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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

Dark-field X-ray microscopy with structured illumination for three-dimensional imaging

Dark-field X-ray microscopy is a lens-based technique that enables real-space imaging of heterogeneous micro- and meso-scale ordered materials. However, achieving accurate three-dimensional (3D) reconstruction often requires meticulous sample alignment or rastering, requiring complex rotational setups and extended acquisition times. To address these challenges, we introduce a structured illumination technique optimized for 3D imaging of ordered materials at sub-micrometer length scales. Our approach employs a coded aperture to spatially modulate the incident X-ray beam, enabling 3D structural reconstruction from images captured at various aperture positions. Unlike current 3D imaging approaches, which often rely on rotational or rastering methods, our technique uses scanning X-ray silhouettes of the coded aperture for depth resolution along the diffraction axis. This eliminates the need for sample rotation or rastering, resulting in a highly stable and efficient imaging modality. We validated the efficacy of this approach through experimental imaging of an isolated twin domain within a bulk single crystal of an iron pnictide using a dark-field X-ray microscope. This advancement aligns with the enhanced brightness upgrades of modern synchrotron radiation facilities, unlocking new possibilities for high-resolution imaging of ordered materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Understanding FLiNaK Salt Intrusion Behavior on Nuclear-Grade Graphite via Neutron Tomography

Graphite is an essential material as a neutron moderator in molten salt reactors (MSRs). To understand the impact of salt on the graphite structure to develop structural materials for MSRs, molten salt intrusion behavior on nuclear-grade graphite was studied. The graphite samples, IG-110 and PCEA, were tested for infiltration with LiF-NaF-KF (FLiNaK) at 750°C, 5 bar for 12 h, and, after the intrusion experiment, the graphite was analyzed by neutron imaging. The graphite and Li from FLiNaK showed great contrast in the neutron attenuation coefficient. Thus, the salt behavior in the graphite structure has been visualized for the first time without damaging the sample. The 3D image of the graphite was reconstructed after a neutron computed tomography scan, and the average salt coverage distribution of the XY surface in different depths was obtained from the reconstructed 3D images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Reconstruction of cosmic-ray muon events with CUORE

We report the in-situ 3D reconstruction of through-going muons in the CUORE experiment, a cryogenic calorimeter array searching for neutrinoless double beta (0vββ) decay, leveraging the segmentation of the detector. Due to the slow time response of the detector, time-of-flight estimation is not feasible. Therefore, the track reconstruction is performed using a multi-objective optimization algorithm that relies on geometrical information from the detector as a whole. We measure the integral flux of cosmic-ray muons underground at the Laboratori Nazionali del Gran Sasso, and find our value to be in good agreement with other experiments that have performed a similar measurement. To our knowledge, this work represents the first demonstration of 3D particle tracking and reconstruction of through-going muons with per-event angular determination in a millikelvin cryogenic detector array. The analysis performed for this work will be critical for validating the muon-related background in CUPID, a next-generation 0vββ experiment, and for follow-up studies on detector response and on delayed products induced by cosmic-ray muons.

Adams, D. Q. [University of South Carolina]↗
NASA NTRSDate not supplied

Modeling Methods for 3D Lightning Mapping from Space

Global lightning detection has advanced greatly over the past few decades both on ground and from orbit. Ground-based systems like the Lightning Mapping Array (LMA) excel at high-precision 3D reconstruction of local flashes, while spaceborne lightning sensors have much larger potential coverage but are limited by coarser resolution and often rely on data from other instruments to determine 3D flash locations. CubeSpark is a new mission concept focused on combining these two methods in the form of six small satellites in low-Earth orbit. CubeSpark will combine RF and bispectral optical measurements of lightning in order to map the 3D structure of both individual flashes and their parent thunderstorms at 1-2 km spatial resolution on a global scale, enabling a host of new atmospheric, climate, and space electricity studies. The goal of this study is to assess the feasibility and expected resolution of lightning mapping via indivudal VHF sources using different methods and detector combinations. Flashes were simulated beneath orbital configurations consisting of 1-6 satellites, taking into account the complicated interactions with Earth's ionosphere. In the multi-satellite (>5) approach, RF detectors on each satellite measure the arrival times of impulsive VHF sources to collectively pinpoint their locations in 3D and reconstruct flashes with higher resolution than has been achieved from space. The same can process can be performed with 3-4 satellites by constraining sources' horizontal locations with onboard optical imagers. A 1-2 station approach follows the established method of determining the height of an RF source using the arrival time difference between direct RF waves and their reflections off the Earth's surface. Here we present preliminary results of the expected accuracy of these methods to inform potential satellite missions like CubeSpark.

