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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 145 records · Page 8

Nanoscale measurements of proton tracks using fluorescent nuclear track detectors

Purpose: The authors describe a method in which fluorescence nuclear track detectors (FNTDs), novel track detectors with nanoscale spatial resolution, are used to determine the linear energy transfer (LET) of individual proton tracks from proton therapy beams by allowing visualization and 3D reconstruction of such tracks. Methods: FNTDs were exposed to proton therapy beams with nominal energies ranging from 100 to 250 MeV. Proton track images were then recorded by confocal microscopy of the FNTDs. Proton tracks in the FNTD images were fit by using a Gaussian function to extract fluorescence amplitudes. Histograms of fluorescence amplitudes were then compared with LET spectra. Results: The authors successfully used FNTDs to register individual proton tracks from high-energy proton therapy beams, allowing reconstruction of 3D images of proton tracks along with delta rays. The track amplitudes from FNTDs could be used to parameterize LET spectra, allowing the LET of individual proton tracks from therapeutic proton beams to be determined. Conclusions: FNTDs can be used to directly visualize proton tracks and their delta rays at the nanoscale level. Because the track intensities in the FNTDs correlate with LET, they could be used further to measure LET of individual proton tracks. This method may be useful for measuring nanoscale radiation quantities and for measuring the LET of individual proton tracks in radiation biology experiments.

60 APPLIED LIFE SCIENCES↗

Caerbannog Point Clouds

The Caerbannog Point Clouds provide point-sampled 3D models occluded in clouds of points. We synthesized the 3D point clouds from polygonal models, point-sampling the models and surrounding them in a point cloud such that the shape of the model is occluded in any 2D projection. We obscure our model-of-interest by repeatedly surrounding it with an amorphous cloud of points, giving the overall point cloud a structure of organic nature, like that of shrubbery. In a user study, participants were significantly better at identifying the models when visualized as 3D scatterplots under rotation than in axis-aligned 2D scatterplots. We provide three point-clouds, both occluded and unoccluded: the Stanford bunny, Utah Teapot, and OSG Cow.

97 MATHEMATICS AND COMPUTING↗

Real-time 3D analysis during electron tomography using tomviz

The demand for high-throughput electron tomography is rapidly increasing in biological and material sciences. However, this 3D imaging technique is computationally bottlenecked by alignment and reconstruction which runs from hours to days. We demonstrate real-time tomography with dynamic 3D tomographic visualization to enable rapid interpretation of specimen structure immediately as data is collected on an electron microscope. Using geometrically complex chiral nanoparticles, we show volumetric interpretation can begin in less than 10 minutes and a high-quality tomogram is available within 30 minutes. Real-time tomography is integrated into tomviz, an open-source and cross-platform 3D data analysis tool that contains intuitive graphical user interfaces (GUI), to enable any scientist to characterize biological and material structure in 3D.

36 MATERIALS SCIENCE↗

Nonlocal Means Denoising of Self-Gated and k-Space Sorted 4-Dimensional Magnetic Resonance Imaging Using Block-Matching and 3-Dimensional Filtering: Implications for Pancreatic Tumor Registration and Segmentation

