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At least 685 records · Page 38

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

Electrical Capacitance Volume Tomography with High-Contrast Dielectrics

The Electrical Capacitance Volume Tomography (ECVT) system has been designed to complement the tools created to sense the presence of water in nonconductive spacecraft materials, by helping to not only find the approximate location of moisture but also its quantity and depth. The ECVT system has been created for use with a new image reconstruction algorithm capable of imaging high-contrast dielectric distributions. Rather than relying solely on mutual capacitance readings as is done in traditional electrical capacitance tomography applications, this method reconstructs high-resolution images using only the self-capacitance measurements. The image reconstruction method assumes that the material under inspection consists of a binary dielectric distribution, with either a high relative dielectric value representing the water or a low dielectric value for the background material. By constraining the unknown dielectric material to one of two values, the inverse math problem that must be solved to generate the image is no longer ill-determined. The image resolution becomes limited only by the accuracy and resolution of the measurement circuitry. Images were reconstructed using this method with both synthetic and real data acquired using an aluminum structure inserted at different positions within the sensing region. The cuboid geometry of the system has two parallel planes of 16 conductors arranged in a 4 4 pattern. The electrode geometry consists of parallel planes of copper conductors, connected through custom-built switch electronics, to a commercially available capacitance to digital converter. The figure shows two 4 4 arrays of electrodes milled from square sections of copper-clad circuit-board material and mounted on two pieces of glass-filled plastic backing, which were cut to approximately square shapes, 10 cm on a side. Each electrode is placed on 2.0-cm centers. The parallel arrays were mounted with the electrode arrays approximately 3 cm apart. The open ends were surrounded by a metal guard to reduce the sensitivity of the electrodes to outside interference and to help maintain the spacing between the arrays. Other uses for this innovation potentially include quantifying the amount of commodity remaining in the fuel and oxidizer tanks while on-orbit without having to fire spacecraft engines. Another orbit application is moisture sensing in plant-growth experiments because microgravity causes moisture in soil to distribute itself in unusual ways. At the moment, the hardware and image reconstruction technique may only be of interest to people involved in nondestructive evaluation. The reconstructed image takes almost a full week to reproduce with existing computer power. However, because computer power and speeds follows Moore s Law, execution times are likely to become acceptable within the next five to eight years. The code was written in Mathematica for dedicated use with the ECVT system. In its present form, it is not suitable to be used directly as a consumer product. However, the code could be likely improved by rewriting it in a compiled language such as C or Fortran.

Nurge, Mark↗

Enhanced Imaging of Corrosion in Aircraft Structures with Reverse Geometry X-ray(registered tm)

The application of Reverse Geometry X-ray to the detection and characterization of corrosion in aircraft structures is presented. Reverse Geometry X-ray is a unique system that utilizes an electronically scanned x-ray source and a discrete detector for real time radiographic imaging of a structure. The scanned source system has several advantages when compared to conventional radiography. First, the discrete x-ray detector can be miniaturized and easily positioned inside a complex structure (such as an aircraft wing) enabling images of each surface of the structure to be obtained separately. Second, using a measurement configuration with multiple detectors enables the simultaneous acquisition of data from several different perspectives without moving the structure or the measurement system. This provides a means for locating the position of flaws and enhances separation of features at the surface from features inside the structure. Data is presented on aircraft specimens with corrosion in the lap joint. Advanced laminographic imaging techniques utilizing data from multiple detectors are demonstrated to be capable of separating surface features from corrosion in the lap joint and locating the corrosion in multilayer structures. Results of this technique are compared to computed tomography cross sections obtained from a microfocus x-ray tomography system. A method is presented for calibration of the detectors of the Reverse Geometry X-ray system to enable quantification of the corrosion to within 2%.

Winfree, William P.↗

Damage evolution and ductile fracture of commercially-pure titanium sheets subjected to simple tension and cyclic bending under tension

This paper describes a study into the evolution of damage in commercial-purity titanium (CP–Ti) sheets subjected to cyclic bending under tension (CBT) and uniaxial tension (simple tension, ST). Sections were taken from sheets that were strained to various levels under both methods and were imaged using X-ray computed tomography (XCT) to reveal insights into the size, density, and distribution of microvoids in the sheets. Digital image correlation (DIC) was also used to observe the surface strain of CBT and ST sheets during testing. These results showed that elongation to failure (ETF) for CBT deformation is about 2.5× higher than for ST, local longitudinal strains in the bulk of the CBT sample are around 1.3× higher than the peak strain in the ST necked region, and 1.7× higher in the localized region of CBT failure. It was found that the volume-density of voids in both sheets followed a similar exponential increase with strain, reaching nearly 45× higher in the CBT than the ST sheets before the onset of failure, mainly due to the higher strain levels achieved. A higher volume density of voids developed in the center of sheets at high levels of strain, for both processes, with the density in the sheet center becoming approximately double that found near the edges. Scanning electron microscopy (SEM) was used to examine the fracture surface of CBT and ST sheets after failure. The observations are presented and discussed highlighting the CBT process as effective to delay ductile fracture of the CP-Ti sheets.

