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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sex Differences in Vagus Nerve Stimulation Effects on Rat Cardiovascular and Immune Systems

Background: Investigations into the benefits of vagus nerve stimulation (VNS) through pre-clinical and clinical research have led to promising findings for treating several disorders. Despite proven effectiveness of VNS on conditions such as epilepsy and depression, understanding of off-target effects and contributing factors such as sex differences can be beneficial to optimize therapy design. New Methods: In this article, we assessed longitudinal effects of VNS on cardiovascular and immune systems, and studied potential sex differences using a rat model of longterm VNS. Rats were implanted with cuff electrodes around the left cervical vagus nerve for VNS, and wireless physiological monitoring devices for continuous monitoring of cardiovascular system using electrocardiogram (ECG) signals. ECG morphology and heart rate variability (HRV) features were extracted to assess cardiovascular changes resulting from VNS in short-term and long-term timescales. We also assessed VNS effects on expression of inflammatory cytokines in blood during the course of the experiment. Statistical analysis was performed to compare results between Treatment and Sham groups, and between male and female animals from Treatment and Sham groups. Results: Considerable differences between male and female rats in cardiovascular effects of VNS were observed in multiple cardiovascular features. However, the effects seemed to be transient with approximately 1-h recovery after VNS. While short-term cardiovascular effects were mainly observed in male rats, females in general showed more significant long-term effects even after VNS stopped. We did not observe notable changes or sex differences in systemic cytokine levels resulting from VNS. Comparison With Existing Methods: Compared to existing methods, our study design incorporated wireless physiological monitoring and systemic blood cytokine level analysis, along with long-term VNS experiments in unanesthetized rats to study sex differences. Conclusion: The contribution of sex differences for long-term VNS off-target effects on cardiovascular and immune systems was assessed using awake behaving rats. Although VNS did not change the concentration of inflammatory biomarkers in systemic circulation for male and female rats, we observed significant differences in cardiovascular effects of VNS characterized using ECG morphology and HRV analyses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Physics-informed machine learning analysis for nanoscale grain mapping by synchrotron Laue microdiffraction

Understanding the grain morphology, orientation distribution and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a powerful technique for characterizing crystal structures and orientation mapping using focused X-rays. However, when the grain sizes are smaller than the beam size, mixed peaks in the Laue pattern from neighboring grains limit the resolution of grain morphology mapping. We propose a physics-informed machine learning (PIML) approach that combines a convolutional neural network feature extractor with a physics-informed filtering algorithm to overcome the spatial resolution limits of X-rays, achieving nanoscale resolution for grain mapping. Our PIML method successfully resolves the grain size, orientation distribution and morphology of Au nanocrystals through synchrotron microdiffraction scans, showing good agreement with electron backscatter diffraction results. This PIML-assisted synchrotron microdiffraction analysis can be generalized to other diffraction-based probes, enabling the characterization of nanosized structures with micrometre-sized probes.

X-ray crystallography↗
NASA NTRS1996

Volcanism in Eastern Africa

In 1891, the Virunga Mountains of Eastern Zaire were first acknowledged as volcanoes, and since then, the Virunga Mountain chain has demonstrated its potentially violent volcanic nature. The Virunga Mountains lie across the Eastern African Rift in an E-W direction located north of Lake Kivu. Mt. Nyamuragira and Mt. Nyiragongo present the most hazard of the eight mountains making up Virunga volcanic field, with the most recent activity during the 1970-90's. In 1977, after almost eighty years of moderate activity and periods of quiescence, Mt. Nyamuragira became highly active with lava flows that extruded from fissures on flanks circumscribing the volcano. The flows destroyed vast areas of vegetation and Zairian National Park areas, but no casualties were reported. Mt. Nyiragongo exhibited the same type volcanic activity, in association with regional tectonics that effected Mt. Nyamuragira, with variations of lava lake levels, lava fountains, and lava flows that resided in Lake Kivu. Mt. Nyiragongo, recently named a Decade volcano, presents both a direct and an indirect hazard to the inhabitants and properties located near the volcano. The Virunga volcanoes pose four major threats: volcanic eruptions, lava flows, toxic gas emission (CH4 and CO2), and earthquakes. Thus, the volcanoes of the Eastern African volcanic field emanate harm to the surrounding area by the forecast of volcanic eruptions. During the JSC Summer Fellowship program, we will acquire and collate remote sensing, photographic (Space Shuttle images), topographic and field data. In addition, maps of the extent and morphology(ies) of the features will be constructed using digital image information. The database generated will serve to create a Geographic Information System for easy access of information of the Eastem African volcanic field. The analysis of volcanism in Eastern Africa will permit a comparison for those areas from which we have field data. Results from this summer's work will permit further study and monitoring of the volcanic activity in the area. This is of concern due to the large numbers of refugees fleeing into Zaire where they are being positioned at the base of Mt. Nyiragongo. The refugees located at the base of the volcano are in direct hazard of suffocation by gas emission and destruction by lava flow. The results from this summer study will be used to secure future funding to enable continuation of this project.