Purpose: To denoise self-gated k-space sorted 4-dimensional magnetic resonance imaging (SG-KS-4D-MRI) by applying a nonlocal means denoising filter, block-matching and 3-dimensional filtering (BM3D), to test its impact on the accuracy of 4D image deformable registration and automated tumor segmentation for pancreatic cancer patients. Methods and Materials: Nine patients with pancreatic cancer and abdominal SG-KS-4D-MRI were included in the study. Block-matching and 3D filtering was adapted to search in the axial slices/frames adjacent to the reference image patch in the spatial and temporal domains. The patches with high similarity to the reference patch were used to collectively denoise the 4D-MRI image. The pancreas tumor was manually contoured on the first end-of-exhalation phase for both the raw and the denoised 4D-MRI. B-spline deformable registration was applied to the subsequent phases for contour propagation. The consistency of tumor volume defined by the standard deviation of gross tumor volumes from 10 breathing phases (σ-GTV), tumor motion trajectories in 3 cardinal motion planes, 4D-MRI imaging noise, and image contrast-to-noise ratio were compared between the raw and denoised groups. Results: Block-matching and 3D filtering visually and quantitatively reduced image noise by 52% and improved image contrast-to-noise ratio by 56%, without compromising soft tissue edge definitions. Automatic tumor segmentation is statistically more consistent on the denoised 4D-MRI (σ-GTV = 0.6 cm{sup 3}) than on the raw 4D-MRI (σ-GTV = 0.8 cm{sup 3}). Tumor end-of-exhalation location is also more reproducible on the denoised 4D-MRI than on the raw 4D-MRI in all 3 cardinal motion planes. Conclusions: Block-matching and 3D filtering can significantly reduce random image noise while maintaining structural features in the SG-KS-4D-MRI datasets. In this study of pancreatic tumor segmentation, automatic segmentation of GTV in the registered image sets is shown to be more consistent on the denoised 4D-MRI than on the raw 4D-MRI.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Astor Pass Seismic Surveys Preliminary Report

In collaboration with the Pyramid Lake Paiute Tribe (PLPT), the University of Nevada, Reno (UNR) and Optim re-processed, or collected and processed, over 24 miles of 2d seismic-reflection data near the northwest corner of Pyramid Lake, Nevada. The network of 2d land surveys achieved a near-3d density at the Astor Pass geothermal prospect that the PLPT drilled during Nov. 2010 to Feb. 2011. The Bureau of Indian Affairs funded additional seismic work around the Lake, and an extensive, detailed single-channel marine survey producing more than 300 miles of section, imaging more than 120 ft below the Lake bottom. Optim’s land data collection utilized multiple heavy vibrators and recorded over 200 channels live, providing a state-of-the-art reflection-refraction data set. After advanced seismic analysis including first-arrival velocity optimization and prestack depth migration, the 2d sections show clear fault-plane reflections, in some areas as deep as 4000 ft, tying to distinct terminations of the mostly volcanic stratigraphy. Some lines achieved velocity control to 3000 ft depth; all lines show reflections and terminations to 5000 ft depth. Three separate sets of normal faults appear in an initial interpretation of fault reflections and stratigraphic terminations, after loading the data into the OpendTect 3d seismic visualization system. Each preliminary fault set includes a continuous trace more than 3000 ft long, and a swarm of short fault strands. The three preliminary normal-fault sets strike northerly with westward dip, northwesterly with northeast dip, and easterly with north dip. An intersection of all three fault systems documented in the seismic sections at the end of Phase I helped to locate the APS-2 and APS-3 slimholes. The seismic sections do not show the faults connected to the Astor Pass tufa spire, suggesting that we have imaged mostly Tertiary-aged faults. We hypothesize that the Recent, active faults that produced the tufa through hotspring activity do not have enough offset to produce seismic terminations. We are conducting further high-resolution seismic studies (to 200 ft depths) at the tufa spire to test this hypothesis. Additional work in progress includes a collaborative, iterative joint interpretation of geologic mapping and the seismic sections for fault locations, building the geologic model; and 3d velocity modeling and imaging to locate additional faultplane images appearing between the 2d lines. Overall, the seismic exploration program cost less than $0.5M from all funders. It defines in detail the geologic structure of much of the north margin of Pyramid Lake.

01 COAL, LIGNITE, AND PEAT↗

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.