Lightning↗
NASA NTRSDate not supplied

Modeling Methods for 3D Lightning Mapping from Space

Global lightning detection has advanced greatly over the past few decades both on ground and from orbit. Ground-based systems like the Lightning Mapping Array (LMA) excel at high-precision 3D reconstruction of local flashes, while spaceborne lightning sensors have much larger potential coverage but have been limited by coarser resolution and often rely on data from other instruments to determine flash location. The primary focus of this study is to examine the level of flash detail that can be expected from one or more low-Earth orbiting small satellites that combine VHF and optical measurements of lightning, which is a new mission concept called CubeSpark. The goal of CubeSpark is to map the 3D charge structure of thunderstorms at 1-2 km spatial resolution on a global scale, enabling a host of new atmospheric and space electricity studies. In order to maximize the potential data quality and minimize potential cost, flashes were simulated beneath single- and multi-satellite configurations. In the multi-satellite approach, RF detectors on each of the six satellites would measure the arrival times of impulsive VHF sources to collectively pinpoint their locations in 3D and reconstruct flashes with higher resolution than has been achieved from space. A single-station approach for 3D observation of lightning would follow the method of determining altitudes of strong VHF sources that produce trans-ionospheric pulse pairs (TIPPs) while relying on an on-board high-resolution optical day/night lightning mapper for approximate horizontal flash locations. Here we present preliminary results comparing the expected data fidelity and accuracy between these methods to inform potential satellite missions like CubeSpark.

lightning↗
DOE OSTI2024

recon3d

SAND2025-00533O recon3d is a software tool that provides automated 3D reconstruction and meshing capabilities. It processes labeled 3D image data from various sources, starting from image stacks, and calculates 3D feature distributions like size, shape, and location. The software also has tools for downscaling rectilinear grid data and creating tetrahedral meshes directly from image data. recon3d can be used by novice users via the command line with a properly formatted configuration file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Emery, John↗
DOE OSTI2023

DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding

Abstract Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million technical drawings with 132,890 object names and 22,394 viewpoints extracted from 14 years of US design patent documents. We demonstrate the usefulness of DeepPatent2 with conceptual captioning. We further provide the potential usefulness of our dataset to facilitate other research areas such as 3D image reconstruction and image retrieval.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Experimental validation of solid oxide fuel cell polarization modeling: An LSM-YSZ/YSZ/Ni-YSZ case study

Polarization modeling based on the measured I-V curves is a useful tool for analyzing SOFC performance and diagnosing performance limitations. Using the polarization model, the overpotential of a cell is usually separated into different polarization contributions, including area specific ohmic polarization, activation polarization, and anodic and cathodic concentration polarizations. In this study, we aim to experimentally validate the accuracy of the polarization model. As a case study, anode-supported cells with LSM-YSZ/YSZ/Ni-YSZ configuration are used. By curve-fitting the I-V curves of a cell tested under different cathode oxygen partial pressures into the polarization model, the contributions of different polarization losses are quantified. To validate the polarization model, independent experiments/studies including electrochemical impedance spectroscopy, cathode kinetics study, ex-situ diffusivity measurement, and tortuosity measurement using 3D reconstructed anode are conducted. The results from polarization modeling and from validation studies are in good agreement, thereby validating the polarization model for SOFC performance analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Assessing the interfacial corrosion mechanism of Inconel 617 in chloride molten salt corrosion using multi-modal advanced characterization techniques

