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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ~20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

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

X-ray Nanocomputed Tomography in Zernike Phase Contrast for Studying 3D Morphology of Li–O 2 Battery Electrode

In this work, we investigated the lithium peroxide (Li 2 O 2 ) and pore size distribution in lithium-O 2 battery electrodes at different states of charge using transmission X-ray microscopy coupled with Zernike phase contrast to carry out nano-Computed Tomography. We report that such technique enables, at the nanoscale, to distinguish light elements such as carbon and Li 2 O 2 in Li-O 2 battery cathode electrodes. We verified by wave-propagation simulation that this approach efficiently improves the contrast of images in comparison with the pure absorption. The Li 2 O 2 distribution and thickness, interphases, and pore network are visualized and quantified, which give a valuable insight into our cathode architecture. From this 3D analysis, we highlight modifications of the air-cathode morphology and the Li 2 O 2 spatial organization as well as their potential implication in terms of carbon surface passivation and pore-clogging. After the full recharge process, this technique can also reveal the spatial distribution of the residual Li 2 O 2 and other byproducts.

25 ENERGY STORAGE↗
DOE OSTI2020

Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. Finally, the ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Dynamical system analysis of Einstein–Skyrme model in a Kantowski–Sachs spacetime

The present work deals with anisotropic (but zero heat flux) Skyrme fluid with a constant radial profile in locally rotational Kantowski–Sachs spacetime in the background of Einstein gravity. By suitably change of variables the field equations are transformed to an autonomous system. To examine the stability of the system critical points are determined. For hyperbolic critical points the analysis of the system is done using Hartman–Grobman theorem, while center manifold theory is used to analyze non-hyperbolic critical points. Also stability at infinity is analyzed to visualize the global evolution of the Universe. As a result the 3D-phase space is identified with the Poincaré 3-sphere embedded in R{sup 4}. It is found that the parameters in the autonomous system play a crucial role for phase transition of the Universe. Finally possible bifurcation scenarios are discussed to identify the point of phase transition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

In situ/operando synchrotron x-ray studies of metal additive manufacturing

Additive manufacturing (AM) comprises a group of transformative technologies that are likely to revolutionize manufacturing. In particular, laser-based metal AM techniques can not only fabricate parts with extreme complexity, but also provide innovative means for designing and processing new metallic systems. However, there are still several technical barriers that constrain metal AM. Overcoming these barriers requires a better understanding of the physics underlying the complex and dynamic laser–metal interaction at the heart of many AM processes. Furthermore, this article briefly describes the state of the art of in situ/operando synchrotron x-ray imaging and diffraction for studying metal AM, mostly the laser powder-bed fusion process. It highlights the immediate impact of operando synchrotron studies on the advancement of AM technologies, and presents future research challenges and opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Investigation of Three-Dimensional Microstructure of Tricalcium Silicate (C 3 S) by Electron Microscopy

A serial block-face scanning electron microscopy (SBFSEM) system, composed of a scanning electron microscope (SEM) and an ultra-microtome installed within the SEM vacuum chamber, has been used to characterize the three-dimensional (3D) microstructure of tricalcium silicate (C 3 S) grains embedded in epoxy resin. A selection of C 3 S grains were segmented and rendered with 3D-image processing software, which allowed the C 3 S grains to be clearly visualized and enabled statistically quantitative analysis. The results show that about 5% of the C 3 S grains have volumes larger than 1 μm 3 and the average volume of the grains is 25 μm 3 . Pores can also be clearly seen in the biggest C 3 S grain, the volume of which is 3.6 × 10 4 μm 3 , and the mean volume and total volume of all the pores within this grain are 4.8 μm 3 and 3.0 × 10 3 μm 3 , respectively. This work provides a new approach for the characterization of the 3D spatial structure of raw C 3 S materials, and the resulting 3D structure of the raw C 3 S is important for further systematic research on the relationships between the spatial microstructure and the hydration kinetics of C 3 S and other cement minerals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_locations API file is an interactive visualization of the updated microseismic event locations. The visualization allows users to view the event locations by dragging, rotating, and zooming in. References: Chai, C., Maceira, M., Santos-Villalobos, H. J., Venkatakrishnan, S. V., Schoenball, M., and EGS Collab Team, 2020, Automatic Seismic Phase Picking Using Deep Learning for the EGS Collab Project, in PROCEEDINGS, 45th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California, 45, 1266-1276.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Integrative visualization of the molecular structure of a cellular microdomain

Abstract An integrative approach to visualization is used to create a visual snapshot of the structural biology of the polar microdomain of Caulobacter crescentus . The visualization is based on the current state of molecular and cellular knowledge of the microdomain and its cellular context. The collaborative process of researching and executing the visualization has identified aspects that are well determined and areas that require further study. The visualization is useful for dissemination, education, and outreach, and the study lays the groundwork for future 3D modeling and simulation of this well‐studied example of a cellular condensate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Demonstration of 3D Shower Reconstruction on MicroBooNE Data

