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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗
DOE OSTI2020

Cusp-artifacts in high order superresolution optical fluctuation imaging

Superresolution optical fluctuation imaging (SOFI) is a simple and affordable super-resolution imaging technique, and attracted a growing community over the past decade. However, the theoretical resolution enhancement of high order SOFI is still not fulfilled. In this study, we identify “cusp artifacts” in high order SOFI images, and show that the high-order cumulants, odd-order moments and balanced-cumulants (bSOFI) are highly vulnerable to cusp artifacts. Our study provides guidelines for developing and screening for fluorescence probes, and improving data acquisition for SOFI. The new insight is important to inspire positive utilization of the cusp artifacts.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Smartphone application for visualizing building air leakage

Annually, unwanted air leakage through building envelopes accounts for 4 quads of energy consumption in the United States, which translates to about 10% of total building energy consumption. Locating and sealing leakage sites is crucial fordecreasing building energy consumption. Smartphones are ubiquitous and contain sophisticated cameras and highperformance processors that could be employed to visualize air leakage using the background-oriented schlieren imaging technique, making leak detection cheaper and easier. This technique requires a textured and high-contrast background such as a brick or concrete masonry unit wall, a building air leak that has a temperature difference compared with the ambient air, and an imaging system. This work focuses on using smartphones as the imaging system to visualize air leakages. The paper discusses application development and the results of testing to determine leakage visualization performance as a function of leak temperature. The results show that leaks with a temperature difference greater than 16°C compared with the ambient air temperature were visualized using existing smartphones.

Boudreaux, Philip [ORNL] (ORCID:0000000229564665)↗
DOE OSTI2021

Toward Discovering the Structure and Dynamics of the Sun-Interstellar Medium System (Los Alamos LDRD Report)

We have taken major steps toward developing the tools necessary to explore with unprecedented resolution the plasma structure and dynamics of the Sun-interstellar medium (ISM) interaction region, known as the heliosheath. We have applied a rigorous imaging technique known as Generalized Ridge Regression (GRR) to construct statistically robust sky maps of hydrogen energetic neutral atoms (ENAs) emanating from this region and detected by the Los Alamos-led IBEX-Hi ENA imager [1] on NASA’s Interstellar Boundary Explorer (IBEX) mission [2]. Our methods go far beyond the map reconstruction process currently applied by the IBEX Science Operations Center (ISOC), opening up the possibility of new discovery science with the IBEX data set and positioning LANL for a lead science role for the upcoming Interstellar Mapping and Acceleration Probe (IMAP) mission [3] for which LANL is providing two key experiments. We have successfully demonstrated that the new maps are higher resolution and are capable of revealing structures that are not presently resolveable in standard ISOC maps

58 GEOSCIENCES↗
DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗
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

Titanium porous-transport layers for PEM water electrolysis prepared by tape casting

While the porous-transport layer (PTL) is a key component in PEM electrolyzers, it is one of the most underexplored due to limited available structures. In this work, we present a novel PTL design for PEM water electrolyzers enabled by a cost-effective, scalable tape-casting technique. Here, a precise control of the PTL pore structure is achieved by incorporating poreformers of various sizes, and by varying the titanium and poreformer ratio. The structures are characterized with SEM and synchrotron X-ray computed tomography imaging techniques. Comprehensive electrochemical performance analysis demonstrates that higher titanium loading provides improved contact at the catalyst-layer/PTL interface but suffers from severe mass-transport losses due to gas bubbles. We solve this mass-transport problem by mixing in large poreformer beads that produce a highly porous structure with excellent gas removal properties yet still maintaining mechanical integrity. The PTL fabricated with 60:40 Ti:PMMA ratio and 60 μm PMMA bead size outperformed the standard commercial Ti powder-based PTL by 62 mV at 4 A/cm 2 .

