−x}Dy{sub x}FeO{sub 3} (x = 0.05, 0.10, and 0.15) nanoparticles range between 50–70, 40–50, and 30–50 nm, respectively. Raman spectra of Bi{sub 1−x}Dy{sub x}FeO{sub 3} (x = 0.05) belonging to rhombohedral (R3c) structure show 4A{sub 1} and 7E fundamental Raman modes in the range of 100–650 cm{sup −1} and two-phonon scattering modes such as 2A{sub 4} (longitudinal optical), 2E8 (transverse optical (TO)), and 2E{sub 9} (TO) in the range of 950–1270 cm{sup −1}. Suppression, broadening, and shifting of Raman modes have been observed with further increase in Dy concentration. The fundamental Raman modes of Bi{sub 1−x}Dy{sub x}FeO{sub 3} (x = 0.15) are assigned under orthorhombic (pnma) rather than rhombohedral (R3c) as the Rietveld analysis of X-ray diffraction data predicts a structural transformation for this particular composition. A complete suppression of two phonon modes has been noticed for this composition. An anomaly in the temperature dependent dielectric studies has been observed in all the samples at the vicinity of Neel temperature indicating a magnetic ordering, and an increase in magnetization with increase of Dy concentration in BiFeO{sub 3} is noticed from the room temperature magnetic studies. P–E hysteresis loop studies show a decrease of remnant polarization (P{sub r}) with the increase in Dy concentration and disappearance of hysteresis loop occurs for Bi{sub 1−x}Dy{sub x}FeO{sub 3} (x = 0.15) depicting a transformation from non-centrosymmetric (R3c) to centrosymmetric (Pnma) system.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

The microwave assisted synthesis of 1-alkyl-3-methylimidazolium bromide as potential corrosion inhibitor toward carbon steel in 1 M HCl solution saturated with carbon dioxide

Injection of corrosion inhibitor into the fluid current of oil and gas pipelines is an effective way to mitigate corrosion rate on the inner-surface parts of pipelines, especially carbon steel pipelines. In this research, two alkylimidazolium ionic liquids, 1-decyl-3-methylimidazolium bromide (IL1) and 1-dodecyl-3-methylimidazolium bromide (IL2) have been synthesized and studied as a potential corrosion inhibitor towards carbon steel in 1 M HCl solution saturated with carbon dioxide. IL1 and IL2 were synthesized using microwave assisted organic synthesis (MAOS) method. Mass Spectrometry analysis of IL1 and IL2 showed molecular mass [M-H+] peak at 223.2166 and 251.2484, respectively. The FTIR,{sup 1}H-NMR and {sup 13}C-NMR spectra confirmed that IL1 and IL2 were successfully synthesized. Corrosion inhibition activity of IL1 and IL2 were determined using weight loss method. The results showed that IL1 and IL2 have the potential as good corrosion inhibitors with corrosion inhibition efficiency of IL1 and IL2 are 96.00% at 100 ppm (343 K) and 95.60% at 50 ppm (343 K), respectively. The increase in the concentration of IL1 and IL2 tends to improve their corrosion inhibition activities. Analysis of the data obtained from the weight loss method shows that the adsorption of IL1 and IL2 on carbon steel is classified into chemisorption which obeys Langmuir’s adsorption isotherm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Dynamic compaction of nickel powder examined by x-ray phase contrast imaging

Understanding the shock response of porous, granular materials is important for many scientific applications. In this work, a propagation-based x-ray phase contrast imaging technique was used to examine the shock compaction response of Ni powder (particle size: 30 and 45 µm), encapsulated in PMMA cylinders, in situ and in real time. The propagating shock wave in the PMMA cylinder and the deformation of the Ni powder column were recorded, but the compaction wave in the Ni powder could not be observed due to insufficient penetration of x-ray photons through the sample. The overall shape of the deformed Ni column downstream of the PMMA shock looked qualitatively similar for both particle sizes: it deformed inward and then outward similar to a converging-diverging nozzle, followed by a ‘mushroom’-like structure at the impact face. A preliminary analysis of our data using shock-polar method provided insight into the observed shock and flow deflection angles at the PMMA/Ni interface, and permitted evaluation of the Ni powder EOS used in this work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

PROBING THE ISOTROPY OF COSMIC ACCELERATION TRACED BY TYPE Ia SUPERNOVAE

We present a method to test the isotropy of the magnitude–redshift relation of Type Ia Supernovae (SNe Ia) and single out the most discrepant direction (in terms of the signal-to-noise ratio) with respect to the all-sky data. Our technique accounts for possible directional variations of the corrections for SNe Ia and yields all-sky maps of the best-fit cosmological parameters with arbitrary angular resolution. To show its potential, we apply our method to the high-redshift SNe Ia from the recent Union2.1 compilation, building maps with three different angular resolutions. We use a Monte Carlo method to estimate the statistical significance with which we could reject the null hypothesis that the magnitude–redshift relation is isotropic based on the properties of the observed most discrepant directions. We find that, based on pure signal-to-noise arguments, the null hypothesis cannot be rejected at any meaningful confidence level. However, if we also consider that the strongest deviations in the Union2.1 sample closely align with the dipole temperature anisotropy of the cosmic microwave background, we find that the null hypothesis should be rejected at the 95%–99% confidence level, slightly depending on the angular resolution of the study. If this result is not due to a statistical fluke, it might either indicate that the SN data have not been cleaned from all possible systematics or even point toward new physics. We finally discuss future perspectives in the field for achieving larger and more uniform data sets that will vastly improve the quality of the results and optimally exploit our method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Temperature distributions and gradients in laser-heated plasmas relevant to magnetized liner inertial fusion

