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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

Introduction Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks. Methods We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph). Results The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing. Discussion Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git .

Chen, Xiaoyi↗
DOE OSTI2022

Comprehensive single-shot biophysical cytometry using simultaneous quantitative phase imaging and Brillouin spectroscopy

Abstract Single-cell analysis, or cytometry, is a ubiquitous tool in the biomedical sciences. Whereas most cytometers use fluorescent probes to ascertain the presence or absence of targeted molecules, biophysical parameters such as the cell density, refractive index, and viscosity are difficult to obtain. In this work, we combine two complementary techniques—quantitative phase imaging and Brillouin spectroscopy—into a label-free image cytometry platform capable of measuring more than a dozen biophysical properties of individual cells simultaneously. Using a geometric simplification linked to freshly plated cells, we can acquire the cellular diameter, volume, refractive index, mass density, non-aqueous mass, fluid volume, dry volume, the fractional water content of cells, both by mass and by volume, the Brillouin shift, Brillouin linewidth, longitudinal modulus, longitudinal viscosity, the loss modulus, and the loss tangent, all from a single acquisition, and with no assumptions of underlying parameters. Our methods are validated across three cell populations, including a control population of CHO-K1 cells, cells exposed to tubulin-disrupting nocodazole, and cells under hypoosmotic shock. Our system will unlock new avenues of research in biophysics, cell biology, and medicine.

Steelman, Zachary A.↗
DOE OSTI2021

Multi-Particle Three-Dimensional Covariance Imaging: “Coincidence” Insights into the Many-Body Fragmentation of Strong-Field Ionized D 2 O

We demonstrate the applicability of covariance analysis to three-dimensional velocity-map imaging experiments using a fast timestamping detector. Studying the photofragmentation of strong-field doubly ionized D$_2$O molecules, we show that combining high count rate measurements with covariance analysis yields the same level of information typically limited to the `gold standard' of true, low count rate coincidence experiments, when averaging over a large ensemble of photofragmentation events. This increases the effective data acquisition rate by approximately two orders of magnitude, enabling a new class of experimental studies. This is illustrated through an investigation into the dependence of three-body D$_2$O$^{2+}$ dissociation on the intensity of the ionizing laser, revealing mechanistic insights into the nuclear dynamics driven during the laser pulse. Here, the experimental methodology laid out, with its drastic reduction in acquisition time, is expected to be of great benefit to future photofragment imaging studies.

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

A non-intrusive optical (NIO) approach to characterize heliostats in utility-scale power tower plants: Methodology and in-situ validation

No reliable in-situ optical characterization tool is available that can efficiently and accurately measure various optical errors of individual heliostats in a utility-scale power-tower plant. Here, an innovative non-intrusive optical (NIO) approach is proposed to measure mirror surface slope error, mirror facet canting error, and heliostat tracking error based on reflection images using the natural target—the tower—in a heliostat field. The NIO approach adopts various techniques in photogrammetry, reflectometry, and geometrical optics to first determine the camera position and the actual tower position with respect to the heliostat. Then, Snell’s law is applied to find the surface normal at the reflection point or line of a reflection image and derive the surface slope error, mirror facet canting error, and heliostat tracking error accordingly. In addition, an in-situ validation is performed to demonstrate the feasibility of the NIO approach. Analysis with multiple sets of reflection images on one single heliostat of interest demonstrates that the NIO method can achieve a measurement uncertainty of 0.22 mrad for mirror facet slope error (root-mean-square) at the given test conditions. The sensitivity of measurement uncertainty to various parameters will be presented in a separate work. In the future, state-of-the-art unmanned aerial systems (UAS) are planned to perform the efficient image collection with a goal to complete the survey across a utility-scale field of over 10,000 heliostats within one or a few days depending on the number of UASs. The development of the NIO approach is expected to fill the critical gap for successful solar-field operation and maintenance, which is necessary for the global growth of the solar power-tower technology. The NIO approach can also be applied to any relevant industry requiring high-precision mirror surface shape characterization.

