Energy Resolved Neutron Imaging @ LANSCE: A Non-Destructive Tool for Interrogating Materials in Next Generation Nuclear Reactor Designs
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One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.
The majority of surface particles were found to be < 5 microns in diameter with increasing numbers close to the optical resolution limit of 0.3 microns. Acceleration grid EDS results show that the majority of materials appear to be from the SRC shell and SLA materials which include carbon-carbon fibers and Si-rich microspheres in a possible silicone binder. Other major debris material from the SRC included white paint, kapton, collector array fragments, and Al. Image analysis also revealed that SRC materials were also found mixed with the Utah mud and salt deposits. The EDS analysis of the acceleration grid showed that particles < 1 m where generally carbon based particles. Chemical cleaning techniques with Xylene and HF in an ultrasonic bath are currently being investigated for removal of small particles by the Genesis science team as well as ultra-pure water megasonic cleaning by the JSC team [4]. Removal of organic contamination from target materials is also being investigated by the science team with the use of UV-ozone cleaning devices at JSC and Open University [5]. In preparation for solar wind oxygen analyses at UCLA and Open University [1, 2], surface particle contamination on three Genesis concentrator targets was closely examined to evaluate cleaning strategies. Two silicon carbide (Genesis sample # 60001 and 60003) and one chemical vapor deposited (CVD) 13C concentrator target (60002) were imaged and mosaic mapped with optical microscopes. The resulting full target mosaic images and particle feature maps were subsequently compared with non-flight, but flight-like, concentrator targets and sample return capsule (SRC) materials. Contamination found on the flown concentrator acceleration grid was further examined using a scanning electron microscope (SEM). Energy dispersive X-ray spectroscopy (EDS) for particle identification was subsequently compared with the optical images from the flown targets. Figure 1 show that all three targets imaged in this report are fully intact and do not show any signs of material fractures. However, previous ellipsometry results and overview imaging of both flown SiC targets show a solar wind irradiation gradient from the center focal point to the outer edge [3]. In addition, due to the hard landing, each target has experienced varying degrees of impacts, scratches, and particle debris from the spacecraft and Utah impact site.
A near real-time, full parallax holographic display system was developed that has the potential to provide a 3-D display for remote handling operations in hazardous environments. The major components of the system consist of a stack of three spatial light modulators which serves as the object source of the hologram; a near real-time holographic recording material (such as thermoplastic and photopolymer); and an optical system for relaying SLM images to the holographic recording material and to the observer for viewing.
The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory (LANL) is a critical facility used for nuclear weapons research and development (Los Alamos National Laboratory). Its primary function is to provide high-resolution, real-time images of the behavior of materials under extreme conditions, specifically during the hydrodynamic testing of nuclear weapons surrogates. The facility uses advanced radiographic techniques, such as dual-axis X-ray imaging, to capture detailed snapshots of these materials as they react to high-pressure environments. DARHT plays a key role in maintaining the safety, security, and reliability of the U.S. nuclear arsenal, supporting the Stockpile Stewardship Program. The facility helps ensure that nuclear weapons perform as designed without the need for nuclear tests. Its dual-axis radiography provides more precise data than traditional single-axis imaging, offering a comprehensive view of the internal dynamics of a weapon's primary stage.
The pre-main sequence star V536 Aql, classified as a K7 classical T Tauri star by Cohen & Kuhi has been resolved, by high angular resolution near-infrared speckle observations, as a close binary (0.52 sec separation at 17 deg) surrounded by extended structures. These structures seen, both in the July 1993 and April 1994 observations, are not at the same position in the reconstructed image and do not present exactly the same shape at both times. Although it is unlikely that the presence of these structures is due to seeing calibration problems, the exact shape might be affected by it. We cannot presently make a final interpretation of the observations but can formulate different possibilities: the 'circumstellar' material seen in our images can be an independent cloud, or simply gas or dust, in front of the system on our line of sight, but close enough to still be illuminated by the binary; this material may be 'by chance' there or be a remnant of the material in which the star was born. We propose a model to explain the position variation of the extended structures. New observations are under reduction and should help to determine the exact value of this motion. At their distance from the star, motions of the extended matter would correspond to velocities much higher than the Kepler velocities. To explain this, we have developed a model based on a 'torch-light' effect. The possibility that the observed elongated structures belong to a circumstellar or circumbinary disk are discussed.