We present two-dimensional temperature measurements of magnetized and unmagnetized plasma experiments performed at Z relevant to the preheat stage in magnetized liner inertial fusion. The deuterium gas fill was doped with a trace amount of argon for spectroscopy purposes, and time-integrated spatially resolved spectra and narrow-band images were collected in both experiments. The spectrum and image data were included in two separate multiobjective analysis methods to extract the electron temperature spatial distribution T e ( r , z ) . The results indicate that the magnetic field increases T e , the axial extent of the laser heating, and the magnitude of the radial temperature gradients. Comparisons with simulations reveal that the simulations overpredict the extent of the laser heating and underpredict the temperature. Temperature gradient scale lengths extracted from the measurements also permit an assessment of the importance of nonlocal heat transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Analyzing Prospects for Quantum Advantage in Topological Data Analysis

Lloyd [Nat. Commun. , 10138 (2016)] were first to demonstrate the promise of quantum algorithms for computing Betti numbers, a way to characterize topological features of data sets. Here, we propose, analyze, and optimize an improved quantum algorithm for topological data analysis (TDA) with reduced scaling, including a method for preparing Dicke states based on inequality testing, a more efficient amplitude estimation algorithm using Kaiser windows, and an optimal implementation of eigenvalue projectors based on Chebyshev polynomials. We compile our approach to a fault-tolerant gate set and estimate constant factors in the Toffoli complexity. Our analysis reveals that superquadratic quantum speedups are only possible for this problem when targeting a multiplicative error approximation and the Betti number grows asymptotically. Further, we propose a dequantization of the quantum TDA algorithm that shows that having exponentially large dimension and Betti number are necessary, but insufficient conditions, for superpolynomial advantage. We then introduce and analyze specific problem examples which have parameters in the regime where superpolynomial advantages may be achieved, and argue that quantum circuits with tens of billions of Toffoli gates can solve seemingly classically intractable instances. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Custom High-Throughput Optical Mapping Instrument for Accelerated Stress Testing of PV Module Materials

The performance and integrity of photovoltaic (PV) modules and materials may be assessed through optical characterizations. We have developed a custom optical mapping instrument (OMI) to improve measurement throughput time, facilitate automated measurements, allow for localized specimen examination, obtain spatial information relative to commercial benchtop spectrophotometer instruments, and provide automated data analysis. Both the key components and the methods used to improve the measurements are described. The measurement precision for the OMI is benchmarked for hemispherical transmittance relative to a previous round-robin study for commercial spectrophotometers. In addition to the unique instrument developed in this study, new insights have emerged from the examination of specimens from previous experiments, including: the depletion of the UV absorber is revealed for specimens beyond a certain size after artificial ultraviolet (UV) weathering; an optical degradation by internal haze formation is confirmed following Damp Heat (85 °C/85% relative humidity) testing; the better uniformity of the wear pattern for falling sand abrasion is used to select the DIN 52348 fixture over the ASTM D968 fixture; and the greater local (in the order of millimeters) heterogeneity of surface contamination in the soiling-prone location of Dubai relative to Kuwait. The results of the UV study have already been used to improve the standardized weathering of encapsulants. The example for Damp Heat testing is given to increase awareness of a degradation believed to be ubiquitously occurring in safety and design-type qualification testing of PV modules.

14 SOLAR ENERGY↗
DOE OSTI2024

To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation

The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring manipulation of multiple primary variables and generating derived data that needs to be handled efficiently, creating challenges for applications that need to parse many large datasets. Relying on individual applications to handle all intermediate data generally leads to redundant computations across studies and unnecessary data transfers. In this paper, we investigate the performance of different approaches where applications define derived variables as quantities of interest (QoIs) and offload the computation and transfer of these QoIs to the I/O library. This significantly reduces redundancy and optimizes data movement across the distributed storage and processing infrastructure by allowing control over when and where derived variables are computed. We present a detailed analysis of the performance-storage trade-offs associated with different solutions and showcase results for our study on two large-scale datasets created from climate and combustion simulations.