Commercially pure titanium↗

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Macrohomogeneous battery models are widely used to predict battery performance, necessarily relying on effective electrode properties, such as specific surface area, tortuosity, and electrical conductivity. While these properties are typically estimated using ideal effective medium theories, in practice they exhibit highly non-ideal behaviors arising from their complex mesostructures. In this paper, we computationally reconstruct electrodes from X-ray computed tomography of 16 nickel–manganese–cobalt-oxide electrodes, manufactured using various material recipes and calendering pressures. Due to imaging limitations, a synthetic conductive binder domain (CBD) consisting of binder and conductive carbon is added to the reconstructions using a binder bridge algorithm. Reconstructed particle surface areas are significantly smaller than standard approximations predicted, as the majority of the particle surface area is covered by CBD, affecting electrochemical reaction availability. Finite element effective property simulations are performed on 320 large electrode subdomains to analyze trends and heterogeneity across the electrodes. Significant anisotropy of up to 27% in tortuosity and 47% in effective conductivity is observed. Electrical conductivity increases up to 7.5× with particle lithiation. We compare the results to traditional Bruggeman approximations and offer improved alternatives for use in cell-scale modeling, with Bruggeman exponents ranging from 1.62 to 1.72 rather than the theoretical value of 1.5. We also conclude that the CBD phase alone, rather than the entire solid phase, should be used to estimate effective electronic conductivity. This study provides insight into mesoscale transport phenomena and results in improved effective property approximations founded on realistic, image-based morphologies.

25 ENERGY STORAGE↗

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗

Evaluation of a positron-emission-tomography-based SiPM readout for compact segmented neutron imagers

Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z shielding without losing significant energy. Furthermore, fast neutrons provide a clear and unambiguous signature of the presence of SNM with few competing natural background sources. The challenge of detecting fast neutrons is twofold. First, the neutron flux from SNM are only a fraction of the corresponding gamma-ray flux. Second, fast neutrons can be difficult to differentiate from gamma rays. The ability to discriminate gamma rays from neutrons, combined with a neutron imaging capability, can in some situations enable the localization of SNM neutron sources distinct from background. With the developments of pulse-shape-sensitive plastic scintillators that offer excellent gamma-ray/neutron discrimination, and arrays of silicon photomultipliers combined with highly scalable and fast positron-emission-tomography (PET) multi-channel readout systems, field-deployable neutron imagers suitable for SNM detection might now be within reach. In this paper, we present a characterization of the performance of a recently available commercial PET-scanner readout, including its sensitivity to pulse-shape differences between fast neutrons and gamma rays, energy and timing resolution. Here, we find that, while the pulse-shape discrimination is achievable with stilbene, further improvement of the readout is required to achieve it with the PSD-capable available plastic scintillators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Third Dimension of Ferroelectric Domain Walls

Abstract Ferroelectric domain walls are quasi‐2D systems that show great promise for the development of nonvolatile memory, memristor technology, and electronic components with ultrasmall feature size. Electric fields, for example, can change the domain wall orientation relative to the spontaneous polarization and switch between resistive and conductive states, controlling the electrical current. Being embedded in a 3D material, however, the domain walls are not perfectly flat and can form networks, which leads to complex physical structures. In this work, the importance of the nanoscale structure for the emergent transport properties is demonstrated, studying electronic conduction in the 3D network of neutral and charged domain walls in ErMnO 3 . By combining tomographic microscopy techniques and finite element modeling, the contribution of domain walls within the bulk is clarified and the significance of curvature effects for the local conduction is shown down to the nanoscale. The findings provide insights into the propagation of electrical currents in domain wall networks, reveal additional degrees of freedom for their control, and provide quantitative guidelines for the design of domain‐wall‐based technology.