25 ENERGY STORAGE↗
DOE OSTI2025

Ptychography at all wavelengths

Ptychography is a computational imaging technique that operates across multiple wavelength regimes, from electron (picometres) to X-ray (~0.1 nm), extreme ultraviolet (~10 nm) and visible light (micrometres). By reconstructing both amplitude and phase from diffraction patterns, ptychography enables high-resolution, quantitative imaging without conventional limitations imposed by lens-based optics. Ptychography has enabled advances across a range of scales: achieving deep-sub-angstrom resolution with electron microscopy, becoming an indispensable tool at X-ray synchrotron facilities worldwide and overcoming the trade-offs between resolution and field-of-view in optical imaging. This Primer provides a unified treatment of ptychography across these wavelength regimes. First, we discuss theoretical foundations, reconstruction algorithms, experimental considerations and wavelength-specific challenges. We then give examples of raw and processed data from various configurations and wavelengths. Next, we highlight key applications of ptychography in life sciences, materials science and industry. We also discuss data standards, open-source software implementations and best practices for ensuring reproducibility across different wavelength regimes. Finally, we consider limitations and future opportunities for ptychography. Together with accompanying datasets and code implementations, this Primer aims to serve newcomers and experienced practitioners in the field, facilitating broader adoption of ptychography across different disciplines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Particle-Tracking Proton Computed Tomography—Data Acquisition, Preprocessing, and Preconditioning

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

42 ENGINEERING↗
DOE OSTI2022

Information content of and the ability to reconstruct dichroic X-ray tomography and laminography

Dichroic tomography is a 3D imaging technique in which the polarization of the incident beam is used to induce contrast due to the magnetization or orientation of a sample. The aim is to reconstruct not only the optical density but the dichroism of the sample. The theory of dichroic tomographic and laminographic imaging in the parallel-beam case is discussed as well as the problem of reconstruction of the sample’s optical properties. The set of projections resulting from a single tomographic/laminographic measurement is not sufficient to reconstruct the magnetic moment for magnetic circular dichroism unless additional constraints are applied or data are taken at two or more tilt angles. For linear dichroism, three polarizations at a common tilt angle are insufficient for unconstrained reconstruction. However, if one of the measurements is done at a different tilt angle than the other, or the measurements are done at a common polarization but at three distinct tilt angles, then there is enough information to reconstruct without constraints. Possible means of applying constraints are discussed. Furthermore, it is shown that for linear dichroism, the basic assumption that the absorption through a ray path is the integral of the absorption coefficient, defined on the volume of the sample, along the ray path, is not correct when dichroism or birefringence is strong. This assumption is fundamental to tomographic methods. An iterative algorithm for reconstruction of linear dichroism is demonstrated on simulated data.

Marcus, Matthew A. (ORCID:0000000325277586)↗
DOE OSTI2022

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Vibrational Sum-Frequency Generation Hyperspectral Microscopy for Molecular Self-Assembled Systems

In this review, we discuss the recent developments and applications of vibrational sum-frequency generation (VSFG) microscopy. This hyperspectral imaging technique can resolve systems without inversion symmetry, such as surfaces, interfaces and noncentrosymmetric self-assembled materials, in the spatial, temporal, and spectral domains. We discuss two common VSFG microscopy geometries: wide-field and confocal point-scanning. We then introduce the principle of VSFG and the relationships between hyperspectral imaging with traditional spectroscopy, microscopy, and time-resolved measurements. We further highlight crucial applications of VSFG microscopy in self-assembled monolayers, cellulose in plants, collagen fibers, and lattice self-assembled biomimetic materials. In these systems, VSFG microscopy reveals relationships between physical properties that would otherwise be hidden without being spectrally, spatially, and temporally resolved. Lastly, we discuss the recent development of ultrafast transient VSFG microscopy, which can spatially measure the ultrafast vibrational dynamics of self-assembled materials. The review ends with an outlook on the technical challenges of and scientific potential for VSFG microscopy.

