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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Application of high-speed, species-specific chemiluminescence imaging for laminar flame speed and Markstein length measurements in spherically expanding flames

A high-speed chemiluminescence imaging diagnostic system has been developed and characterized for measuring species-specific properties of spherically expanding flames, with the objective of obtaining synchronized measurements of multiple flame properties from a single flame experiment. The imaging system comprises a high-speed camera coupled to a high-speed image intensifier and optical filters to isolate emission from desired excited species. Here this study validates the diagnostic scheme specifically for measuring laminar flame speed and Markstein length from chemiluminescence at three wavelength bands corresponding to OH*, CH*, and total chemiluminescence, respectively. Mixtures of methane-air and methane/ethane-air were tested at initial conditions of atmospheric pressure and room temperature. An under-utilized methodology for computing unburned Markstein length from burned Markstein length was implemented. Flame speed modeling of each mixture was conducted in Chemkin using AramcoMech 2.0. No significant differences were observed between the results derived from the three emission wavelength bands for the flame speeds nor the Markstein lengths. For both of these properties, excellent agreement was observed between the experimental results and the values reported in the literature. Because laminar flame speed and Markstein length show no dependency on the imaging wavelength, the present results imply that multiple flame properties, such as laminar flame speed, Markstein length, flame thickness, and excited-species intensity profiles, can all be acquired simultaneously for the same flame using this method.

42 ENGINEERING↗
DOE OSTI2022

Identification of a quasi-liquid phase at solid–liquid interface

Abstract An understanding of solid–liquid interfaces is of great importance for fundamental research as well as industrial applications. However, it has been very challenging to directly image solid–liquid interfaces with high resolution, thus their structure and properties are often unknown. Here, we report a quasi-liquid phase between metal (In, Sn) nanoparticle surfaces and an aqueous solution observed using liquid cell transmission electron microscopy. Our real-time high-resolution imaging reveals a thin layer of liquid-like materials at the interfaces with the frequent appearance of small In nanoclusters. Such a quasi-liquid phase serves as an intermediate for the mass transport from the metal nanoparticle to the liquid. Density functional theory-molecular dynamics simulations demonstrate that the positive charges of In ions greatly contribute to the stabilization of the quasi-liquid phase on the metal surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Systematic Interpretation of Subsurface Proppant Concentration from Drilling Mud Returns: Case Study from Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin

The aim of this study is generation and validation of a proppant log using analysis of drilling mud returns for child wells. Proppant log provides qualitative as well as quantitative insights into spatial distribution of proppant sand particles from prior stimulation of parent wells. While the basic methodology was developed and formalized during analysis of material collected from through fracture cores at Hydraulic Fracturing Test Site in Midland Basin (HFTS – 1), the test wells at HFTS – 2 in the neighboring Delaware Basin allowed the opportunity to validate the workflow on actual mud return samples from subsurface. As a child well is being drilled, periodic mud return samples are collected at the rig site and preserved for analysis. The workflow involves systematic cleaning of the samples including various steps such as washing, drying and segregation of samples into relevant size fractions of interest (< Mesh 20) based on specifications of pumped sand during stimulation of the parent well. Clean samples are imaged using high resolution transparency scanning. Scan images are then systematically analyzed for particles of interest using computer vision techniques. Sample counts are further validated using elemental analysis of smaller sub-samples at various depths of interest. This step is necessary to isolate proppant versus other naturally occurring minerals such as sulphates and carbonates which show similar optical properties. We successfully correlated proppant distribution against the existing parent well and validated propped versus relatively un-propped zones for a child well at the test site. The advantage of testing the proppant log concept at the HFTS – 2 site is the plethora of additional diagnostic data that is available to validate our primary observations. We can correlate spatial proppant distribution against variability in stimulation response based on independent observations such as image logs, microseismic attributes as well as DAS response, all of which tend to corroborate one another. One of our significant successes was being able to describe varying degrees of impact of the parent well along the lateral length of a stimulated child well. Our workflow represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling child wells. This provides unique opportunities to better understand the current state of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R003/2477415/urtec-2021-5189-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5189 2 reservoir being targeted including zones which are likely more drained relative to others and how the planned completion of the child well can be improved. Lastly, this log can be useful is validating optimal well spacing in relatively new fields under development.