60 APPLIED LIFE SCIENCES↗

Bulk and Short-Circuit Anion Diffusion in Epitaxial Fe 2 O 3 Films Quantified Using Buried Isotopic Tracer Layers

Self-diffusion is a fundamental physical process that, in solid materials, is intimately correlated with both microstructure and functional properties. In this work, a universal approach is presented to precisely characterize self-diffusion in ionic solids by isotopically enriching anions and/or cations at specific locations within an epitaxial film stack, and characterize their redistribution at high spatial resolution with atom probe tomography. Nanoscale anion diffusivity is quantified in epitaxial α-Fe 2 O 3 thin films deposited by molecular beam epitaxy with a thin (10 nm) buried layer highly enriched in 18 O. The isotopic sensitivity of the atom probe allows precise measurement of 18 O distribution across the sharp interfaces between this layer and the surrounding Fe 2 O 3 after annealing. Short-circuit anion diffusion through 1D and 2D structural defects in Fe 2 O 3 are also directly visualized in 3D. This versatile approach to study precisely tailored thin film samples at high spatial and mass fidelity will facilitate a deeper understanding of atomic-scale diffusion phenomena.

36 MATERIALS SCIENCE↗

A complex approach to assessing porous structure of structured ceramics obtained by SPS technique

Highlights: • A complex approach to microstructural analysis of nanostructured SPS ceramics was presented. • A bunch of gas, intrusion and microscopic methods were applied for open/closed porosity determination in nanoceramics. • Kinetic TPR analysis for structural changes in nanoceramic was carried out. • 3D pore visualization for nanoceramics was provided via SEM/FIB tomography • Porosity calculations were performed via BET, BJH, t-plot, Washburn equation, FEI Avizo 9.1 software results. - Abstract: Spark plasma sintering (SPS) is a highly prospective technology providing rapid consolidation of nano-disperse compositions into structured ceramics with complex structural organization. Characterizing pore structure of such systems remains a challenge due to different types, size and shape of the pores as well as structural defects occurring in the material, thus requiring special methods to quantify certain porosity type. The paper presents a complex approach to studying structure of SPS hematite-based structured ceramics. The method involves a number of gas, intrusion and electron microscopy probing techniques to characterize open and closed pores in the ceramics bulk. Low temperature nitrogen sorption has been implemented to estimate open micro- and mesoporosity in the size range 0.7–50 nm using BET, BJH and t-plot methods to process experimental data. Additionally, structural peculiarities of consolidated structured ceramics have been studied using temperature-programmed reduction (TPR) with the kinetic analysis of the results being carried out. Volume of macropores sized above 50 nm has been measured with mercury intrusion. Closed pores and structural defects have been quantified with SEM and FIB/SEM tomography. By comparing experimental and estimated results we have shown that addressing all porosity types provides a highly precise structural characterization of the material.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Linking morphology with activity through the lifetime of pretreated PtNi nanostructured thin film catalysts

In this study, the nanoscale morphology of highly active Pt 3 Ni 7 nanostructured thin film fuel cell catalysts is linked with catalyst surface area and activity following catalyst pretreatments, conditioning and potential cycling. The significant role of fuel cell conditioning on the structure and composition of these extended surface catalysts is demonstrated by high resolution imaging, elemental mapping and tomography. The dissolution of Ni during fuel cell conditioning leads to highly complex, porous structures which were visualized in 3D by electron tomography. Quantification of the rendered surfaces following catalyst pretreatment, conditioning, and cycling shows the important role pore structure plays in surface area, activity, and durability.

30 DIRECT ENERGY CONVERSION↗

MicroXRF tomographic visualization of zinc and iron in the zebrafish embryo at the onset of the hatching period

Transition metals such as zinc, copper, and iron play key roles in cellular proliferation, cell differentiation, growth, and development. Over the past decade, advances in synchrotron X-ray fluorescence instrumentation presented new opportunities for the three-dimensional mapping of trace metal distributions within intact specimens. Taking advantage of microXRF tomography, we visualized the 3D distribution of zinc and iron in a zebrafish embryo at the onset of the hatching period. The reconstructed volumetric data revealed distinct differences in the elemental distributions, with zinc predominantly localized to the yolk and yolk extension, and iron to various regions of the brain as well as the myotome extending along the dorsal side of the embryo. The data set complements an earlier tomographic study of an embryo at the pharyngula stage (24 hpf), thus offering new insights into the trace metal distribution at key stages of embryonic development.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic cone beam CT angiography of carotid and cerebral arteries using canine model

