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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fast External Quantum Efficiency Measurements of Photovoltaic Modules

The external quantum efficiency (EQE) or associated spectral response is widely used to evaluate the performance of photovoltaics, light emitting diodes, photodetectors, photodiodes, semiconductor lasers, laser-induced refrigeration of solids etc. For photovoltaic (PV) devices, The EQE is used to determine the spectral mismatch correction that is used to convert a performance measurement from a non-ideal simulator spectrum to a standard spectrum in PV device calibrations. Moreover, EQE can provide important insight into the physics of a PV device. For instance, the EQE shape can be used to infer mechanisms limiting the performance of the device. However, EQE measurements of full-size PV modules remain a challenge in the PV community due to rare availability of reliable module QE measurement tools worldwide and the size and complexity of module architecture that comprises several cells connected in strings (series or/and parallel). Here, we use a customized nondestructive tool made of high-power light emitting diodes to perform high-throughput EQE measurements on PV modules. Circuit simulations show that the measurement system can safely be used to measure both crystalline silicon and thin film-based PV modules with series connected cells without the risk of damage through reverse bias. In addition, EQE mapping combined with electroluminescence show a strong correlation and provide a way to determine both spatial non-uniformity of the spectral response and defects/degradation effects across the module.

PV module↗
DOE OSTI2019

Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets v1.1.0

BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via REpresentational State Transfer (REST) Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model

Varadharajan, Charuleka↗
DOE OSTI2012

X-Ray Fluorescence Imaging: A New Tool for Studying Manganese Neurotoxicity

The neurotoxic effect of manganese (Mn) establishes itself in a condition known as manganism or Mn induced parkinsonism. While this condition was first diagnosed about 170 years ago, the mechanism of the neurotoxic action of Mn remains unknown. Moreover, the possibility that Mn exposure combined with other genetic and environmental factors can contribute to the development of Parkinson’s disease has been discussed in the literature and several epidemiological studies have demonstrated a correlation between Mn exposure and an elevated risk of Parkinson’s disease. Here, we introduce X-ray fluorescence imaging as a new quantitative tool for analysis of the Mn distribution in the brain with high spatial resolution. The animal model employed mimics deficits observed in affected human subjects. The obtained maps of Mn distribution in the brain demonstrate the highest Mn content in the globus pallidus, the thalamus, and the substantia nigra pars compacta. To test the hypothesis that Mn transport into/distribution within brain cells mimics that of other biologically relevant metal ions, such as iron, copper, or zinc, their distributions were compared. It was demonstrated that the Mn distribution does not follow the distributions of any of these metals in the brain. The majority of Mn in the brain was shown to occur in the mobile state, confirming the relevance of the chelation therapy currently used to treat Mn intoxication. In cells with accumulated Mn, it can cause neurotoxic action by affecting the mitochondrial respiratory chain. This can result in increased susceptibility of the neurons of the globus pallidus, thalamus, and substantia nigra pars compacta to various environmental or genetic insults. The obtained data is the first demonstration of Mn accumulation in the substantia nigra pars compacta, and thus, can represent a link between Mn exposure and its potential effects for development of Parkinson’s disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Catalog of Environmental Metrics for Hydropower

Evaluating the sustainability of new U.S. hydropower development will necessitate an approach that is comprehensive, transparent and consistent. The ORNL Environmental Metrics for Hydropower (EMH) project team addressed this need by conducting a literature review to extract and analyze a swath of environmental metrics related to hydropower projects. The assessed documents included peer-reviewed journal articles, U.S. Federal Energy Regulatory Commission licensing documents, and two sets of certification documents from the Low Impact Hydropower Institute and the International Hydropower Association. Review of 117 documents led to creation of a database of > 3000 current environmental metrics related to hydropower projects in 285 locations worldwide. Information recorded for each environmental metric was used to map the comprehensiveness of environmental measurement types gathered across primary categories, dam life cycle stages, spatial scales and locations. A majority of metrics were related to water quantity and water quality, a large number of metrics were related to biota and biodiversity, and relatively few metrics were related to the categories of geomorphology, land cover, connectivity and fragmentation, and infrastructure and design. Forty-five subcategories of environmental metrics emerged from our analysis, thereby suggesting an envelope of measurements that are important for understanding the environmental effects of new hydropower projects. The categories and subcategories of environmental metrics represented in each type of literature varied, however. The EMH database summarized in this Catalog will be used to inform stakeholder selection of appropriate environmental metrics for evaluating progress toward collective goals for new U.S. hydropower development.

13 HYDRO ENERGY↗
DOE OSTI2018

American Society of Composites, 32nd Technical Conference

This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissor angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.

42 ENGINEERING↗
DOE OSTI2018

Observations of GW170817 by DESGW and the DECam GW-EM Collaboration

On August 17, 2017 LIGO/Virgo detected a binary neutron star via gravitational waves. We observed 70 sq-degrees in the LIGO/Virgo spatial localization with the DECam on the 4m Blanco telescope covering 80% of the nal map. Our group independently discovered an optical counterpart in NGC 4993. We searched our entire imaged region: the object in NGC 4993 was the only viable candidate. Our observations of NGC4993 show complicated morphology but simple star formation history. Our x-ray and radio observations indicate an o-axis jet as afterglow. Our high-cadence optical and infrared spectra show a source that must be described by at least two components, one of which is dominated by the r-process nucleosynthesis elements characteristic of a kilonova. Our modeling of the light curve demonstrates such a model in which 0.05 M of material is ejected from the system. Finally, we discuss the first standard siren measurement of H0.