58 GEOSCIENCES↗
DOE OSTI2020

Performance of Scintillation Detectors Based on Quantum Dots in a Semiconductor Matrix (Final Technical Report)

InAs Quantum Dots (QDs) embedded into GaAs semiconductor waveguide have unique scintillation properties, valuable for nuclear security, medical imaging, and high energy physics. In this work, we developed thick (~25um) epitaxial heterostructres with high luminescence efficiency composed of self-assembled nano-engineered InAs QDs grown by molecular beam epitaxy. In this type of detector, the GaAs matrix acts as a stopping material for charged particles or photons generating electrons captured by the QDs acting as luminescence centers. The QD medium is designed to provide fast capture of electrons into QDs (few ps), high QD luminescence efficiency at room temperature (>50%), and strong red-shift of photoluminescence (PL) from the GaAs absorption edge (>250nm). Typical devices consist of a 10-25um thick GaAs layer with embedded sheets of modulation p-type doped InAs QDs and an InGaAs photodetector tuned to the QD emission wavelength. The thick GaAs layer acts also as a waveguide when layer-transferred onto a low-index substrate. Waveguiding and self-absorption (~1cm -1 ) were studied using photoluminescence with scanning laser excitation and modeled with ray optics approximation and geometrical coupling of high-index waveguide to a collection fiber. Scintillating signals from α-particles were analyzed with both an external photodiode (PD) and an integrated PD which provided an improved optical coupling. In the former case, the external InGaAs PD was air-coupled to the scintillator and had the light collection efficiency of about 1% corresponding to limited light extraction through a planar interface with air due to total internal reflection. The mean charge collected by the integrated PD was in the range of (3÷5)×10 4 photoelectrons per 1 MeV of deposited energy, or ~13-20% of the theoretically achievable light yield. Timing of the integrated device was measured by wire-bonding it to the input of an 8 GHz IC. The scintillation response shows an extremely fast 0.3-0.6 ns decay constant and about 40-70 ps time resolution, limited by the system noise. The combined light yield and decay time makes the InAs/GaAs QD heterostructures the fastest high yield scintillation material reported making it valuable for high energy physics and medical imaging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Gamma ray Imaging Based Methods to Improve the Accuracy of Uranium Holdup Quantification

Deposits in commercial uranium processing facilities of interest to nuclear safeguards are predominantly low enriched uranium (LEU). The shapes and sizes of holdup deposits can vary significantly, thus making it difficult to model the deposits accurately for calibration purposes. This presents a challenge to currently employed methods such as the Generalized Geometry Holdup (GGH) that rely on quantifying 235U mass by simplifying deposit shapes as a point, a line, or an area. In this work, gamma ray imaging using high energy resolution Germanium Gamma Imagers (GeGI™) is employed to determine the distribution of uranium inside the source containment. Two types of imaging methods are employed; coded-aperture imaging and Compton imaging. Gamma-ray emissions seen in different regions of the image are quantified using an inverse gamma-ray transport solver being developed at ORNL. Using measured data, the inverse method will be used to solve for unknown source parameters such as source matrix thickness, density, and attenuation due to container wall and shielding. The intrinsic efficiency of the detector is determined based on a library of built-in response functions and key dimensions of the detector (e.g., thickness and radius of the detector crystal). Measurements are performed in both imaging modalities using uranium sources of well-known masses and enrichments configured inside mocked-up holdup fixtures. Results from the two imaging modalities are intercompared. The paper presents preliminary results of the imaging measurements and the progress made in the computational methods to quantify uranium mass.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Combining visible shadowgraph imaging with x-ray imaging for dynamic shock experiments

