Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “TOMOGRAPHY”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2022

Nanoscale Compositional Mapping of Commercial LiNi 0.8 Co 0.15 Al 0.05 O 2 Cathodes Using Atom Probe Tomography

Nickel-rich cathodes provide improved specific capacity that lead to higher gravimetric energy density, critical for electric vehicles. However, poor long-term capacity retention at elevated temperatures/high C-rates (the rate of charge and discharge on a battery) stem from material issues: surface phase changes, corrosive side reactions with the electrolyte, ion dissolution and propagation of cracks. Introducing dopants, developing nanoscale surface coatings and graded core-shell structures have all improved the electrochemical performance of nickel-rich cathodes. However, a material level understanding on the effect of Li composition and distribution in Ni-rich cathodes is limited, due to a lack of characterization methods available that can directly image Li at the nanoscale. Hence, it is critical to establish methods such as atom probe tomography (APT), having both nanometer scale spatial resolution and high compositional sensitivity to quantitatively analyze battery cathodes. To fully realize its potential as a method for quantitative compositional analysis of commercial Li-ion batteries, we provide a comprehensive description of the challenges in sample preparation and analyze the dependency of the analysis parameters, specifically laser pulse energy on the measured stoichiometry of elements in a high Ni content cathode material; LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA). In this work, our findings show the stoichiometry variations cannot be explained by charge state ratios or Ga implantation damage alone during FIB preparation, indicating that additional factors such as crystallographic orientation may need to be considered to achieve quantitative nanoscale compositional analysis of such battery cathodes using APT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations

Abstract We report a new model (WUS256) of radially anisotropic seismic wavespeeds of the crust and upper mantle of the western United States (WUS) obtained from adjoint waveform tomography for the purpose of improving synthetic waveform fits to observed data. WUS256 is based on inversion of over 94,000 waveforms from 72 earthquakes recorded by nearly 3,400 stations. We started with the SPiRaL global model (Simmons et al., 2021, https://doi.org/10.1093/gji/ggab277 ) and waveforms in the period band of 50–120 s. We followed a conservative multiscale inversion approach with eight stages and 256 total inversion iterations which enabled monotonic misfit reduction to 20‐s minimum‐period waves. WUS256 relied on time‐frequency (TF) phase misfits and a trust region limited memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) optimization. Hessian‐vector products were used to qualitatively assess model resolution. Results indicate that WUS256 has good coverage of the continental regions to depths of about 150 km and is able to resolve features on lateral scales of about 200 km. We quantify waveform fits by the reduction in TF and normalized amplitude difference misfits between WUS256 and the SPiRaL starting model. WUS256 significantly improves waveform fits with misfit reduction 64% for both inversion and validation data sets compared to the SPiRaL starting model and shows even better fits compared to other models. Waveform fits illustrate that WUS256 reproduces body‐waves, fundamental mode surface waves as well as late arriving dispersed and/or scattered short period surface waves. The improvement in waveform fit indicates that WUS256 can be used to reproduce path effects on regional complete waveforms and moment tensor inversions.

58 GEOSCIENCES↗
DOE OSTI2023

Attentional Ptycho-Tomography (APT) for three-dimensional nanoscale X-ray imaging with minimal data acquisition and computation time

Abstract Noninvasive X-ray imaging of nanoscale three-dimensional objects, such as integrated circuits (ICs), generally requires two types of scanning: ptychographic, which is translational and returns estimates of the complex electromagnetic field through the IC; combined with a tomographic scan, which collects these complex field projections from multiple angles. Here, we present Attentional Ptycho-Tomography (APT), an approach to drastically reduce the amount of angular scanning, and thus the total acquisition time. APT is machine learning-based, utilizing axial self-Attention for Ptycho-Tomographic reconstruction. APT is trained to obtain accurate reconstructions of the ICs, despite the incompleteness of the measurements. The training process includes regularizing priors in the form of typical patterns found in IC interiors, and the physics of X-ray propagation through the IC. We show that APT with ×12 reduced angles achieves fidelity comparable to the gold standard Simultaneous Algebraic Reconstruction Technique (SART) with the original set of angles. When using the same set of reduced angles, then APT also outperforms Filtered Back Projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT) and SART. The time needed to compute the reconstruction is also reduced, because the trained neural network is a forward operation, unlike the iterative nature of these alternatives. Our experiments show that, without loss in quality, for a 4.48 × 93.2 × 3.92 µm 3 IC (≃6 × 10 8 voxels), APT reduces the total data acquisition and computation time from 67.96 h to 38 min. We expect our physics-assisted and attention-utilizing machine learning framework to be applicable to other branches of nanoscale imaging, including materials science and biological imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A tabletop X-ray tomography instrument for nanometer-scale imaging: reconstructions