This paper presents a high-fidelity multiscale framework to simulate the mechanical behavior of ceramic matrix composites (CMCs), accounting for the complex micromorphology captured using detailed material characterization. First, high-resolution micrographs are obtained for the specific carbon fiber silicon-carbide-nitride matrix (C/SiNC) CMC to characterize the variability of the architectural features and manufacturing-induced defects at the microscale. An image processing algorithm is then used to precisely estimate the size and distribution of all subscale features and defects from the micrographs. The information is then used to generate a three-dimensional stochastic representative volume element (SRVE) to reconstruct microscale constituents accounting for the variability. As a result, the generated SRVEs are simulated using the high-fidelity generalized method of cells (HFGMC) micromechanics theory to investigate the effects of defects on the elastic properties of C/SiNC CMCs.
PROJECT 1: Address critical problems in materials science and simultaneously advance the state-of-the-art in multiscale and multimode characterization using the combined advanced analytical capabilities and expertise of Colorado School of Mines (CSM) and the National Renewable Energy Laboratory (NREL). The primary effort of the Phase I of this CRADA is to establish the International Center for Multiscale Characterization using shared resources at both NREL and CSM. Phase II will focus on capability development and marketing, choosing candidate materials science issues in the areas of structure imaging, chemical composition mapping, and correlating properties and performance of materials for impact in energy-related, environmental and critical materials areas. The CRADA will be modified to include specific topics of concern in materials science to industry member partners. Advanced analytical capabilities and expertise at CSM and NREL will be used to advance materials understanding and performance through characterization of multiscale phenomena including structural imaging, chemical composition mapping, and other techniques correlating properties and performance of materials. PROJECT 2: As part of the International Center for Materials Characterization, work under Modification #1 will be led by Colorado School of Mines (CSM), working in collaboration with NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments. The purpose of the modification is to provide for NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments, including mentoring and advising the CSM-NREL team on proper Secondary Ion Mass Spectrometry (SIMS) data analysis as needed. SIMS measurements of 10-20 samples will be performed at NREL during the project duration.
With its ability to efficiently probe low-Z materials, X-ray phase imaging methods have recently raised high interest in multiple fields from biology and medical applications to high energy density (HED) physics. Initially developed with synchrotron light and X-ray tubes, we present a novel grating based Talbot X-ray deflectometer (TXD) diagnostic that was coupled with laser-generated K-α X-ray sources. The multi-terawatt laser (I > 1 × 10 14 W cm -2 ) was used as a testbed for diagnostic development. It was found that X-ray source chromaticity plays an important role in TXD. Indeed, the broadband spectrum of laser-generated X-ray sources may strongly impact image quality and thus diagnostic performance. We qualified X-ray emission from different laser-produced sources and determined laser, target, and deflectometer parameters that optimize TXD performance. We present the first results of referenceless grating-based X-ray imaging at high-power laser facilities and discuss the implications of this new development in HED research.
Earth-based radar measurements [1-3] have yielded images of radar-bright material at the poles of Mercury postulated to be near-surface water ice residing in cold traps on the permanently shadowed floors of polar impact craters. The Mercury Laser Altimeter (MLA) on board the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft has now mapped much of the north polar region of Mercury [4] (Fig. 1). Radar-bright zones lie within polar craters or along poleward-facing scarps lying mainly in shadow. Calculations of illumination with respect to solid-body motion [5] show that at least 0.5% of the surface area north of 75deg N lies in permanent shadow, and that most such permanently shadowed regions (PSRs) coincide with radar-bright regions. MLA transmits a 1064-nm-wavelength laser pulse at 8 Hz, timing the leading and trailing edges of the return pulse. MLA can in some cases infer energy and thereby surface reflectance at the laser wavelength from the returned pulses. Surficial exposures of water ice would be optically brighter than the surroundings, but persistent surface water ice would require temperatures over all seasons to remain extremely low (<110 K). Thermal models [6,7] incorporating direct and scattered radiation, Mercury s eccentric orbit, 3:2 spin-orbit resonance, and near-zero obliquity generally do not support such conditions in all permanently shadowed craters but suggest that water ice buried near the surface (<0.5 m depth) could survive for > 1 Gy. We describe measurements of reflectivity derived from MLA pulse returns. These reflectivity data show that surface materials in the shadowed regions are darker than their surroundings, enough to strongly attenuate or extinguish laser returns. Such measurements appear to rule out widespread surface exposures of water ice. We consider explanations for the apparent low reflectivity of these regions involving other types of volatile deposit.
FORTRAN computer algorithm containing various image-processing analysis and enhancement functions developed. Algorithm developed specifically to process images of developmental heat-engine materials obtained with sophisticated nondestructive evaluation instruments. Applications of program include scientific, industrial, and biomedical imaging for studies of flaws in materials, analyses of steel and ores, and pathology.