Gainaru, Ana↗
DOE OSTI2016

SU-F-T-300: Impact of Electron Density Modeling of ArcCHECK Cylindricaldiode Array On 3DVH Patient Specific QA Software Tool Analysis

Purpose: 3DVH software is a patient specific quality assurance tool which estimates the 3D dose to the patient specific geometry with the help of Planned Dose Perturbation algorithm. The purpose of this study is to evaluate the impact of HU value of ArcCHECK phantom entered in Eclipse TPS on 3D dose & DVH QA analysis. Methods: Manufacturer of ArcCHECK phantom provides CT data set of phantom & recommends considering it as a homogeneous phantom with electron density (1.19 gm/cc or 282 HU) close to PMMA. We performed this study on Eclipse TPS (V13, VMS) & trueBEAM STx VMS Linac & ArcCHECK phantom (SNC). Plans were generated for 6MV photon beam, 20cm×20cm field size at isocentre & SPD (Source to phantom distance) of 86.7 cm to deliver 100cGy at isocentre. 3DVH software requires patients DICOM data generated by TPS & plan delivered on ArcCHECK phantom. Plans were generated in TPS by assigning different HU values to phantom. We analyzed gamma index & the dose profile for all plans along vertical down direction of beam’s central axis for Entry, Exit & Isocentre dose. Results: The global gamma passing rate (2% & 2mm) for manufacturer recommended HU value 282 was 96.3%. Detector entry, Isocentre & detector exit Doses were 1.9048 (1.9270), 1.00(1.0199) & 0.5078(0.527) Gy for TPS (Measured) respectively.The global gamma passing rate for electron density 1.1302 gm/cc was 98.6%. Detector entry, Isocentre & detector exit Doses were 1.8714 (1.8873), 1.00(0.9988) & 0.5211(0.516) Gy for TPS (Measured) respectively. Conclusion: Electron density value assigned by manufacturer does not hold true for every user. Proper modeling of electron density of ArcCHECK in TPS is essential to avoid systematic error in dose calculation of patient specific QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A New Genomics-Driven Taxonomy of Bacteria and Archaea: Are We There Yet?

Taxonomy is often criticized for being too conservative and too slow and having limited relevance because it has not taken into consideration the latest methods and findings. Yet the cumulative work product of its practitioners underpins contemporary microbiology and serves as a principal means of shaping and referencing knowledge. Here, using methods drawn from the field of exploratory data analysis, this minireview examines the current state of the field as it transitions from a taxonomy based on 16S rRNA gene sequences to one based on whole-genome sequences and tests the validity of some commonly held beliefs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

CERT TST November 2016 Visit Summary

The dozen plus presentations covered the span of the Center’s activities, including experimental progress, simulations of the experiments (both for calibration and validation), UQ analysis, nuclear data impacts, status of simulation codes, methods development, computational science progress, and plans for upcoming priorities. All three institutions comprising the Center (Texas A&M, University of Colorado Boulder, and Simon Fraser University) were represented. Center-supported students not only gave two of the oral presentations, but also highlighted their research in a number of excellent posters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Chemical Tool Peer Review Summary.

Chemical tracers are commonly used to characterize fracture networks and to determine the connectivity between the injection and production wells. Currently, most tracer experiments involve injecting the tracer at the injection well, manually collecting liquid samples at the wellhead of the production well, and sending the samples off for laboratory analysis. While this method provides accurate tracer concentration data, it does not provide information regarding the location of the fractures conducting the tracer between wellbores. The goal of this project is to develop chemical sensors and design a prototype tool to help understand the fracture properties of a geothermal reservoir by monitoring tracer concentrations along the depth of the well. The sensors will be able to detect certain species of the ionic tracers (mainly iodide) and pH in-situ during the tracer experiment. The proposed high-temperature (HT) tool will house the chemical sensors as well as a standard logging sensor package of pressure, temperature, and flow sensors in order to provide additional information on the state of the geothermal reservoir. The sensors and the tool will be able to survive extended deployments at temperatures up to 225 °C and high pressures to provide real-time temporal and spatial feedback of tracer concentration. Data collected from this tool will allow for the real-time identification of the fractures conducting chemical tracers between wellbores along with the pH of the reservoir fluid at various depths.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Removal of Stationary Sinusoidal Noise from Random Vibration Signals

In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metrics to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Mapped Moments to a Cartesian Grid (MMCG) Value-Added Product Report

Objective analysis (OA) is a method of mapping unstructured data to a structured grid. In the context of scanning radar data, OA is used to interpolate data in antenna coordinates (range, azimuth, and elevation) onto a regularly spaced Cartesian grid (Trapp and Doswell 2000). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Mapped Moments to a Cartesian Grid (MMCG) Value-Added Product (VAP) uses the Python ARM Radar Toolkit (Py-ART), a data model-driven interactive architecture for working with weather radar data, to map the data to a Cartesian grid (Helmus and Collis 2016). MMCG, with Py-ART built in, has the ability to take radar data in antenna coordinates and map the gates to a Cartesian grid using inverse distance weight functions such as Cressman (square) and Barnes (exponential), but also can filter the data during the interpolation. MMCG also allows arbitrary formulations for the radius of influence, which are matched to particular radar scanning strategies. This creates a complex parameter space for optimizing the retention of storm structure detail while minimizing artifacts. MMCG takes data processed with ARM’s Corrected Precipitation Radar Moments in Antenna Coordinates (CMAC) VAP and maps it to a Cartesian grid as the output product. A variety of fields that have been mapped to the Cartesian grid are then saved to plots to complement each grid file.

54 ENVIRONMENTAL SCIENCES↗