Cauthen, Clay↗
NASA NTRS1999

Both necrosis and apoptosis contribute to HIV-1-induced killing of CD4 cells

BACKGROUND: Data currently available on HIV-1-induced cytopathology is unclear regarding the mechanism of cell killing. OBJECTIVE: To clarify the extent to which apoptosis or necrosis is involved in HIV-1-induced cell death in view of conflicting existing data. METHODS: T lymphoblastoid cells or peripheral blood mononuclear cells were infected by various strains of HIV-1 and the numbers of apoptotic or necrotic cells were quantified at various times after infection using video-image analysis techniques; the results were compared with the amount of fragmented DNA using a quantitative method. Measurement of mitochondrial transmembrane potential (deltapsi(m)) and intracellular calcium concentrations [Ca2+]i was performed with fluorescent probes and fluorescence concentration analysis (FCA). RESULTS: Although lymphoblastoid and monocytoid cells acutely infected by HIV-1 had increased levels of fragmented DNA, a marker of apoptotic cell death, few (<12%) had condensed chromatin and fragmented nuclei, the morphological features of apoptosis. The predominant alterations in acutely infected cells were distended endoplasmic reticulum and abnormal mitochondria; these ultrastructural changes are consistent with necrosis, although some infected cells simultaneously displayed features of both necrosis and apoptosis. Viability of cells persistently infected by HIV-1 was only minimally reduced from that of uninfected cells. This reduction was accounted for by an increased propensity of the persistently infected cells to die by apoptosis. Alterations in [Ca2+]i and deltapsi(m) occurred in both acutely and persistently infected cells. CONCLUSION: Both necrosis and apoptosis contribute to HIV-1-induced killing of CD4 cells.

Non-NASA Center↗
DOE OSTI2025

From pixels to patterns: Coupling Optical Coherence Tomography and machine learning for monitoring coastal wetland root systems

Coastal wetlands are crucial in shoreline stabilization, carbon sequestration, and storm protection. Yet, due to limitations in traditional destructive sampling techniques, the belowground biomass (live root mass) and necromass (dead and decaying roots) remain difficult to assess in coastal wetlands, limiting our understanding on coastal resilience, nutrient cycling, and soil structure. This study employs Optical Coherence Tomography (OCT) as a high-resolution imaging technique to analyze root biomass and necromass in the Terrebonne Basin, Louisiana. A Random Forest (RF) model was developed to classify root health states based on OCT-derived features, achieving an accuracy of 70% in distinguishing live from dead root segments. The results demonstrate that OCT, combined with ML, offers a promising novel approach to root analysis, providing fine-scale insights into root morphology and decay patterns that are not easily captured by conventional methods. This research lays the foundation for future integration of OCT with complementary imaging modalities such as X-ray Computed Tomography (XCT) and advanced ML algorithms to enhance classification accuracy and scalability. Future work aims to expand the dataset diversity across different wetland types and apply the methodology for large-scale, repeatable assessments of root biomass turnover and accumulation, with important implications for wetland monitoring, conservation, and restoration under changing environmental conditions.

AI/ML↗
DOE OSTI2023

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗
NASA NTRS2008

Innovative Applications of Laser Scanning and Rapid Prototype Printing to Rock Breakdown Experiments

We present the novel application of two technologies for use in rock breakdown experiments, i.e. close-range, ground-based 3D triangulation scanning and rapid prototype printing. These techniques aid analyses of form-process interactions across the range of scales relevant to breakdown (micron-m). This is achieved through (a) the creation of DEMs (which permit quantitative description and analysis of rock surface morphology and morphological change) and (b) the production of more realistically-shaped experimental blocks. We illustrate the use of these techniques, alongside appropriate data analysis routines, in experiments designed to investigate the persistence of fluvially-derived features in the face of subsequent wind abrasion and weathering. These techniques have a range of potential applications in experimental field and lab-based geomorphic studies beyond those specifically outlined here.