Utilizing a sample of $\nu_µ$ inclusive charged current events we select four events which visually contain π 0 decays associated with a neutrino interaction vertex. This sample of charged current induced π 0 s provides us with data-driven photon showers to vet our reconstruction. The π 0 provides us with a standard candle to study how our shower reconstruction performs. The vertex of the interaction is determined by the start point of the long muon track in the event and the π 0 production point. We utilize two different methods to cluster the charge coming from these showers and reconstruct the 3D properties of the showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Development and validation of an automatic method to detect the latest contracting viable left ventricular segments to assist guide CRT therapy from gated SPECT myocardial perfusion imaging

Objectives: The purpose of this study is to use ECG-gated SPECT MPI to detect the latest contracting viable left ventricular (LV) segments to help guide the LV probe placement used in CRT therapy and to validate segment selection against the visual integration method by experts. Methods: For each patient, the resting ECG-gated SPECT MPI short-axis images were sampled in 3D to generate a polar map of the perfusion distribution used to determine LV myocardial viability, and to measure LV synchronicity using our phase analysis tool. In the visual integration method, two experts visually interpreted the LV viability and mechanical dyssynchrony from the short-axis images and polar maps of viability and phase, to determine the latest contracting viable segments using the 17-segment model. In the automatic method, the apical segments, septal segments, and segments with more than 50% scar were excluded as these are not candidates for CRT LV probe placement. Amongst the remaining viable segments, the segments, whose phase angles were within 10° of the latest phase angle (the most delayed contracting segment), were identified for potential CRT LV probe placement and ranked based on the phase angles of the segments. Both methods were tested in 36 pre-CRT patients who underwent ECG-gated SPECT MPI. The accuracy was determined as the percent agreement between the visual integration and automatic methods. The automatic method was performed by a second independent operator to evaluate the inter-operator processing reproducibility. Results: In all the 36 patients, the LV lead positions of the 1st choices recommended by the automatic and visual integration methods were in the same segments in 35 patients, which achieved an agreement rate of 97.2%. In the inter-operator reproducibility test, the LV lead positions of the 1st choices recommended by the two operators were in the same segments in 25 patients, and were in the adjacent segments in 7 patients, which achieved an overall agreement of 88.8%. Conclusions: An automatic method has been developed to detect the latest contracting viable LV segments to help guide the LV probe placement used in CRT therapy. The retrospective clinical study with 36 patients suggests that this method has high agreement against the visual integration method by experts and good inter-operator reproducibility. Consequently, this method is promising to be a clinical tool to recommend the CRT LV lead positions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Quantitative Nanoscale 3D Imaging of Intergranular Corrosion of 304 Stainless Steel Using Hard X-Ray Nanoprobe

Multi-modal imaging, which visualizes changes in the structure and chemistry of the same region of interest in materials by combining various techniques, is becoming attractive to material scientists. Here, we describe a multi-modal approach to investigate intergranular (IG) corrosion of sensitized stainless steels using synchrotron-based nanoscale X-ray imaging with sensitivity to microstructure and chemical composition. Three-dimensional tomography of 304 stainless steel samples deteriorated by IG corrosion, was carried out using X-ray fluorescence and differential phase contrast imaging. These findings were further supported with surface imaging and chemical analysis using scanning electron microscopy and energy dispersive X-ray spectroscopy. The combined quantitative structural and chemical analysis indicates that chromium segregates along grain boundaries, cracking is due to IG corrosion, and Cr-enrichment occurs on the cracked surfaces. Such quantitative 3D imaging of Cr 23 C 6 nucleation at grain boundaries and Cr enriched oxides at cracked surfaces is a powerful tool to correlate IG corrosion mechanisms at nanoscale with buried grain boundary structure and alloy composition. Such understanding of IG corrosion mechanisms is critical for both the development of predictive multiscale corrosion models, and the engineering of corrosion resistant materials.

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

TU-F-17A-04: Respiratory Phase-Resolved 3D MRI with Isotropic High Spatial Resolution: Determination of the Average Breathing Motion Pattern for Abdominal Radiotherapy Planning

