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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hydrothermal mineral alterations in the Brady and Desert Peak geothermal fields

Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. The analysis was performed using ENVI's Target Detection process against USGS library spectra for Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite. Each compressed file includes three raster images created after fusing the target detection results for all minerals: _fusion_all - Contains the 8 layers resulting from target detection and fusion of the 5 minerals _fusion_all_normal - Contains each layer as above, after Winsorization (99% percentile on the positive side only due to skewness of results), and normalization of each layer to achieve a range between [0-1] _fusion_final - Contains a fused raster by sub-setting the normalized layers, with the results of MTMF, MTTCIMF, OSP and SAM. Both CEM and MF were discarded as being less accurate than MTMF, and TCIMF is less accurate than MTTCIMF, ACE results were discarded because they were notably different from the rest of the analyses. The base_names are: brady - Brady geothermal area only desert - Desert Peak geothermal area only hymap - Full image analysis comprising both the Brady and Desert Peak geothermal areas

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Correlating Nanoscale Secondary Ion Mass Spectrometry and Atom Probe Tomography Analysis of Uranium Enrichment in Metallic Nuclear Fuel

Distribution and enrichment of 235U within nuclear fuels are essential to material performance and reactor safety. With the development of metallic U fuels, understanding 235U homogeneity has become increasingly important, however, it is difficult to map with high spatial, and mass resolution to analyze both matrix and secondary phase precipitates. Here, we analyze 235U enrichment in matrix and carbide phases in LEU-Mo via two chemical imaging modalities: nanoscale secondary ion mass spectrometry (nanoSIMS) and atom probe tomography (APT). NanoSIMS and APT provided consistent results, with no statistically significant difference between measured and nominal enrichment (19.75 % 235U).

U-10Mo, atom probe tomography, nanoscale secondary↗
DOE OSTI2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope – I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near-infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired ‘target’ point spread function (PSF). We present here an initial application of imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the ‘leakage’), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper (‘Paper II’) explores the implications for weak lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Current Density Regulated Atomic to Nanoscale Process on Li Deposition and Solid Electrolyte Interphase Revealed by Cryogenic Transmission Electron Microscopy

Current density has been perceived to play a critical rule for controlling Li deposition morphology and solid electrolyte interphase (SEI). However, the atomic level mechanism of current density on Li deposition and the SEI remains unclear. In this work, based on cryogenic transmission electron microscopy imaging combined with energy dispersive X-ray spectroscopy and electron energy loss spectroscopy electronic structure analyses, we reveal the atomic level correlation of Li deposition morphology and SEI with current density. We discover that increasing current density leads to increased overpotential for Li nucleation and growth, leading to the transition from growth-limited to nucleation-limited mode for Li dendrite. Independence of current density, the electrochemically deposited Li metal (EDLi) exhibits crystalline whisker-like morphology. The SEI formed at low current density (0.1 mA cm -2 ) is monolithic amorphous; while, a current density of above 2 mA cm -2 leads to a mosaic structured SEI, featuring an amorphous matrix with Li 2 O and LiF dispersoids, and the thickness of the SEI increases with the increase of current density. Uniquely, the Li 2 O particles is spatially located at the top surface of the SEI, while LiF is spatially adjacent to the Li-SEI interface. These results highlight the possible tuning of crucial structural and chemical features of EDLi and SEI through altering deposit conditions and consequently direct correlation with electrochemical performance.

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

Eocene-Oligocene Metamorphism, Fluid Flow and Deformation in the Ruby Mountains-East Humboldt Range Metamorphic Core Complex