This paper describes how fusion between thermal and range imaging allows us to discriminate different types of materials in outdoor scenes. First, we analyze how pure vision segmentation algorithms applied to thermal images allow discriminating materials such as rock and sand. Second, we show how combining thermal and range information allows us to better discriminate rocks from sand. Third, as an application, we examine how an autonomous legged robot can use these techniques to explore other planets.
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.
In-situ resource utilization (ISRU) is critical to enable future efforts to have a long-term human presence on the Moon as well as Mars. ISRU technologies are being developed for radiation protection, dust mitigation, thermal insulation, and other applications. One such ISRU technology for creating construction materials out of lunar and Martian regolith is sintering, which is a thermal-based construction process that bonds finely grained material together at temperatures below the melting point. However, the conditions employed during the sintering, such as temperature, atmospheric composition, duration of the process, and pressure, can have a significant impact on the quality and strength of the resulting materials. In parallel, the development of methods for characterizing the quality, porosity, density, and other properties of these materials is critical. X-ray computed tomography (X-ray CT) can image large changes in density within a material, such as the presence of pores throughout an otherwise uniform medium, with relatively high spatial resolution. Similarly, Terahertz time-domain spectroscopic (THz-TDS) imaging is sensitive to density variations within samples, but is restricted to non-conducting materials. Specifically, previous work has shown that the refractive index (n eff ) values obtained through the analysis of THz-TDS images increases with increasing density within plastic samples. Even further, this work showed that it is possible to create a calibration curve for a given material from samples of different, but known density, which can enable one to directly convert n eff to density for samples having the same composition, but unknown density. Here, we report on the fabrication of a lunar simulant-based sintered construction material using vacuum hot pressed (VHP) sintering, then show X-ray CT and THz-TDS imaging results of the sample, which show spatial variations in the material. This has important implications for efforts to improve these types of lunar construction material processes and verify the quality of these materials in terms of consolidation. To the best of our knowledge, there is no previous work utilizing VHP sintering to make lunar simulant-based construction materials or exploring the feasibility of THz imaging to spatially map the density variation through a lunar simulant-based construction material.
Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.
Topics covered include: Device for Measuring Low Flow Speed in a Duct, Measuring Thermal Conductivity of a Small Insulation Sample, Alignment Jig for the Precise Measurement of THz Radiation, Autoignition Chamber for Remote Testing of Pyrotechnic Devices, Microwave Power Combiners for Signals of Arbitrary Amplitude, Synthetic Foveal Imaging Technology, Airborne Antenna System for Minimum-Cycle-Slip GPS Reception, Improved Starting Materials for Back-Illuminated Imagers, Multi-Modulator for Bandwidth-Efficient Communication, Some Improvements in Utilization of Flash Memory Devices, GPS/MEMS IMU/Microprocessor Board for Navigation, T/R Multi-Chip MMIC Modules for 150 GHz, Pneumatic Haptic Interfaces, Device Acquires and Retains Rock or Ice Samples, Cryogenic Feedthrough Test Rig, Improved Assembly for Gas Shielding During Welding or Brazing, Two-Step Plasma Process for Cleaning Indium Bonding Bumps, Tool for Crimping Flexible Circuit Leads, Yb14MnSb11 as a High-Efficiency Thermoelectric Material, Polyimide-Foam/Aerogel Composites for Thermal Insulation, Converting CSV Files to RKSML Files, Service Management Database for DSN Equipment, Chemochromic Hydrogen Leak Detectors, Compatibility of Segments of Thermoelectric Generators, Complementary Barrier Infrared Detector, JPL Greenland Moulin Exploration Probe, Ultra-Lightweight Self-Deployable Nanocomposite Structure for Habitat Applications, and Room-Temperature Ionic Liquids for Electrochemical Capacitors.
Recent advances in lasers and electron optics technology have allowed transmission electron microscopes to achieve high spatial and temporal resolution, making them capable of tracking atoms, charges and spin motions down to the attosecond and nanometre scales. This Primer discusses the most common and practical experimental implementation of time-resolved transmission electron microscopy and the stroboscopic mode for evaluating ultrafast reversible dynamics. An in-depth discussion of photo-induced near-field electron microscopy, a technique unique to laser-assisted electron microscopy, is also provided, covering its prospective applications in the study of coherent phenomena in quantum materials. The experimental strategies and limitations in investigating the structural dynamics of materials and nanostructures by imaging, diffraction and spectroscopy are also described in detail, with a direct comparison with more conventional and established techniques. Here, we provide key information for new researchers who intend to use ultrafast transmission electron microscopy to address new challenges in specific materials science, condensed matter and nanophotonics.