Bourke, Mary↗
NASA NTRS2005

Surface Clutter Removal in Airborne Radar Sounding Data from the Dry Valleys, Antarctica

We have collected roughly 1,000 line-km of airborne radar sounding data over glaciers, rock/ice glaciers, permafrost, subsurface ice bodies, ice-covered saline lakes, and glacial deposits in Taylor and Beacon Valley. These data are being analyzed in order to develop techniques for discriminating between subsurface and off-nadir echoes and for detecting and characterizing subsurface interfaces. The identification of features on Mars exhibiting morphologies consistent with ice/rock mixtures, near-surface ice bodies and near-surface liquid water, and the importance of such features to the search for water on Mars, highlights the need for appropriate terrestrial analogs and analysis techniques in order to prepare for radar sounder missions to Mars. Climatic, hydrological, and geological conditions in the Dry Valleys of Antarctica are analogous in many ways to those on Mars. A crucial first step in the data analysis process is the discrimination of echo sources in the radar data. The goal is to identify all returns from the surface of off-nadir topography in order to positively identify subsurface echoes. This process will also be critical for radar data that will be collected in areas of Mars exhibiting significant topography, so that subsurface echoes are identified unambiguously. The positive detection and characterization of subsurface (including sub-ice) water is a primary goal of NASA's Mars exploration program. Our data over the Dry Valleys provides an opportunity to implement techniques we are developing to accomplish these goals.

Holt, J. W.↗
NASA NTRS1992

SkICAT: A cataloging and analysis tool for wide field imaging surveys

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Weir, N.↗
NASA NTRS1980

Formation of complex impact craters - Evidence from Mars and other planets

An analysis of the depth vs diameter data of Arthur (1980), is given along with geomorphic data for 73 Martian craters. The implications for the formation of complex impact craters on solid planets is discussed. The analysis integrates detailed morphological observations on planetary craters with geologic data from terrestrial meteorite and explosion craters. The simple to complex transition for impact craters on Mars appears at diameters in the range of 3 to 8 km. Five features appear sequentially with increasing crater size, flat floors, central peaks and shallower depths, scalloped rims, and terraced walls. This order suggests that a shallow depth of excavation and a rebound mechanism have produced the central peaks, not centripetal collapse and deep sliding. Simple craters are relatively uniform in shape from planet to planet, but complex craters vary considerably. Both the average onset diameter for complex impact craters on Mars and the average depth of complex craters vary inversely with gravitational acceleration on four planets.

Pike, R. J.↗
NASA NTRS1992

Steep-sided domes on Venus - Characteristics, geologic setting, and eruption conditions from Magellan data

A survey of more than 95 percent of the Venus surface reveals 145 steep-sided domes which can be subdivided into a variety of morphologic forms, the most common being shaped like inverted bowls or flat-topped domes. Results of a preliminary analysis of the distribution and geologic setting of the domes are presented. The relation of the domes to analogous terrestrial features is examined, and possible models for their mode of emplacement are outlined.

Pavri, Betina↗
NASA NTRS2011

Superpixel-Augmented Endmember Detection for Hyperspectral Images

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.↗
DOE OSTI2024

Single-colony MALDI mass spectrometry imaging reveals spatial differences in metabolite abundance between natural and cultured Trichodesmium morphotypes

Trichodesmium, a globally significant N 2 -fixing marine cyanobacterium, forms extensive surface blooms in nutrient-poor ocean regions. These blooms consist of a dynamic assemblage of Trichodesmium species that form distinct colony morphotypes and are inhabited by diverse microorganisms. Trichodesmium colony morphotypes vary in ecological niche, nutrient uptake, and organic molecule release, differentially impacting ocean carbon and nitrogen biogeochemical cycles. Here, we assessed the poorly studied spatial abundance of metabolites within and between three morphologically distinct Trichodesmium colonies collected from the Red Sea. We also compared these results with two morphotypes of the cultivable Trichodesmium strain IMS101. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) coupled with liquid extraction surface analysis (LESA) tandem mass spectrometry (MS2), we identified and localized a wide range of small metabolites associated with single-colony Trichodesmium morphotypes. Our untargeted MALDI-MSI approach revealed 80 unique features (metabolites) shared between Trichodesmium morphotypes. Discrimination analysis showed spatial variations in 57 shared metabolites, accounting for 62% of the observed variation between morphotypes. The greatest variations in metabolite abundance were observed between the cultured morphotypes compared to the natural colony morphotypes, suggesting substantial differences in metabolite production between the cultivable strain IMS101 and the naturally occurring colony morphotypes that the cultivable strain is meant to represent. This study highlights the variations in metabolite abundance between natural and cultured Trichodesmium morphotypes and provides valuable insights into metabolites common to morphologically distinct Trichodesmium colonies, offering a foundation for future targeted metabolomic investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗
DOE OSTI2024