Metamorphic core complexes are ubiquitous in collapsed orogens globally and play a primary role in crustal exhumation. Here, we investigate the metamorphic history of the Ruby Mountains-East Humboldt Range metamorphic core complex, Nevada, using petrochronology to understand how magmatism, metamorphism and deformation interact to modulate crustal rheology, and the timing of exhumation within the Sevier orogenic belt. Field study, microstructural analysis, thermobarometry and laser ablation split-stream monazite, titanite and allanite petrochronology of the mylonitic footwall were integrated to elucidate the pressure-temperature-time (P-T-t) evolution. Major-, trace-element and quartz-in-garnet thermobarometry show peak metamorphism occurred at 5.5–6 kbar and 600–650°C across the study area. Monazite and titanite U-(Th)-Pb petrochronology constrain this episode of metamorphism to 88–81 Ma with the structurally deepest samples yielding dates down to ca. 71 Ma. The preservation of peak metamorphic mineral assemblages indicates these rocks remained at near-peak temperature conditions into the Cenozoic. Cenozoic metamorphism occurred during a punctuated episode contemporaneous with the Great Basin ignimbrite flare up. All samples show a distinct 39–37 Ma population of monazite, titanite and allanite dates that correlate with the emplacement of quartz diorite and gabbro intrusions throughout the footwall. Accessory phases contain zoning textures in backscattered electron images that are consistent with fluid-mediated dissolution-reprecipitation reactions. The U-(Th)-Pb analyses from these zones yield 39–27 Ma dates interpreted as the timing of fluid flow. The results of this study elucidate the integrated importance of magmatism, melting and fluid flow in driving the coupled evolution of Late Cretaceous metamorphism within the Sevier hinterland and the subsequent Cenozoic metamorphic core complex development that exhumed the middle crust.

58 GEOSCIENCES↗
DOE OSTI2026

FTIR imaging identifies alterations in lung tissue structure and biochemical composition in human idiopathic pulmonary fibrosis

Idiopathic Pulmonary Fibrosis (IPF) is a chronic, progressive, and fatal lung disease characterized by damage to the epithelial tissue and a reduced ability of the alveoli to repair themselves. This impaired repair process leads to abnormal accumulation of extracellular matrix (ECM), resulting in scarring and stiffening of lung tissue. Fourier transform infrared imaging (FTIRI) is a promising technique for imaging the biochemical changes related to fibrotic changes in a label-free and non-destructive manner, which can be analyzed to mark the progression of IPF. In this study, FTIRI was used to image human lung tissue biopsies with IPF and control biopsies without disease. In-depth spectral analyses were performed to observe the biochemical changes in the tissue composition using FTIRI. The parameters that were analyzed included collagen structure, total lipid content, lipid chain length, and phospholipids. Results showed a significant increase in lipid content in IPF compared to control, where long chain lipids dominated and phospholipids were reduced. Minor changes in collagen structure were also observed in IPF, likely attributed to the excess formation of extracellular matrix in the disease. These findings indicate that FTIRI has the potential to be a promising diagnostic technique to understand the molecular changes during IPF, as analysis of infrared data can reveal detailed biochemical information regarding disease progression and provide spatial insights on the molecular changes across the IPF lung tissue.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Brady’s Geothermal Field Computed Tomography Core Characterization

We present a publicly accessible database centered around multi-scale Computed Tomographic (CT) imaging of samples from the BCH-03 well, supplemented by a wide range of supporting geological analyses (Brown, et al., 2022). The data include detailed petrologic descriptions of core samples, core-scale medical CT scans, high-resolution micro-CT scans, thin section photomicrographs, elemental abundance data from X-ray diffraction, velocity wave measurements, and helium porosimetry of the matrix.

computed tomography↗
DOE OSTI2024

High–Performance NiCo 2 O 4 /Graphene Quantum Dots for Asymmetric and Symmetric Supercapacitors with Enhanced Energy Efficiency

For the sustainable growth of future generations, energy storage technologies like supercapacitors and batteries are becoming more and more common. However, reliable and high-performance materials’ design and development is the key for the widespread adoption of batteries and supercapacitors. Quantum dots with fascinating and unusual properties are expected to revolutionize future technologies. However, while the recent discovery of quantum dots honored with a Nobel prize in Chemistry, their benefits for the tenacious problem of energy are not realized yet. In this context, herein, chemical-composition tuning enabled exceptional performance of NiCo 2 O 4 (NCO)/graphene quantum dots (GQDs) is reported, which outperform the existing similar materials, in supercapacitors. A comprehensive study is performed on the synthesis, characterization, and electrochemical performance evaluation of highly functional NCO/GQDs in supercapacitors delivering enhanced energy efficiency. The high-performance, functional NCO/GQDs electrode materials are synthesized by the incorporation of GQDs into NCO. The effect of variable amount of GQDs on the energy performance characteristics of NCO/GQDs in supercapacitors is studied systematically. In-depth structural and chemical bonding analyses using X-ray diffraction (XRD) and Raman spectroscopic studies indicate that all the NCO/GQDs composites crystallize in the spinel cubic phase of NiCo 2 O 4 while graphene integration evident in all the NCO/GQDs. The scanning electron microscopy imaging analysis reveals homogeneously distributed spherical particles with a size distribution of 5–9 nm validating the formation of QDs. The high-resolution transmission electron microscopy analyses reveal that the NCOQDs are anchored on graphene sheets, which provide a high surface area of 42.27 m 2 g –1 and high mesoporosity for the composition of NCO/GQDs-10%. In addition to establishing reliable electrical connection to graphene sheets, the NCOQDs provide reliable 3D-conductive channels for rapid transport throughout the electrode as well as synergistic effects. Chemical-composition tuning, and optimization yields NCO/GQDs-10% to deliver the best specific capacitance of 3940 Fg –1 at 0.5 Ag –1 , where the electrodes retain ≈98% capacitance after 5000 cycles. The NCO/GQD-10%//AC asymmetric supercapacitor device demonstrates outstanding energy density and power density values of 118.04 Wh kg –1 and 798.76 W kg –1 , respectively. The NCO/GQDs-10%//NCO/GQDs-10% symmetric supercapacitor device delivers excellent energy and power density of 24.30 Wh kg –1 and 500 W kg –1 , respectively. These results demonstrate and conclude that NCO/GQDs are exceptional and prospective candidates for developing next-generation high-performance and sustainable energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2024