The United States Department of Energy (DOE) has committed to expanding the domestic clean energy portfolio in response to the rising challenges of energy security in the wake of climate change. Accordingly, the construction of a series of Generation IV reactor technologies are being demonstrated, including sodium-cooled, small modular, and molten chloride fast reactors (MCFRs). To date, there are no fully qualified structural materials for constructing MCFRs. A number of commercial structural alloys have been considered for the construction of MCFRs, including alloys from the Inconel and Hastelloy series. Informed qualification of structural materials for the construction of MCFRs in the future can only be ensured by expanding the current fundamental knowledgebase of information pertaining to material performance under environmental stressors relevant to operation of the reactor, including corrosion susceptibility. The purpose of this investigation is to illustrate how a correlative multi-modal electron microscopy characterization approach, including the novel application of focused-ion beam 3D reconstruction capabilities, can elucidate the corrosion mechanism of a candidate structural material Inconel 617 for MCFR in NaCl-MgCl 2 eutectic salt at 700°C for 1,000 h. Evidence of intergranular corrosion, Ni and Fe dealloying, and Cr-O enrichment along the grain boundary, which most likely corresponds to Cr 2 O 3 , is a phenomenon that has been documented in other Ni-based superalloys exposed to chloride molten salt systems. Additional corrosion products, including the formation of insoluble MgAl 2 O 4 , within the porous network produced by the salt attack is a novel observation. In addition, Mo 3 Si 5 and τ 2 precipitates are detected in the alloy bulk and are dissolved by the salt. Furthermore, the lack of detection of design γ' precipitates in Inconel 617 after 1,000 h could indicate that the molten salt corrosion mechanism has indirectly induced a phase transformation of Al 2 TiNi (τ 2 ) and Ni 3 (Al,Ti) (γ’) phase. This investigation provides a comprehensive understanding of molten salt corrosion mechanisms in a complex material system such as a commercial structural alloy for applications in MCFRs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electron tomography imaging methods with diffraction contrast for materials research

Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable the visualization of three-dimensional (3D) microstructures ranging from atomic to micrometer scales using 3D reconstruction techniques based on computed tomography algorithms. This 3D microscopy method is called electron tomography (ET) and has been utilized in the fields of materials science and engineering for more than two decades. Although atomic resolution is one of the current topics in ET research, the development and deployment of intermediate-resolution (non-atomic-resolution) ET imaging methods have garnered considerable attention from researchers. This research trend is probably not irrelevant due to the fact that the spatial resolution and functionality of 3D imaging methods of scanning electron microscopy (SEM) and X-ray microscopy have come to overlap with those of ET. In other words, there may be multiple ways to carry out 3D visualization using different microscopy methods for nanometer-scale objects in materials. From the above standpoint, this review paper aims to (i) describe the current status and issues of intermediate-resolution ET with regard to enhancing the effectiveness of TEM/STEM imaging and (ii) discuss promising applications of state-of-the-art intermediate-resolution ET for materials research with a particular focus on diffraction contrast ET for crystalline microstructures (superlattice domains and dislocations) including a demonstration of in situ dislocation tomography.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

XCal: model-based approach to X-ray CT spectral calibration

Transmission X-ray computed tomography (CT) is widely used to quantitatively reconstruct 3D objects composed of multiple materials. However, accurate CT reconstruction requires the system to be calibrated to account for the effective X-ray spectrum. Unfortunately, measurement of the effective spectrum is ill-posed, and existing calibration methods require that the system be recalibrated when the system parameters are changed. In this paper, we propose XCal, a multi-energy model-based spectral calibration approach for X-ray CT. The XCal approach models the effective spectrum using a separable physics-based model of the CT system. The model parameters are then estimated by fitting calibration data with known objects at multiple energies. An important advantage of XCal is that it allows the user to change scanner settings, such as the source voltage or X-ray filters, without the need for recalibration. Evaluations on simulated and measured datasets demonstrate that XCal significantly improves the accuracy of the estimated spectrum as compared to existing calibration methods.

Li, Wenrui [Purdue Univ., West Lafayette, IN (Unit↗
DOE OSTI2021

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired. To improve the imaging quality as a result of this limitation, convolutional neural networks (CNNs) have recently been shown to be capable of producing 3D models from visible light images or medical x-ray images rendered by volumetric computed tomography. Here, we propose a CNN to reconstruct 3D ICF spherical shells from single radiographs. We also examine the sensitivity of the 3D reconstruction to different illumination models using preprocessing techniques such as pseudo-flatfielding. To resolve the issue of the lack of 3D supervision, we show that training the CNN utilizing synthetic radiographs produced by known simulation methods allows for reconstruction of experimental data as long as the experimental data are similar to the synthetic data. We also show that the CNN allows for 3D reconstruction of shells that possess low mode asymmetries. Further comparisons of the 3D reconstructions with direct multiple LOS measurements are justified.