Annis, James↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Northern Saguache County, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data around Pinkerton Hot Springs, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Northwest Delta, Colorado

This map shows areas of anomalous surface temperature in northern Saguache Counties identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗
DOE OSTI2018

Enabling high resolution strain mapping in zirconium alloys

Highlights: • Optimisation of speckle patterns suitable for high resolution digital image correlation in a zirconium alloy • Evidence of distinct strain patterning at the macro and micro scale • Analysis of strain heterogeneity in a neighbouring low and high strain band • Paved the way for future studies on strain localization in zirconium alloys subjected to hydriding and irradiation damage - Abstract: High Resolution Digital Image Correlation (HRDIC) has been established recently as a novel displacement mapping technique during mechanical loading experiments to quantify strain localisation down to the level of individual slip traces. This is achieved by the creation of a nano-scale gold pattern naturally formed during remodelling of a thin gold layer that was sputtered onto the region of interest. To date, the gold remodelling is carried out in a water vapourisation environment, which excludes the technique to be applied to materials that readily form noticeable oxide layers in such environments. The current paper describes a recently developed gold remodelling technique using a styrene-argon environment at substantially lower temperatures than the water-vapour based technique. The material used in the present work is a zirconium alloy where we first demonstrate the problem of oxide formation during remodelling in water vapour and the benefit of the modified remodelling procedure. The error associated with the spatial drift was assessed for different interrogation window sizes followed by detailed analysis of the subsequent strain maps produced using the styrene remodelled patterns after tensile deformation to nominal applied strains of ~3.5% and ~7.0%. The level of detail captured demonstrate the suitability of styrene-argon-based remodelling for materials like Zr alloys with the strain maps showing clear strain patterning on both a transgranular and single grain scale with the possibility of quantifying strain across a single slip trace.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Off-axis electron holography of bacterial cells and magnetic nanoparticles in liquid

Here, the mapping of electrostatic potentials and magnetic fields in liquids using electron holography has been considered to be unrealistic. Here, we show that hydrated cells of Magnetospirillum magneticum strain AMB-1 and assemblies of magnetic nanoparticles can be studied using off-axis electron holography in a fluid cell specimen holder within the transmission electron microscope. Considering that the holographic object and reference wave both pass through liquid, the recorded electron holograms show sufficient interference fringe contrast to permit reconstruction of the phase shift of the electron wave and mapping of the magnetic induction from bacterial magnetite nanocrystals. We assess the challenges of performing in situ magnetization reversal experiments using a fluid cell specimen holder, discuss approaches for improving spatial resolution and specimen stability, and outline future perspectives for studying scientific phenomena, ranging from interparticle interactions in liquids and electrical double layers at solid–liquid interfaces to biomineralization and the mapping of electrostatic potentials associated with protein aggregation and folding.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Determination of the Spatial Distribution of Indigenous Lipid Biomarkers in an Immature Jurassic Sediment Using Time-of-Flight–Secondary Ion Mass Spectrometry

The ability to detect and map lipids, including potential lipid biomarkers, within a sedimentary matrix using mass spectrometry (MS) imaging may be critical to determine whether potential lipids detected in samples returned from Mars are indigenous to Mars or are contaminants. Here, we use gas chromatography–mass spectrometry (GC-MS) and time-of-flight–secondary ion mass spectrometry (ToF-SIMS) datasets collected from an organic-rich, thermally immature Jurassic geologic sample to constrain MS imaging analysis of indigenous lipid biomarkers in geologic samples. GC-MS data show that the extractable fractions are dominated by C 27 –C 30 steranes and sterenes as well as isorenieratene derivatives. ToF-SIMS spectra from organic matter-rich laminae contain a strong, spatially restricted signal for ions m/z 370.3, m/z 372.3, and m/z 386.3, which we assign to C 27 sterenes, cholestane (C 27 ), and 4- or 24-methyl steranes (C 28 ), respectively, as well as characteristic fragment ions of isorenieratene derivatives, including m/z 133.1, m/z 171.1, and m/z 237.1. We observed individual steroid spatial heterogeneity at the scale of 10's to 100's of microns. The fine-scale heterogeneity observed implies that indigenous lipid biomarkers concentrated within specific regions may be detectable via ToF-SIMS in samples with even low amounts of organic carbon, including in samples returned from Mars.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗
DOE OSTI2017

Unraveling submicron-scale mechanical heterogeneity by three-dimensional X-ray microdiffraction

Shear banding is a ubiquitous phenomenon of severe plastic deformation, and damage accumulation in shear bands often results in the catastrophic failure of a material. Despite extensive studies, the microscopic mechanisms of strain localization and deformation damage in shear bands remain elusive due to their spatial-temporal complexities embedded in bulk materials. Here we conducted synchrotron-based X-ray microdiffraction (μXRD) experiments to map out the 3D lattice strain field with a submicron resolution around fatigue shear bands in a stainless steel. Both in situ and postmortem μXRD results revealed large lattice strain gradients at intersections of the primary and secondary shear bands. Such strain gradients resulted in severe mechanical heterogeneities across the fatigue shear bands, leading to reduced fatigue limits in the high-cycle regime. The ability to spatially quantify the localized strain gradients with submicron resolution through μXRD opens opportunities for understanding the microscopic mechanisms of damage and failure in bulk materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A reference tissue atlas for the human kidney

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm{sup 3}, FOV 22 × 22 × 4.2 cm{sup 3}, and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm{sup 3}, and broader coverage 22 × 22 × 19 cm{sup 3}. Temporal resolution was 5 s for both protocols. Time-resolved images and blood–brain barrier permeability maps were qualitatively evaluated by two radiologists. Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

60 APPLIED LIFE SCIENCES↗