Generation of realistic input parameters for simulating atmospheric point-spread functions at astronomical observatories

High-fidelity simulated astronomical images are an important tool in developing and measuring the performance of image-processing algorithms, particularly for high precision measurements of cosmic shear – correlated distortions of images of distant galaxies due to weak gravitational lensing caused by the large-scale mass distribution in the Universe. For unbiased measurements of cosmic shear, all other sources of correlated image distortions must be modeled or removed. One such source is the correlated blurring of images due to optical turbulence in the atmosphere, which dominates the point-spread function (PSF) for ground-based instruments. In this work, we leverage data from weather forecasting models to produce wind speeds and directions, and turbulence parameters, that are realistically correlated with altitude. To study the resulting correlations in the size and shape of the PSF, we generate simulated images of the PSF across a ~10 square-degree field of view – the size of the camera focal plane for the Vera C. Rubin Observatory in Chile – using weather data and historical seeing for a geographic location near the Observatory. We make quantitative predictions for two-point correlation functions (2PCF) that are used in analyses of cosmic shear. We observe a strong anisotropy in the two-dimensional 2PCF, which is expected based on observations in real images, and study the dependence of the orientation of the anisotropy on dominant wind directions near the ground and at higher altitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Magnetic imaging and statistical analysis of the metamagnetic phase transition of FeRh with electron spins in diamond

Magnetic imaging based on nitrogen-vacancy (NV) centers in diamond has emerged as a powerful tool for probing magnetic phenomena in fields ranging from biology to physics. A key strength of NV sensing is its local-probe nature, enabling high-resolution spatial images of magnetic stray fields emanating from a sample. However, this local character can also form a drawback for analyzing the global properties of a system, such as a phase transition temperature. Here, we address this challenge by using statistical analyses of magnetic-field maps to characterize the first-order temperature-driven metamagnetic phase transition from the antiferromagnetic to the ferromagnetic state in FeRh. After imaging the phase transition and identifying the regimes of nucleation, growth, and coalescence of ferromagnetic domains, we statistically characterize the spatial magnetic-field maps to extract the transition temperature and thermal hysteresis width. By analyzing the spatial correlations of the maps in relation to the magnetocrystalline anisotropy and external magnetic field, we detect a reorientation of domain walls across the phase transition. The employed statistical approach can be extended to the study of other magnetic phenomena with NV magnetometry or other sensing techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Molecular Imaging of Matrix Metalloproteinase-2 in Atherosclerosis Using a Smart Multifunctional PET/MRI Nanoparticle