Chemistry↗
DOE OSTI2020

RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models

Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale values carry important information about porosity, kerogen content, and mineral composition of the shale. Here, we introduce RockFlow, a method based on generative flow models that creates grayscale volumes from 2D training data. We apply RockFlow to baseline binary micro-CT image volumes and compare performance to a previously proposed model. We also show the extension of our model to 2D grayscale data by generating grayscale image volumes from 2D SEM and dual modality nanoscale shale images. The results show that our method underestimates the porosity and surface area on the binary baseline datasets but is able to generate realistic grayscale image volumes for shales. With improved binary data preprocessing, we believe that our model is capable of generating synthetic porous media volumes for a very broad class of rocks from shale to carbonates to sandstone.

58 GEOSCIENCES↗
DOE OSTI2020

Holotomography Phase-Retrieval

Holotomography is a non-destructive x-ray imaging technique which allows to visualize the interior morphology of object without damaging them. It is similar to x-ray computed tomography (CT), but unlike conventional CT, which is based on the attenuation of x-rays passing through the object, holotomography exploits the phase shift caused by the sample. This phase-contrast imaging allows to increase image contrast by recovering refractive index of materials and is proven to be more sensitive to density variations than conventional absorption-based X-ray imaging when applied to low-Z materials. In holotomography, the phase is retrieved by measuring the variations in intensity of the object at different sample to detector distances. Several algorithms exist to perform this task such as, contrast transfer function (CTF), transport of intensity equation (TIE), and a mixed approach which combine both TIE and CTF.

Forien, Jean-Baptiste↗
DOE OSTI2022

In-Situ Spatial Mapping of Hydrogen in Yttrium Hydrides at LANSCE

This report summarizes the neutron imaging techniques and experimental activities performed at the Los Alamos Neutron Science Center (LANSCE) with the main goal of measuring temperature driven hydrogen diffusion within bulk-yttrium hydride (YH x ) materials. The experimental results and technique developments reported herein support the US Department of Energy Office of Nuclear Energy’s (DOE-NE) Microreactor Program under Technology Maturation. In particular, the critical need to experimentally validate and verify hydrogen-diffusion models of metal hydrides used in hightemperature microreactor designs is addressed by means of high-spatial-resolution neutron imaging coupled with custom-built and application-specific furnaces. These capabilities were designed to apply large temperature gradients across centimeter-sized YH x pellets to simulate conditions faced in the microreactor environment. Neutron imaging, combined with in-situ sample heating, enables near real-time tracking of hydrogen diffusion in YH x on the sub-millimeter scale. In this report, an overview of neutron imaging methodology and technologies are given in the context of recent spatial measures of hydrogen concentrations in similar metals hydrides. Additionally, the commissioning and operation of a custom-built compact dual-zone furnace is given along with details on the first two in-situ heating measurements of YH x performed over the 2020 and 2021 LANSCE operation cycles. In parallel with in-situ heating measurements, neutron computed tomography scans were performed to visualize hydrogen aggregates in post-heated YH x samples. Analysis and results from these neutron imaging measurements are given along with outlooks and plans for improving future hydrogen diffusion measurements at LANSCE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Characterization of a collimated neutron imager for low-rate fast neutron imaging

Spatial localization of special nuclear materials (SNM) via their neutron signatures amidst background requires knowledge of the background neutron environment or a means of separating a source from background based on low amounts of information. This requirement has created the need for characterizing the spatial distribution of the cosmogenic neutron background. Neutron scatter cameras have been developed and optimized for rapid detection of high activity sources, but have low imaging efficiency, making it difficult to use them to characterize low rate diffuse sources, such as the neutron background. The Low Intensity Neutron Imaging System (LINIS) is a collimated neutron imager that has been designed and optimized for imaging diffuse cosmogenic neutron background in the energy range of 0.5–15 MeV. LINIS operates using 16 liquid scintillation detectors shielded by ultra-high molecular weight polyethylene cylindrical collimators in a staggered orientation and rotates to 7 discrete positions, giving it roughly 2π sensitivity. Finally, LINIS has been characterized using (α, n) and fission neutron sources using two imaging techniques for neutron source localization, simple backprojection and Maximum Likelihood Expectation Maximization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