Abstract We show three-dimensional reconstructions of a region of an integrated circuit from a 130 nm copper process. The reconstructions employ x-ray computed tomography, measured with a new and innovative high-magnification x-ray microscope. The instrument uses a focused electron beam to generate x-rays in a 100 nm spot and energy-resolving x-ray detectors that minimize backgrounds and hold promise for the identification of materials within the sample. The x-ray generation target, a layer of platinum, is fabricated on the circuit wafer itself. A region of interest is imaged from a limited range of angles and without physically removing the region from the larger circuit. The reconstruction is consistent with the circuit’s design file.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements

Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanoscale. Both techniques have limitations, particularly APT, because of insufficient understanding of void imaging. Here, we employ a correlative APT and STEM approach to investigate the APT imaging process and reveal that voids can lead to either an increase or a decrease in local atomic densities in the APT reconstruction. Simulated APT experiments demonstrate the local density variations near voids are controlled by the unique ring structures as voids open and the different evaporation fields of the surrounding atoms. We provide a general approach for quantifying chemical segregations near voids within an APT dataset, in which the composition can be directly determined with a higher accuracy than STEM-based techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanostructure-specific X-ray tomography reveals myelin levels, integrity and axon orientations in mouse and human nervous tissue

Myelin insulates neuronal axons and enables fast signal transmission, constituting a key component of brain development, aging and disease. Yet, myelin-specific imaging of macroscopic samples remains a challenge. Here, we exploit myelin’s nanostructural periodicity, and use small-angle X-ray scattering tensor tomography (SAXS-TT) to simultaneously quantify myelin levels, nanostructural integrity and axon orientations in nervous tissue. Proof-of-principle is demonstrated in whole mouse brain, mouse spinal cord and human white and gray matter samples. Outcomes are validated by 2D/3D histology and compared to MRI measurements sensitive to myelin and axon orientations. Specificity to nanostructure is exemplified by concomitantly imaging different myelin types with distinct periodicities. Finally, we illustrate the method’s sensitivity towards myelin-related diseases by quantifying myelin alterations in dysmyelinated mouse brain. This non-destructive, stain-free molecular imaging approach enables quantitative studies of myelination within and across samples during development, aging, disease and treatment, and is applicable to other ordered biomolecules or nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Formation of three-dimensional bicontinuous structures via molten salt dealloying studied in real-time by in situ synchrotron X-ray nano-tomography

Abstract Three-dimensional bicontinuous porous materials formed by dealloying contribute significantly to various applications including catalysis, sensor development and energy storage. This work studies a method of molten salt dealloying via real-time in situ synchrotron three-dimensional X-ray nano-tomography. Quantification of morphological parameters determined that long-range diffusion is the rate-determining step for the dealloying process. The subsequent coarsening rate was primarily surface diffusion controlled, with Rayleigh instability leading to ligament pinch-off and creating isolated bubbles in ligaments, while bulk diffusion leads to a slight densification. Chemical environments characterized by X-ray absorption near edge structure spectroscopic imaging show that molten salt dealloying prevents surface oxidation of the metal. In this work, gaining a fundamental mechanistic understanding of the molten salt dealloying process in forming porous structures provides a nontoxic, tunable dealloying technique and has important implications for molten salt corrosion processes, which is one of the major challenges in molten salt reactors and concentrated solar power plants.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bayesian tomography of high-dimensional on-chip biphoton frequency combs with randomized measurements

Abstract Owing in large part to the advent of integrated biphoton frequency combs, recent years have witnessed increased attention to quantum information processing in the frequency domain for its inherent high dimensionality and entanglement compatible with fiber-optic networks. Quantum state tomography of such states, however, has required complex and precise engineering of active frequency mixing operations, which are difficult to scale. To address these limitations, we propose a solution that employs a pulse shaper and electro-optic phase modulator to perform random operations instead of mixing in a prescribed manner. We successfully verify the entanglement and reconstruct the full density matrix of biphoton frequency combs generated from an on-chip Si 3 N 4 microring resonator in up to an 8 × 8-dimensional two-qudit Hilbert space, the highest dimension to date for frequency bins. More generally, our employed Bayesian statistical model can be tailored to a variety of quantum systems with restricted measurement capabilities, forming an opportunistic tomographic framework that utilizes all available data in an optimal way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography

Abstract Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B 2 -CSRO instead of the generally-expected D0 3 -CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D0 3 -CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Non-averaged single-molecule tertiary structures reveal RNA self-folding through individual-particle cryo-electron tomography

Large-scale and continuous conformational changes in the RNA self-folding process present significant challenges for structural studies, often requiring trade-offs between resolution and observational scope. Here, we utilize individual-particle cryo-electron tomography (IPET) to examine the post-transcriptional self-folding process of designed RNA origami 6-helix bundle with a clasp helix (6HBC). By avoiding selection, classification, averaging, or chemical fixation and optimizing cryo-ET data acquisition parameters, we reconstruct 120 three-dimensional (3D) density maps from 120 individual particles at an electron dose of no more than 168 e - Å -2 , achieving averaged resolutions ranging from 23 to 35 Å, as estimated by Fourier shell correlation (FSC) at 0.5. Each map allows us to identify distinct RNA helices and determine a unique tertiary structure. Statistical analysis of these 120 structures confirms two reported conformations and reveals a range of kinetically trapped, intermediate, and highly compacted states, demonstrating a maturation folding landscape likely driven by helix-helix compaction interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution. In this study, we introduce the method of time-resolved Brownian tomography to investigate the temporal evolution of the 3D atomic structures of individual nanocrystals in solution. The methodology is applied to examine the atomic-level structural transformations of Pt nanocrystals during oxidative etching. The time-resolved 3D atomic maps reveal the structural evolution of dissolving Pt nanocrystals, transitioning from a crystalline to a disordered structure. Our study demonstrates the emergence of a phase at the nanometer length scale that has received less attention in bulk thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

PhaseT3M: 3D imaging at 1.6 Å resolution via electron cryo-tomography with nonlinear phase retrieval

Electron cryo-tomography (cryo-ET) enables 3D imaging of complex, radiation-sensitive structures with molecular detail. However, image contrast from the interference of scattered electrons is nonlinear with atomic density and multiple scattering further complicates interpretation. These effects degrade resolution, particularly in conventional reconstruction algorithms, which assume linearity. Particle averaging can reduce such issues but is unsuitable for heterogeneous or dynamic samples ubiquitous in biology, chemistry, and materials sciences. Here, we develop a phase retrieval-based cryo-ET method, PhaseT3M. We experimentally demonstrate its application to an approximately 7 nm Co3O4 nanoparticle on an approximately 30 nm carbon substrate, achieving a maximum resolution of 1.6 Å, surpassing conventional limits using standard cryo-TEM equipment. PhaseT3M uses a multislice model for multiple scattering and Bayesian optimization for alignment and computational aberration correction, with a positivity constraint to recover ‘missing wedge’ information. Applied directly to biological particles, it enhances reconstruction quality and reduces artifacts, establishing a standard for routine 3D imaging with phase contrast.

Biophysics↗
DOE OSTI2025

Soft X-ray tomography reveals variations in B. subtilis biofilm structure upon tasA deletion

Bacterial biofilms are complex cell communities within a self-produced extracellular matrix, crucial in various fields but challenging to analyze in 3D. We developed a "biofilm-in-capillary" growth method compatible with full-rotation soft X-ray tomography, enabling high-resolution 3D imaging of bacterial cells and their matrix during biofilm formation. This approach offers 50 nm isotropic spatial resolution, rapid imaging, and quantitative native analysis of biofilm structure. Using Bacillus subtilis biofilms, we detected coherent alignment and chaining of wild-type cells towards the oxygen-rich capillary tip. In contrast, the ΔtasA genetic knock-out showed a loss of cellular orientation and changes in the extracellular matrix. Adding TasA protein to the ΔtasA strain restored matrix density and led to cell assembly compaction, but without the chaining observed in wild-type biofilms. This scalable and transferable approach opens new avenues for examining biofilm structure and function across various species, including mixed biofilms, and response to genetic and environmental factors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

Operando X-ray micro-computed tomography (µCT) provides an opportunity to observe the evolution of Li structures inside pouch cells. Segmentation is an essential step to quantitatively analyzing µCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the datasets. Herein, we report a computational approach, batteryNET, to train an Iterative Residual U-Net-based network to detect Li structures. The resulting semantic segmentation shows singular Li-related component changes, addressing diverse morphologies in the dataset. In addition, visualizations of the dead Li are provided, including calculations about the volume and effective thickness of electrodes, deposited Li, and redeposited Li. We also report discoveries about the spatial relationships between these components. The approach focuses on a method for analyzing battery performance, which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantum circuit cutting with maximum-likelihood tomography

Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.

97 MATHEMATICS AND COMPUTING↗