Matrix metalloproteinases from macrophages are important intraplaque components that play pivotal roles in plaque progression and regression. This study sought to develop a novel multifunctional positron emission tomography (PET) and magnetic resonance imaging (MRI) contrast agents based on MMP-2 cleavable nanoparticles to noninvasive assessment of MMP-2 activity in mouse carotid atherosclerotic plaques. Macrophage-rich vascular lesions were induced by carotid ligation plus high-fat diet and streptozotocin-induced diabetes in CL57/BL6 mice. To render iron oxide nanoparticles (IONP) specific for the extracellular MMP-2, the magnetic nanoparticle base material has been derivatized with 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) for the nuclear tracer 64 Cu labeling and the MMP-2-cleavable peptide modified with polyethylene glycol 2000, yielding a multi-modality reporter ( 64 Cu-NOTA-IONP@MMP2c-PEG2K, MMP2cNPs) for PET/MR imaging. Small animal PET imaging and biodistribution data revealed that MMP2cNPs exhibited remarkable plaque uptake (3.06 ± 0.87% ID/g and 1.83 ± 0.28% ID/g at 4 and 12 h, respectively). And MMP2cNPs were rapidly cleared from the contralateral normal carotid artery, resulting in excellent plaque-to-normal carotid artery contrasts. Furthermore, in vivo MRI showed a preferential accumulation of MMP2cNPs in atherosclerotic lesions compared with the non-cleavable reference compound, MMP2ncNPs. In addition, histological analyses revealed iron accumulations in the carotid atherosclerotic plaque, in colocalization with MMP-2 expression and macrophages. Using a combination of innovative imaging modalities, in this study, we demonstrate the feasibility of applying the novel smart MMP2cNPs as a PET/MR hybrid imaging contrast agent for detection of MMP-2 in atherosclerotic plaque in vivo.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Effect of glutathione-coated Mn-doped ZnS quantum dots on nutrient delivery in basil ( Ocimum basilicum ) plants

Ensuring efficient nutrient delivery while minimizing environmental impacts remains a significant challenge for modern agriculture. Nanotechnology-based fertilizers offer promising strategies to improve nutrient uptake and bioavailability in plants. This research aims to evaluate the use of Glutathione-coated Manganese-doped Zinc Sulfide quantum dots (GSH-ZnS-Mn QDs) as a potential nano fertilizer for basil (Ocimum basilicum). QDs' physicochemical properties were characterized using UV–Vis spectroscopy, photoluminescence, FTIR, and energy-dispersive X-ray spectroscopy, confirming successful Mn doping and glutathione surface functionalization. Basil plants were exposed to different concentrations of GSH-ZnS-Mn QDs under soil and hydroponic conditions. Plant growth parameters, oxidative stress responses, photosynthetic pigments, and macro- and micronutrient uptake were assessed using biochemical assays and inductively coupled plasma optical emission spectrometry (ICP-OES). Elemental uptake, spatial distribution, and zinc speciation were further investigated using synchrotron-based micro-X-ray fluorescence (μ-XRF) imaging and X-ray absorption near-edge structure (XANES) spectroscopy. Results show that exposure to GSH-ZnS-Mn QDs resulted in a concentration-dependent increase in leaf and stem biomass, accompanied by enhanced Zn accumulation in plant tissues. Catalase activity decreased across all tested concentrations, suggesting a shift toward glutathione-dependent antioxidant pathways rather than oxidative damage. Chlorophyll levels exhibited moderate reductions at higher concentrations. The higher increase in macronutrient (K, Ca, and Mg) uptake was reported in plants exposed to 200 ppm of QDs. μ-XRF imaging indicated a selective accumulation of Zn in roots and stems, with partial translocation to leaves. XANES analyses revealed that Zn from QDs was mainly converted into organic Zn species, such as Zn-phytate, Zn-acetate, and Zn-cysteine, indicating transformation and complexation within the plant. The findings demonstrate that a glutathione coating on GSH-ZnS-Mn QDs improves biocompatibility and nutrient delivery efficiency. These results highlight the relevance of surface functionalization in regulating nanoparticle fate, transformation, and nutrient bioavailability, supporting the potential application of GSH–ZnS–Mn QDs as modern nano fertilizers.

Basil↗
DOE OSTI2020

Sweeping potential regulated structural and chemical evolution of solid-electrolyte interphase on Cu and Li as revealed by cryo-TEM

A fundamental understanding of solid-electrolyte interphase (SEI) is paramount importance for controlling the cycling performance of rechargeable lithium metal batteries. The structural and chemical evolution of SEI with respect to electrochemical operating condition remains barely established. Here we develop a unique method for imaging the evolution of SEI formed on the Cu foil under sweeping electrochemical potential. By using cryogenic TEM imaging combined with energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy electronic structure analyses, we reveal that, for the vinylene carbonate (VC)-free electrolyte, the SEI formed at 1.0 V is a monolithic amorphous structure, which evolves to amorphous matrix embedded with Li 2 O particles as the voltage decreases to 0 V. In the case of VC-containing electrolyte, the SEI is featured by an amorphous matrix with Li 2 O particles from 1.0 V to 0 V. The thickness of SEI formed on Cu foil increases with decreasing voltage. Associated with the localized charge modulation by the surface topographic feature and defects in the Cu foil, the SEI layer shows direct spatial correlation with these structural defects in the Cu. In addition, upon Li deposition, the SEI formed on the Li metal has similar thickness with, but different composition from the SEI formed on the Cu foil at 0 V. Furthermore, those results provide insight toward SEI engineering for enhanced cycling stability of Li metal.