Interrogating ejecta particles launched from target materials that are undergoing dynamic shock can be done with both x-ray imaging and visible shadowgraph imaging. Our dynamic testing must be done inside a containment vessel with limited access ports available. We designed an imaging system to relay both types of imaging systems through a single port using the same optical relay and then splitting the images onto three separate high-speed imaging cameras outside the containment vessel. X-ray imaging provides ejecta density measurements. Shadowgraph imaging that is done at two wavelengths (blue and red) constrains ejecta particle size distributions and provides areal density measurements of the ejecta cloud. The ejecta particles are positioned 225 mm before the x-ray scintillators; this arrangement permits a folded mirror system to allow the shadowgraph data to bypass the x-ray scintillators. This configuration results in spatial separations between the intermediate image planes of the x-ray and shadowgraph images along the optical axis. At the position of the x-ray intermediate image plane, mirrors are positioned such that the shadowgraph images are kicked out and their images are sent on to different cameras. Positioning of the large doublet relay lenses keeps shrapnel from impacting the vessel containment windows.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.

Schuhl, Haley [Donald Danforth Plant Science Cente↗
DOE OSTI2020

High dynamic range CdTe mixed-mode pixel array detector (MM-PAD) for kilohertz imaging of hard x-rays

A hard x-ray, high-speed, high dynamic range scientific x-ray imager is described. The imager is based on the mixed-mode pixel array detector (MM-PAD) readout chip coupled to a 750 µm thick cadmium telluride (CdTe) sensor. The full imager is a 2 × 3 tiled array of MM-PAD sensor/readout chip hybrids. CdTe improves detection for high energy x-rays as compared to silicon sensors, enabling efficient x-ray imaging to extend to >100 keV. The detector is capable of 1 kHz imaging and in-pixel circuitry has been designed to allow for well depths of greater than 4 × 10 6 80 keV x-rays. Here, a charge integrating front-end allows for quantitative measurement of high flux x-ray images beyond the capabilities of photon counting detectors. Detector performance is summarized and experimental measurements are presented.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗
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 OSTI2020

In-situ Observations of Directed Energy Deposition Additive Manufacturing Using High-Speed X-ray Imaging

In laser-based directed energy deposition (DED) additive manufacturing, interactions among the laser beam, particle flow, and melt pool influence the properties of the solidified final part. Two separate DED systems, one with high powder flow rates to represent industrial-scale DED processing and the other with low powder flow rates for individual particle tracking, were synchronized with the high-speed imaging setup at the Advanced Photon Source in Argonne National Laboratory. In-situ x-ray imaging of the DED process using both systems highlighted the influence of powder flow rates. Increased powder flow rates resulted in less laser absorption into the melt pool, leading to a transition from a keyhole mode to a melt pool without a keyhole but with surface fluctuations due to powder flow. Increased velocities of particles during powder flow resulted in a decrease in particle melting times and a greater propensity for porosity formation. Altogether, better understanding of the interactions that occur during various scales of the DED process will enable flexibility, control, and new materials development in DED-based additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Material Characterization of Grade 91 Steel Welds using, Micro-resolution Ultrasonic Imaging System

Grade 91 (9Cr-1Mo-V) steel is a common structural material for fossil-fuel fired and nuclear power plants because of its creep strength and oxidation resistance at high temperatures. In this research, we studied the feasibility of correlating the high-resolution images obtained from the immersion ultrasonic imaging technique to microstructure regions in Grade 91 steel plate weldments. The high-resolution ultrasonic images presented in this paper were generated using a 20-MHz focused transducer as the transmitter, and a laser vibrometer as the receiver in the through transmission configuration to produce longitudinal and shear waves. This nondestructive evaluation (NDE) method was used to identify the Fusion Zone (FZ), Heat-Affected Zone (HAZ), and Base Metal (BM) regions of Grade 91 cold metal transfer (CMT) and flux core arc welds (FCAW). The ultrasonic imaging results were analyzed using beam propagation amplitudes and homogeneity, which in turn were used to relate the different microstructure regions of the FCAW and CMT welded samples. With this study, we were able to identify highly susceptible microstructures in the weld that could potentially promote creep type failures.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Argon broad ion beam sectioning and high resolution scanning electron microscopy imaging of hydrated alite