14 SOLAR ENERGY↗
DOE OSTI2021

Molecular imaging of plant-microbe interactions on the Brachypodium seed surface

Plant growth-promoting rhizobacteria (PGPR) play a crucial role in biological control and pathogenic defense on and with-in plant tissues, however the mechanism(s) by which plants associate with PGPR to elicit such beneficial effects needs further study. Here, we present high mass resolution time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of Brachypodium distachyon (Brachypodium) seeds with and without exposure to two model PGPR, i.e., Gram-negative Pseudomonas fluorescens SBW25::GFP (P.) and Gram-positive Arthrobacter chlorophenolicus A6::GFP (A.). Delayed image extraction was used to image PGPB-treated seed sections to reveal morphological changes. ToF-SIMS spectral compari-son, principal component analysis (PCA), and two-dimensional (2D) imaging show that the selected PGPR have different effects on the host seed surface, resulting in changes in chemical composition and morphology. Metabolite prod-ucts and biomarkers, such as flavonoids, phenolic com-pounds, fatty acids, and indole-3-acetic acid (IAA), were ob-served on the PGPR-treated seed surfaces. These compounds had different distributions on the Brachypodium seed surface for the two PGPR, indicating that the different bacteria elicited distinct responses from the host. Our results illustrate that ToF-SIMS is an effective tool to study plant-microbe interac-tions and to provide insightful information with submicrome-ter lateral resolution of the chemical distributions associated with morphological features, potentially offering a new way to study the mechanisms underlying beneficial roles of PGPR.

PGPR, Brachypodium distachyon, ToF-SIMS, metabolit↗
DOE OSTI2024

Looking in the axion mirror: An all-sky analysis of stimulated decay

Axion dark matter (DM) produces echo images of bright radio sources via stimulated decay. These images appear as a faint radio line centered at half the axion mass, with the line width set by the DM velocity dispersion. Due to the kinematics of the decay, the echo can be emitted in the direction nearly opposite to the incoming source of stimulating radiation, meaning that axions effectively behave as imperfect monochromatic mirrors. We present an all-sky analysis of axion DM-induced echo images using extragalactic radio point sources, Galactic supernova remnants (SNRs), and Galactic synchrotron radiation (GSR) as sources of stimulating radiation. The aggregate signal strength is not significantly affected by unknown properties of individual sources of stimulating radiation, which we sample from an empirical distribution to generate an ensemble of realizations for the all-sky signal template. We perform forecasts for CHIME, HERA, CHORD, HIRAX, and BURSTT, finding that they can run as competitive axion experiments simultaneously with other objectives, requiring no new hardware.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Nondestructive Evaluation of Stress Corrosion Cracking in a Welded Steel Plate Using Guided Ultrasonic Waves

Stress corrosion cracking (SCC) had occurred in early-generation high-level nuclear waste tanks constructed by welding carbon steel. This paper describes an ultrasonic inspection system and its fundamental ability to detect and quantify the length of SCC on thick welded steel plates. The finite element method (FEM) was applied to simulate the welding process to estimate the welding residual stress field. Growth of stress corrosion cracks is driven by crack stress intensities exceeding the subcritical cracking threshold intensity. The subject plate was experimentally inspected with ultrasonic nondestructive evaluation (NDE) techniques to characterize the extent of SCC. The NDE system uses a piezoelectric transducer to generate guided waves in the thick steel plate, and a scanning laser Doppler vibrometer (SLDV) to measure multidimensional time–space wavefield data over a user-defined scanning area in the plate surface. The measured wavefield data can show wave interactions in a localized area in the plate due to the presence of the discontinuities of the SCC. To generate an inspection image that can precisely show the crack’s location and/or the dimension, the wavefield data are further processed to generate inspection image that maps the entire sample plate so the crack can be clearly identified in the plate while its length can be readily estimated. In conclusion, the ultrasonic test results for crack length agree well with the visually estimated length and are close to that predicted by the FEM for cracks in the weld residual stress field.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

spammR: an R package designed for analysis and integration of spatial multi-omic measurements

Spatial omics is a young and evolving field and as such shows rapid development of novel technologies and analysis methods to measure transcripts, proteins, metabolites, and post-translational modifications at high spatial resolution. These advances in technology have enabled the simultaneous generation of abundance profiles for multiple different omics types and associated microscopy imaging data, as well as their analysis in a spatial context. However, most analytical tools are designed for spatial transcriptomics platforms and are challenging to use in other contexts such as mass spectrometry-based measurements or metagenomics. To this end we present spammR (spatial analysis of multi-omics measurements in R), an R package that enables end-to-end analysis with a specific focus on mass-spectrometry derived spatial omics datasets with (1) smaller sample sizes and spatial sparsity of samples, (2) considerable missingness, and (3) no a-priori knowledge about proteins or genes of interest, relying on a fully data-driven approach.

spammR↗
DOE OSTI2025

Imaging Power Losses in CdSeTe Solar Cells

Much of the research on CdSeTe photovoltaics is focused on improving the open-circuit voltage (V oc ) of the solar cell. But solar cells operate at the maximum power point (MPP) rather than at V oc . The recombination processes at MPP may be different than those at V oc , and increasing the power output at MPP is the key to advancing efficiency. Here, we introduce a camera-based PL imaging system that enables power loss analysis under operating conditions and across cm-sized areas covering multiple cells. The instrument is demonstrated with CdSeTe devices having efficiencies greater than 19%. An implied current density versus implied voltage (iJV) curve can be produced at each pixel with <20 µm resolution. We find that regions with high implied open circuit voltage are often those with low implied fill factor, showing that voltage loss analysis at open circuit is not sufficient to understand power losses under operating conditions. Measurement of JV curves as a function of irradiance can also be performed in the system, which allows series resistance-free pseudo JV (pJV) curves to be produced. Comparison of pJV to measured JV and iJV curves allows further analysis of the operational losses, pointing the way to higher efficiency.