Purpose: This research is designed to develop and evaluate a flat-panel detector-based dynamic cone beam CT system for dynamic angiography imaging, which is able to provide both dynamic functional information and dynamic anatomic information from one multirevolution cone beam CT scan. Methods: A dynamic cone beam CT scan acquired projections over four revolutions within a time window of 40 s after contrast agent injection through a femoral vein to cover the entire wash-in and wash-out phases. A dynamic cone beam CT reconstruction algorithm was utilized and a novel recovery method was developed to correct the time-enhancement curve of contrast flow. From the same data set, both projection-based subtraction and reconstruction-based subtraction approaches were utilized and compared to remove the background tissues and visualize the 3D vascular structure to provide the dynamic anatomic information. Results: Through computer simulations, the new recovery algorithm for dynamic time-enhancement curves was optimized and showed excellent accuracy to recover the actual contrast flow. Canine model experiments also indicated that the recovered time-enhancement curves from dynamic cone beam CT imaging agreed well with that of an IV-digital subtraction angiography (DSA) study. The dynamic vascular structures reconstructed using both projection-based subtraction and reconstruction-based subtraction were almost identical as the differences between them were comparable to the background noise level. At the enhancement peak, all the major carotid and cerebral arteries and the Circle of Willis could be clearly observed. Conclusions: The proposed dynamic cone beam CT approach can accurately recover the actual contrast flow, and dynamic anatomic imaging can be obtained with high isotropic 3D resolution. This approach is promising for diagnosis and treatment planning of vascular diseases and strokes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing

Modern quantum chemistry algorithms are increasingly able to accurately predict molecular properties that are useful for chemists in research and education. Despite this progress, performing such calculations is currently unattainable to the wider chemistry community, as they often require domain expertise, computer programming skills, and powerful computer hardware. In this review, we outline methods to eliminate these barriers using cutting-edge technologies. We discuss the ingredients needed to create accessible platforms that can compute quantum chemistry properties in real time, including graphical processing units–accelerated quantum chemistry in the cloud, artificial intelligence–driven natural molecule input methods, and extended reality visualization. We end by highlighting a series of exciting applications that assemble these components to create uniquely interactive platforms for computing and visualizing spectra, 3D structures, molecular orbitals, and many other chemical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bubble Transport through a Porous Lattice with an Applied Inlet Flow

Within gas-evolving electrochemical systems, bubbles negatively impact performance by covering electrode active sites for reactions, blocking electric field lines, and obstructing liquid electrolyte flow causing pressure buildup. Recent additive manufacturing advances have enabled tuned porous electrode microstructures to be created, but producing systems that maximize electrochemical throughput and minimize bubble impact remains challenging. Thus, improved physical understanding of and modeling capabilities for bubble behavior are critical to improve electrolyzer design. To address this need, this study examines rising stage bubbles within a lattice with an applied liquid flow—an underexplored regime that strongly influences an electrochemical bubble’s fate. Notably, theoretical predictions and resolved bubble simulations are complemented by experiments from a 3D-printed visualization cell that matches the simulation geometry. The minimum threshold flow rate to achieve bubble breakthrough is found to be larger for higher porosities and for smaller bubbles. Different-sized bubbles decrease expected electrochemical performance in different ways; smaller bubbles tend to stay stuck but cover less solid surface, while larger bubbles more readily break through but cover more surface while in the lattice. The bubble trajectory, deformation, and contact area provide insight into these different behaviors. These findings provide design guidelines toward creating more effective electrolyzers.

Guo, Jack [Lawrence Livermore National Laboratory ↗

Convert XML to VTK

Converts XML format files to VTK format files for visualization of 3D printing.