Purpose: To develop a retrospective 4D-MRI technique (respiratory phase-resolved 3D-MRI) for providing an accurate assessment of tumor motion secondary to respiration. Methods: A 3D projection reconstruction (PR) sequence with self-gating (SG) was developed for 4D-MRI on a 3.0T MRI scanner. The respiration-induced shift of the imaging target was recorded by SG signals acquired in the superior-inferior direction every 15 radial projections (i.e. temporal resolution 98 ms). A total of 73000 radial projections obtained in 8-min were retrospectively sorted into 10 time-domain evenly distributed respiratory phases based on the SG information. Ten 3D image sets were then reconstructed offline. The technique was validated on a motion phantom (gadolinium-doped water-filled box, frequency of 10 and 18 cycles/min) and humans (4 healthy and 2 patients with liver tumors). Imaging protocol included 8-min 4D-MRI followed by 1-min 2D-realtime (498 ms/frame) MRI as a reference. Results: The multiphase 3D image sets with isotropic high spatial resolution (1.56 mm) permits flexible image reformatting and visualization. No intra-phase motion-induced blurring was observed. Comparing to 2D-realtime, 4D-MRI yielded similar motion range (phantom: 10.46 vs. 11.27 mm; healthy subject: 25.20 vs. 17.9 mm; patient: 11.38 vs. 9.30 mm), reasonable displacement difference averaged over the 10 phases (0.74mm; 3.63mm; 1.65mm), and excellent cross-correlation (0.98; 0.96; 0.94) between the two displacement series. Conclusion: Our preliminary study has demonstrated that the 4D-MRI technique can provide high-quality respiratory phase-resolved 3D images that feature: a) isotropic high spatial resolution, b) a fixed scan time of 8 minutes, c) an accurate estimate of average motion pattern, and d) minimal intra-phase motion artifact. This approach has the potential to become a viable alternative solution to assess the impact of breathing on tumor motion and determine appropriate treatment margins. Comparison with 4D-CT in a clinical setting is warranted to assess the value of 4D-MRI in radiotherapy planning. This work supported in part by grant 1R03CA173273-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion

Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational and clinical use. More software tools are under development for automatic analysis of other 4D imaging modalities. This research is in part supported by NIH (U54CA137788/132378) and City Seed FY13(Grant No. 93348-14 01). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

The application of cinematic rendering to CT evaluation of upper tract urothelial tumors: principles and practice

Upper tract urothelial carcinoma (UTUC) is a relatively uncommon but aggressive genitourinary malignancy for which multi-phase contrast-enhanced computed tomography (CT) plays an important role in evaluation and staging. 3D imaging with maximum intensity projection (MIP) and volume-rendered (VR) images has been described as a useful means of evaluating UTUC. In this study, we describe the technique of a novel 3D methodology known as cinematic rendering (CR) and provide clinical examples of UTUC visualized with CR. CR utilizes a complex universal lighting model in order to create photorealistic images with improved detail and depth in comparison to MIP or VR images. In the case of UTUC, CR can be used in different contrast phases to show abnormally thickened and enhancing urothelium or filling defects in the renal collecting system or ureters in the excretory phase. CR images can also be manipulated in order to generate translucent views of the upper urinary tract in order to add conspicuity to intraluminal findings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Identification of optimal landforms to reduce impacts on the landscape using LiDAR for hosting a new highway

Highlights: •New territorial indicators were designed to quantify landscape impacts. •Reduction of visual impacts caused by new roads from planning and design stages. •LIDAR and 3D realistic views were considered to locate observer's views. •Bands of less cumulative impact were obtained as guides for highway tracing. •Preventive and corrective measures for impact mitigation were located.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

An Update on Improvements to NiCE Support for RELAP-7

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is a framework that facilitates the development of applications that rely on finite-element analysis to solve a coupled, nonlinear system of partial differential equations. RELAP-7 represents an update to the venerable RELAP-5 simulator that is built upon this framework and attempts to model the balance-of-plant concerns in a full nuclear plant. This report details the continued support and integration of RELAP-7 and the NEAMS Integrated Computational Environment (NiCE). RELAP-7 is fully supported by the NiCE due to on-going work to tightly integrate NiCE with the MOOSE framework, and subsequently the applications built upon it. NiCE development throughout the first quarter of FY15 has focused on improvements, bug fixes, and feature additions to existing MOOSE-based application support. Specifically, this report will focus on improvements to the NiCE MOOSE Model Builder, the MOOSE application job launcher, and the 3D Nuclear Plant Viewer. This report also includes a comprehensive tutorial that guides RELAP-7 users through the basic NiCE workflow: from input generation and 3D Plant modeling, to massively parallel job launch and post-simulation data visualization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Structural response of 3D-printed rubber lattice structures under compressive fatigue

In this work, a new direct UV curing, polyurethane-like, highly stretchable rubber, Elastic ToughRubber 90™ (ETR 90), is demonstrated for 3D printing via photocuring with Texas Instruments DLP® optical systems. An array of test specimens, comprising a sandwich structure with a body-centered cubic lattice core, are 3D printed from ETR 90. The compressive behavior of these specimens is characterized up to 10 k and up to 100 k fatigue-loading cycles. The internal, visually obstructed, structures under loads are visualized using in situ X-ray tomography. All lattice structures remain intact and full recovery is observed, indicating the cyclic durability of the 3D-printed rubber.

36 MATERIALS SCIENCE↗