Highlights: • The native fibrous outer and dense inner C-S-H structure are preserved by using low energy argon broad ion beam sectioning. • Possible artefacts of the preparation and imaging of hydrated alite are shown and discussed. • An approach for a semi automated pore analysis of the obtained high resolution images is demonstrated. Scanning electron microscopy (SEM) imaging is able to visualize micro- to nano-structures of cement and concrete. A prerequisite is that the sample preparation preserves the native structure of the specimen. In this study, argon broad ion beam (BIB) sectioning is compared to state-of-the-art sample preparation (resin embedding, polishing) for hydrated alite. Additionally, it is investigated if during BIB, sample cooling is beneficial to avoid deterioration of cement hydrates. The aim is to quantitatively measure pore size distributions in hardened alite pastes. Therefore, not only optimized sample preparation but also optimized imaging conditions are investigated. Finally, it is demonstrated that by image analysis pores down to a diameter of 5 nm in hydrated alite pastes can be quantitatively analysed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Zero-Power Analog Optical Processing

The motivation behind this research is the growing challenge of handling the massive amounts of data generated by modern imaging systems. Conventional digital image processing techniques are struggling to keep pace with the demands of high-resolution and high-speed imaging systems for remote sensing due to their high-power consumption and data storage requirements. We present a novel approach based on analog photonics to address this challenge. The proposed system utilizes a silicon-photonics-based image encoder positioned after image formation and initial optical-to-electrical conversion. The photonic encoder compresses image data using a passive disordered photonic structure to perform kernel-type random projections of the raw data. The compressed data is then processed by a back-end neural network, which reconstructs the original image with high fidelity (structural similarity exceeding 90%). Our proposed approach has the potential to compress images with ~ 1000X lower power consumption compared to digital approaches with data rates exceeding 1 terapixel/second.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Wide Dynamic Range, 10 kHz Framing Detector for 4D-STEM

Hybrid pixel array detectors (PADs) have expanded the fidelity, frame rate and dynamic range for diffractive imaging in electron microscopes. With their high detective quantum efficiencies (DQE), the noise performance limited is by counting statistics. Consequently, improving the precision and quality of high-speed images requires increasing the linear dynamic range and the maximum usable beam current. Here we describe a new prototype hybrid PAD, our next-generation electron microscope pixel array detector (NG-EMPAD) that expands both the framing speed and dynamic range of our earlier EMPAD design. Like the EMPAD, electrons are detected directly in a 500 μm thick silicon sensor bonded pixel-by-pixel to a custom signal processing integrated circuit (IC). Each pixel in the IC integrates charge carriers produced by the high-energy incident electrons. Here, in-pixel circuitry uses a combination of techniques to extend the dynamic range, including adaptive gain switching and the quantitative excess charge dumping similar to the EMPAD. In-pixel buffering of signals during readout allows acquiring a new image while reading out the previously collected image, yielding an image collection duty cycle of nearly 100%.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Global Multimodal Dataset for Nighttime Light Super-Resolution

The dataset is a collection of spatially and temporally registered high-resolution and low-resolution nighttime light (NTL) images, high-resolution land-use binary masks, and high-resolution road density images from around the world. The NTL images are sourced from the NASA Black Marble product VNP46A2 and the LuoJia1-01 satellite. The land-use binary masks are derived from Google's and the World Resources Institute's DynamicWorld dataset, and the road density images are sourced from OpenStreetMap.

Nighttime lights↗