3D Reconstruction↗
DOE OSTI2020

Atomic electron tomography in three and four dimensions

Atomic electron tomography (AET) has become a powerful tool for atomic-scale structural characterization in three and four dimensions. It provides the ability to correlate structures and properties of materials at the single-atom level. With recent advances in data acquisition methods, iterative three-dimensional (3D) reconstruction algorithms, and post-processing methods, AET can now determine 3D atomic coordinates and chemical species with sub-Angstrom precision, and reveal their atomic-scale time evolution during dynamical processes. In this work, we review the recent experimental and algorithmic developments of AET and highlight several groundbreaking experiments, which include pinpointing the 3D atom positions and chemical order/disorder in technologically relevant materials and capturing how atoms rearrange during early nucleation at four-dimensional atomic resolution.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Model and Standard Operating Procedures Supporting Signal Variation Flow Graph Analysis

This document will describe the principles of the Signal Variation Flow Technique, and the uncertainty models generated using it. We focus on the capture of the variation between the ideal signal and the measured signal. The ideal signal is defined to represent the signal output of a system whose full state behavior is known, with no variation in environment or during operation, and whose photons trajectories are not modified by the object. A CT uncertainty analysis is the result of two main steps. First, the radiography regime extends from the source to the collected image, which is 2D in the case of standard CT. This maps all upstream uncertainties into the variation observed on the radiograph and captures all variation in the physical domain. Second, the reconstruction regime extends from the captured images to the reconstructed 3D image. This regime is purely in the mathematical domain and corrects reconstruction algorithm artifacts/anomalies. The present work focuses on building the model through the radiography regime. The reconstruction regime is expected to be largely a study of algorithmic sensitivity, requiring the definition of a range of standardized tests through which the algorithms would be run. Radiographic variation would then be mapped through reconstruction sensitivities to predict the signal variation in the final image. An incomplete list for the reconstructed image variation output basis includes voxel density, edge blur and length variation, in analogous fashion to the basis functions presented in this work. The signal variation occurs in several forms at the radiograph. These forms are gathered into a complete basis set of functions describing all variation on the radiograph. The scale of each basis function is calculated independently via a specific SVFG. This includes 0D pixel noise (0DI), 0D energy noise (0DE), 1D blur (1DB), 1D length (1DL) or 2D position (2DP). These models are orthogonal in that they each explore a space in the signal variation domain that cannot be reached by the other basis functions. The variation basis functions, and associated SVFG models are split by output dimensionality, a term loosely used for categorization, and explained further below.

42 ENGINEERING↗
DOE OSTI2020

Adaptive Machine Learning for Bragg Coherent Diffraction Imaging (BCDI) of 3D Electron Density Maps with Application to La 2-x Ba x CuO 4 (LBCO) High Temperature Superconductor Studies [PowerPoint]

Understanding mesoscale heterogeneity is important for evaluating fatigue and failure of structural materials and for manufacturing processes. Data-driven tools can facilitate in guiding effort investment (measurements and computations) at various stages of the materials development. Our 3D reconstruction approach is to find a set of coefficients which define a bounding surface of the electron density. Data for training the 3D CNN was generated by sampling coefficients from uniform distributions. Test vs. prediction values are shown for the 28 even-valued coefficients for 1000 test structures, with the best and worst performers highlighted. The adaptive part of this work utilized a model independent extremum seeking (ES). The predictions of the CNN were used as the starting point for the ES algorithm. The convergence of the ES algorithm for 3 different structures is illustrated, and the robustness of the adaptive ML approach was demonstrated on experimentally measured 3D crystal from high energy diffraction microscopy. Reconstruction of a non-uniform density volume with different levels of Poisson noise is also shown. Preliminary attempts at reconstructing measured La 2-x Ba x CuO 4 diffraction patterns have so far failed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