Ashby, AvaS.↗

Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasmas

In this project, we have developed techniques for visualizing large-scale time-varying multivariate particle and field data produced by the GPS_TTBP team. Our basic approach to particle data visualization is to provide the user with an intuitive interactive interface for exploring the data. We have designed a multivariate filtering interface for scientists to effortlessly isolate those particles of interest for revealing structures in densely packed particles as well as the temporal behaviors of selected particles. With such a visualization system, scientists on the GPS-TTBP project can validate known relationships and temporal trends, and possibly gain new insights in their simulations. We have tested the system using over several millions of particles on a single PC. We will also need to address the scalability of the system to handle billions of particles using a cluster of PCs. To visualize the field data, we choose to use direct volume rendering. Because the data provided by PPPL is on a curvilinear mesh, several processing steps have to be taken. The mesh is curvilinear in nature, following the shape of a deformed torus. Additionally, in order to properly interpolate between the given slices we cannot use simple linear interpolation in Cartesian space but instead have to interpolate along the magnetic field lines given to us by the scientists. With these limitations, building a system that can provide an accurate visualization of the dataset is quite a challenge to overcome. In the end we use a combination of deformation methods such as deformation textures in order to fit a normal torus into their deformed torus, allowing us to store the data in toroidal coordinates in order to take advantage of modern GPUs to perform the interpolation along the field lines for us. The resulting new rendering capability produces visualizations at a quality and detail level previously not available to the scientists at the PPPL. In summary, in this project we have successfully created new capabilities for the scientists to visualize their 3D data at higher accuracy and quality, enhancing their ability to evaluate the simulations and understand the modeled phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Investigating intermolecular interactions among CO 2 , water and PEEK-ionene membrane using cryo ToF-SIMS and isotopic labeling

Cryogenic time-of-flight secondary ion mass spectrometry (cryo ToF-SIMS) has emerged as a powerful tool for investigating molecular interactions, speciation, and dynamics in materials for CO 2 capture. In this study, we apply cryo ToF-SIMS to probe interactions between CO 2 , water, and PEEK-ionene membranes—a promising material for direct CO 2 capture due to its selectivity, durability, and efficiency. Despite this potential, the mechanisms governing CO 2 diffusion and the influence of water vapor on CO 2 behavior remain unclear. To address this, we loaded PEEK-ionene membranes with 13 CO 2 and D 2 O and employed cryo ToF-SIMS to visualize the 3D distribution of CO 2 and water within the membrane. While prior studies suggest that 13 CO 2 is absorbed under ambient conditions, our cryo ToF-SIMS analysis revealed no enhancement of the 13 C/ 12 C ratio, suggesting weak CO 2 -membrane interactions. As a result, CO 2 vaporizes even at low temperatures (−140°C) under vacuum conditions. In contrast, D 2 O displayed a relatively homogeneous distribution in the membrane, suggesting stronger water-membrane interactions via hydrogen bonding (18–20 kJ/mol). Interestingly, CO 2 was not detected in D 2 O-loaded membranes, indicating minimal interference from water vapor on CO 2 diffusion. As a comparison, the cryo ToF-SIMS data show that 13 CO 2 can readily react with a basic Na 2 CO 3 aqueous solution to form NaH 13 CO 3 . These findings demonstrate cryo ToF-SIMS as a critical technique for understanding gas-water-membrane interactions, offering insights for membrane functionalization to improve CO 2 capture efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactive automated Bragg peak identification with 3D neutron scattering data

Neutron scattering experiments have undergone significant technological development through large area detectors with concurrent enhancements in neutron transport and electronic functionality. Data collected for neutron events include detector pixel location in 3D, time and associated metadata, such as, sample orientation, neutron wavelength, and environmental conditions. RadiaSoft and Oak Ridge National Laboratory personnel are considering single-crystal diffraction data from the TOPAZ instrument. We are leveraging a new method for rapid, interactive analysis of neutron data using NVIDIA’s IndeX 3D volumetric visualization framework. We have implemented machine learning techniques to automatically identify Bragg peaks and separate them from diffuse backgrounds and analyze the crystalline lattice parameters for further analysis. The implementation of automatic peak identification into IndeX allows scientists to visualize and analyze data in real-time. Our methods include a robust comparison with current analysis techniques which show improvement in a variety of aspects. These improvements will be incorporated into IndeX for visualization to allow scientists an interactive tool for crystal analysis.

Kilpatrick, Matthew↗