25 ENERGY STORAGE↗
DOE OSTI2022

A Machine Learning Framework to Predict Images of Edge-on Protoplanetary Disks

The physical structure and properties of protoplanetary disks are typically derived from spatially resolved disk images. Edge-on disks in particular provide an important view point on the vertical structure and degree of settling of disks. Such analyses rely on radiative transfer (RT) calculations that are generally computationally intensive due to the high optical depth of disks. Here we present a machine learning framework that has the potential to dramatically speed up the forward modeling process by approximating the results of RT calculations. This framework, trained on an initial set of RT calculations, utilizes an autoencoder neural network to enable the generation of synthetic scattered light images of edge-on disks directly from a set of physical parameters. We demonstrate that this framework generates synthetic images 2–3 orders of magnitude faster than using RT calculations. These machine learning-generated images appear to approximate the RT images well, in particular preserving their size and shape. We also find a strong correlation between the latent space representations of the generated disk images and several of their associated physical parameters. Finally, we discuss potential changes to the framework, such as methods to further improve the image quality, extending the framework to multiple wavelengths, and inverting the process to infer physical parameters from observed images. Overall, these new tools have the potential to enable a more efficient and uniform analysis of edge-on disk properties and the initial conditions of planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

DeepGhostBusters: Using Mask R-CNN to Detect and Mask Ghosting and Scattered-Light Artifacts from Optical Survey Images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as "ghosting artifacts" or "ghosts") and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. However, the identification of ghosts and scattered-light artifacts is challenging due to a) the complex morphology of these features and b) the large data volume of current and near-future surveys. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered-light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms and traditional convolutional neural networks methods. We propose that a multi-step pipeline combining Mask R-CNN segmentation with a classical CNN classifier provides a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Soft X-Ray Tomography Has Evolved into a Powerful Tool for Revealing Cell Structures

Over the past three decades, soft X-ray tomography (SXT) has rapidly evolved from a proof-of-concept microscopy method into a high-throughput quantitative imaging modality. This advancement enables researchers to address central questions in cell biology. Despite its relatively short developmental period compared to light and electron microscopy, SXT has emerged as a powerful imaging technology. It enables measuring chemical changes in cellular organelles, analyzing three-dimensional structures of whole cells and creating digital cellular models to study cell motility. We discuss the unique nature of SXT to visualize cells without fixation or labeling, enabling quantitative analyses of organelle chemical composition. We explore SXT microscopes available worldwide, SXT segmentation software, and the diverse cell types studied using this technique. We conclude with emerging directions in SXT imaging, including a brief discussion of recent discoveries that are highly influential and likely to become integral to cell biology textbooks.

Weinhardt, Venera↗
DOE OSTI2022

Gantryless Associated-Particle Neutron Radiography

The present work reports on the development of techniques for in-field fast-neutron radiography measurements using the associated-particle imaging (API) method. The API method employs alpha-neutron coincidences from the d+t→α+n reaction to enable fast neutron transmission imaging with excellent contrast using a wide cone beam. However, for field radiography applications, the API method is burdened by the need for the relative positions of the source and detector to be known. Fortunately, these relative positions can be inferred from transmission data. The inferred positions also enable accurate stitching of multiple images into a composite image even when using a low-resolution detector panel and acquiring images having few overlapping pixels. The developed techniques address analysis of measurements where (1) the source and detector panel are separately hand positioned rather than held in registration by a gantry, (2) multiple detector panel positions within the “coincident cone” of tagged neutrons are required to piece together an image of an item of interest, and (3) normalization measurements that have identical source-detector positioning but without the inspected object are not possible. The present work will describe the system calibrations (including timing calibrations and neutron direction calibrations) necessary for subsequent analyses, the method of locating the detector in the coincident cone of neutrons with millimeter precision using the timing and directions of coincident neutrons, the method of calculating a normalization image for a given detector panel position, and the method used to project multiple images into a common image.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