14 SOLAR ENERGY↗
DOE OSTI2026

Quantum imaging with positronium-decay-emitted gamma rays

The use of entangled gamma rays from positronium decay for quantum-enhanced imaging of dense materials is demonstrated. Quantum ghost images, where only one of the entangled 511-keV photons interacts with the object, are obtained for tantalum samples of varying density using a 210-ps time-resolution dual detector system and a Na-22 positron source. An analysis comparing both classical and quantum imaging modalities is employed to isolate true 511-keV events from background noise. Image quality is quantitatively assessed using transmission ratios and the Michelson contrast. Quantum-correlated images are found to exhibit superior (up to approximately 1.7x, from 0.49 to 0.83 in the thickest sample measured) contrast compared to classical methods and align well with theoretical expectations. These results suggest that quantum ghost imaging with positronium-based entangled gamma rays could significantly enhance noninvasive imaging of high-density objects, with potential applications in areas such as cargo inspection and security screening.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Analysis of the Statistics and Systematics of Limb Anomaly Detections in HST/STIS Transit Images of Europa

Several recent studies derived the existence of plumes on Jupiter’s moon Europa. The only technique that provided multiple detections is the far-ultraviolet imaging observations of Europa in transit of Jupiter taken by the Space Telescope Imaging Spectrograph (STIS) on the Hubble Space Telescope (HST). In this study, we reanalyze the three HST/STIS transit images in which Sparks et al. identified limb anomalies as evidence for Europa’s plume activity. After reproducing the results of Sparks et al., we find that positive outliers are similarly present in the images as the negative outliers that were attributed to plume absorption. A physical explanation for the positive outliers is missing. We then investigate the systematic uncertainties and statistics in the images and identify two factors that are crucial when searching for anomalies around the limb. One factor is the alignment between the actual and assumed locations of Europa on the detector. A misalignment introduces distorted statistics, most strongly affecting the limb above the darker trailing hemisphere where the plumes were detected. The second factor is a discrepancy between the observation and the model used for comparison, adding uncertainty in the statistics. When accounting for these two factors, the limb minima (and maxima) are consistent with random statistical occurrence in a sample size given by the number of pixels in the analyzed limb region. The plume candidate features in the three analyzed images can be explained by purely statistical fluctuations and do not provide evidence for absorption by plumes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

braggedgemodeling

braggedgemodeling (bem) is an open-source Python package for modeling neutron Bragg-edge imaging. It computes the wavelength-dependent total neutron cross-section of a material (coherent and incoherent elastic, coherent and incoherent inelastic scattering, and absorption) from its crystal structure, and implements the March-Dollase texture model and the Jorgensen peak profile, supporting quantitative analysis of energy-resolved neutron imaging data (phase, stress/strain, and texture). Published in the Journal of Open Source Software (2018).

Lin, Jiao [Oak Ridge National Laboratory (ORNL), O↗
DOE OSTI2021

Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245

We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0 m telescope nodes located at McDonald Observatory using the Sinistro imaging instrument. In this search, we find 38 variable sources, of which 27 are newly discovered or newly classified (71%) based on comparisons with previously published catalogs, thereby increasing the number of detections in the field of view under consideration by a factor of ≈2.5. We find that the improved photometric precision per exposure due to longer exposure time for LCO images combined with the greater time sampling of LCO photometry enables us to increase the total number of detections in this field of view. Each LCO image covers a field of view of 26' × 26' and observes a region close to the Galactic plane (b = -9.°4) abundant in stars with an average stellar density of ≈8 arcmin{sup -2}. We perform aperture photometry and Fourier analysis on over 2000 stars across 1560 LCO images spanning 537 days to find 28 candidate BY Draconis variables, three candidate eclipsing binaries of type EA, and seven candidate eclipsing binaries of type EW. In assigning preliminary classifications to our detections, we demonstrate the applicability of the Gaia color–magnitude diagram as a powerful classification tool for variable-star studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Emissions and Flame Structure Assessment of Aeroengine Micromixing Injectors for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends

Abstract The present study focuses on whether adapting low emissions liquid fuel injection concepts can be applied to gaseous mixtures. The goal is to develop an injector with specific geometric characteristics that will achieve the lowest emissions. This is conducted by evaluating emissions and flame diagnostics on a set of test hardware that has been developed for combustion of pure hydrogen and hydrogen/methane mixtures. The current test hardware adapts lean direct injection concepts from aeroengine injectors to a ground-based engine based on target flows associated with a Solar Turbines Industrial Engine gas turbine. A statistical test plan was developed to assess these geometric characteristics using a three level Box Behnken design. The test plan investigates the effect of injector flow splits, air swirl, fuel swirl, pressure drop, preheat temperature, fuel composition, and the adiabatic flame temperature on the flame structure and emissions performance. A total of 16 injectors were considered for a total of 688 test points for emission and imaging data. Emissions data were reported on a mass basis in ng/J and chemical reactor network analysis were conducted to further interpret emissions behavior. Images were also captured to analyze the flame structure features of interest including reaction volume, flame length, flame spread, and flame width. With these results, a predictive model for emissions was made to conclude the most optimal injector configuration is to have the highest level of air split (more volume of air through the injector plate versus the injector) and air swirl angle for both methane and hydrogen gas mixtures. The predictive emissions level for all of these cases were below 10 ng/J.

08 HYDROGEN↗
DOE OSTI2024

Hydra: Computer Vision for Data Quality Monitoring

Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.

Roy, Ayan↗
DOE OSTI2024

Multifrequency Analysis of Favored Models for the Messier 87* Accretion Flow

Abstract The polarized images of the supermassive black hole Messier 87* (M87*) produced by the Event Horizon Telescope (EHT) provide a direct view of the near-horizon emission from a black hole accretion and jet system. The EHT theoretical analysis of the polarized M87* images compared thousands of snapshots from numerical models with a variety of spins, magnetization states, viewing inclinations, and electron energy distributions, and found a small subset consistent with the observed image. In this article, we examine two models favored by EHT analyses: a magnetically arrested disk with moderate retrograde spin and a magnetically arrested disk with high prograde spin. Both have electron distribution functions that lead to strong depolarization by cold electrons. We ray trace five snapshots from each model at 22, 43, 86, 230, 345, and 690 GHz to forecast future very long baseline interferometry (VLBI) observations and examine limitations in numerical models. We find that even at low frequencies where optical and Faraday rotation depths are large, approximately rotationally symmetric polarization persists, suggesting that shallow depths dominate the polarization signal. However, morphology and spectra suggest that the assumed thermal electron distribution is not adequate to describe emission from the jet. We find 86 GHz images show a ringlike shape determined by a combination of plasma and spacetime imprints, smaller in diameter than recent results from the Global mm-VLBI Array. We find that the photon ring becomes more apparent with increasing frequency, and is more apparent in the retrograde model, leading to large differences between models in asymmetry and polarization structure.

Astronomy & Astrophysics↗
DOE OSTI2021

NO PLIF flow visualization and time-resolved temperature distributions in laser induced breakdown plumes

NO planar laser induced fluorescence (PLIF) is used to obtain images of laser-induced breakdown plasma plumes in NO-seeded nitrogen and dry air at near atmospheric pressure. Single-shot PLIF-images show that the plume development 5–50 μs after the breakdown pulse is fairly reproducible shot-to-shot, although the plume becomes increasingly stochastic on longer timescales, 100–500 μs. The stochastic behavior of the plume is quantified using probability distributions of the loci of the plume boundary. Analysis of the single-shot images indicates that the mixing of the plume with ambient gas on sub-ms time scale is insignificant. The induced flow velocity in the plume is fairly low, up to 30 m s –1 , suggesting that laser breakdowns are ineffective for mixing enhancement in high speed flows. The ensemble-averaged PLIF images indicate the evolution of the plume from an initially elongated shape to near-spherical to toroidal shape, with a subsequent radial expansion and formation of an axial jet in the center. Temperature distributions in the plume in air are obtained from the NO PLIF images, using two rotational transitions in the NO(X, v' = 0 → A, v'' = 0) band, J'' = 6.5 and 12.5 of the Q R 12 + Q 2 branch. The results indicate that the temperature in the plume remains high, above 1000 K, for approximately 100 μs, after which it decays gradually, to below 500 K at 500 μs. The residual NO fraction in the plume is ~0.1%, indicating that repetitive laser-assisted ignition may result in significant NO-generation. Furthermore, these measured temperature and velocity distributions can be used for detailed validation of kinetic models of laser-induced breakdown and assessment of their predictive capability.

42 ENGINEERING↗