Metasurface‐Based Mueller Matrix Microscope

In conventional optical microscopes, image contrast of objects mainly results from the differences in light intensity and/or color. Muller matrix optical microscopes (MMMs), on the other hand, can provide significantly enhanced image contrast and rich information about objects by analyzing their interactions with polarized light. However, state-of-the-art MMMs are fundamentally limited by bulky and slow polarization state generators and analyzers. Here, the study demonstrates a metasurface-based MMM, i.e., Meta-MMM, which is equipped with a chip-integrated, single-shot metasurface polarization state analyzer (Meta-PSA). The Meta-MMM is featured with high-speed measurement (≈2s per Muller matrix (MM) image), superior operation stability, dual-color operation, and high measurement accuracy (measurement error 1–2%) for MM imaging. The Meta-MMM is applied to nanostructure characterization, surface morphology analysis, and discovering birefringent structures in honeybee wings. As a result, the Meta-MMMs hold the promise to revolutionize various applications from biological imaging, medical diagnosis, and material characterization to industry inspection and space exploration.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The characterization of wear-causing particles and silica sand in particular

Erodants and abradants are two types of wear-causing particles (WCP). Despite their effects on the severity and rate of wear, WCP are inadequately characterized in a surprising number of publications, especially those involving impingement erosion and three-body abrasion. That shortfall makes it difficult to correlate features of WCP with the details of worn surfaces, or to develop wear models that account for those features. It is argued that the documentation of WCP should go beyond simply reporting their composition and mean particle size. In late 1985, ASTM Committee G2 on Wear and Erosion established a task group on the characterization of WCP. At that time, image analysis was slower and less sophisticated than it is today. While that ASTM task group failed to produce a consensus standard, computerized particle characterization methods were developing in fields other than tribology, fields like geoscience, heavy sand mining, materials processing, and pharmaceuticals. A notable exception to this is ferrography, which is a widely-used diagnostic for lubricated tribosystems. In the context of dry wear, it is useful to identify which features of WCP would be beneficial to document, and to identify some techniques and scales of detail appropriate to particular tribosystems. In this paper, examples are presented for the morphological and mechanical characterization of silica sand grains, as prompted by a triboanalysis of the abrasive and erosive wear of biomass pre-processing equipment. The authors propose a minimum level of documentation for WCP, one that can enrich tribosystem analysis both in laboratory tests and field studies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Direct Recycling R&D at the ReCell Center

The expected rapid growth in electric vehicle deployment will inevitably be followed by a corresponding rise in the supply of end-of-life vehicles and their lithium-ion batteries (LIBs). The batteries may be reused, but will eventually be spent and provide a potential domestic resource that can help supply materials for future battery production. However, commercial recycling processes depend on profits from recovery of cobalt, use of which is being reduced in new cathode chemistries. The U.S. Department of Energy, therefore, established the ReCell Center in early 2019 to develop robust LIB recycling technology that would be economical even for batteries that contain no cobalt. The central feature of the technology is recovery of the cathode material with its unique crystalline cathode morphology intact in order to retain its value and functionality. Other materials are recovered as well in order to maximize revenues and minimize waste-handling costs. Analysis and modeling serve to evaluate and compare process options so that we can identify those that will be most economical while still minimizing energy use and environmental impacts. This paper provides background and describes highlights of the center’s first 2 years of operation.

Gaines, Linda (ORCID:0000000237263387)↗
NASA NTRS1983

Outer satellite atmospheres: Their extended nature and planetary interactions

Significant progress in model analysis of data for the directional features of the Io sodium cloud is reported and appears to provide some support for a satellite emission mechanism that is driven by a magnetospheric wind. A number of model calculations for the two dimensional intensity morphology of the Io sodium (region B) cloud are compared with six observations. Results of this comparison support tentative conclusions regarding the satellite emission conditions, the role of the plasma torus and the sodium atom escape flux. Progress in updating the Titan hydrogen torus model is also discussed.

Smyth, W. H.↗