36 MATERIALS SCIENCE↗

Low-dose high-resolution $\mathrm{TOF}$-$\mathrm{PET}$ using ionization-activated multi-state low-$\mathrm{Z}$ detector media

We propose PET scanners using low atomic number media that undergo a persistent local change of state along the paths of the Compton recoil electrons. Measurement of the individual scattering locations and angles, deposited energies, and recoil electron directions allows using the kinematical constraints of the 2-body Compton scattering process to perform a statistical time-ordering of the scatterings, with a high probability of precisely identifying where the gamma first interacted in the detector. In these cases the Line-of-Response is measured with high resolution, determined by the underlying physics processes and not the detector segmentation. There are multiple such media that act through different mechanisms. As an example in which the change of state is quantum-mechanical through a change in molecular configuration, rather than thermodynamic, as in a bubble chamber, we present simulations of a two-state photoswitchable organic dye, a ‘Switchillator’, that is activated to a fluorescent-capable state by the ionization of the recoil electrons. The activated state is persistent, and can be optically excited multiple times to image individual activated molecules. Energy resolution is provided by counting the activated molecules. Location along the LOR is implemented by large-area time-of-flight MCP-PMT photodetectors with single photon time resolution in the tens of ps and sub-mm spatial resolution. Simulations indicate a large reduction of dose.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC)

METRIC is a robotic science laboratory that can determine the mineralogy, elemental chemistry, micromorphology, and thermophysical properties of planetary regolith. The METRIC suite comprises METRIC XRD/F, an X-ray diffraction/X-ray fluorescence instrument that can determine the mineralogy and elemental chemistry of regolith samples; METRIC XCT, a micro X-ray computed tomography instrument that can be used to evaluate grain/crystallite sizes and textures; METRIC IRS, an imaging spectrometer mounted on a rover that can determine mineralogy and thermophysical properties at the landing site; and a pneumatic sample collection, processing, distribution system developed by Honeybee Robotics. The payload elements could be deployed on a static lander or a rover. Data returned from the METRIC payload would inform origin, formation, and evolution of rocky planetary bodies. METRIC XRD/F draws on heritage from the CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover [1], with a few important improvements. Like CheMin, METRIC XRD/F operates in transmission geometry and uses piezoelectric actuators on sample cells in a tuning fork geometry to induce convective grain motion of the regolith to create a randomly oriented powder. MSL CheMin uses an energy-sensitive CCD to collect XRD patterns and XRF spectra simultaneously from the same sample cell, resulting in qualitative XRF data. METRIC XRD/F uses two different sample cells, one optimized for XRD and one optimized for XRF, and a silicon drift detector to detect fluoresced X-rays. This improvement to the XRF capabilities provides quantitative geochemical data of major elements down to Z = 11 and allows for the detection of minor and trace elements that are critical for evaluating geologic evolution of the Moon (e.g., P and Th). Modest improvements to the XRD geometry and hardware allow for better angular resolution and the ability to distinguish between members of the pyroxene group. METRIC XCT uses the same geometry and much of the same hardware as METRIC XRD/F, where a CCD would capture images of a regolith sample in a 3 mm diameter sample tube that is rotated 360° in steps <1°. Image brightness can be used to infer compositional data, where brighter materials indicate a higher Z, much like scanning electron microscopy. Data from METRIC XCT complement those from METRIC XRD/F. Particle size, shape, and texture can provide petrologic and provenance information, whereas vesicle size and morphology in volcanic or impact melt lithologies can inform cooling rates. METRIC IRS is a hyperspectral thermal imager that can be mounted to a lander or rover to provide mineralogical data from the broader landing site and help determine whether the samples analyzed by METRIC XRD/F and XCT are representative. The METRIC IRS spectral range (8–14 μm) and resolution (10.8 cm-1) allow for quantitative mineralogy from modelling Reststrahlen bands of major rock-forming minerals (e.g., silicates, phosphates). Radiance cubes can be processed and modelled with an onboard high-performance computer to determine mineral abundances of plagioclase, high-Ca pyroxene, pigeonite, orthopyroxene, olivine, and glass. Regolith samples can be acquired, processed, and delivered to the X-ray instruments via multiple sample handling systems, but the pneumatic sampling systems developed by Honeybee Robotics [e.g., 2] are best suited for relatively low-cost missions that are being competed for the Moon (e.g., NASA’s Payloads and Research Investigations for the Surface of the Moon program). There are pneumatic sampling systems that collect surface material and other systems that pneumatically drill up to ~1 m below the surface, providing material that has not been space weathered and has not been affected by the lander’s exhaust. [1] Blake, D. F., Vaniman, D., Achilles, C., Anderson, R., Bish, D., et al. (2012). Space Sci. Rev. 170, 341-478. https://doi.org/10.1007/s11214-012-9905-1. [2] Zacny, K., Betts, B., Hedlund, M., Long, P., Gramlich, M., Tura, K., Chu, P., Jacob, A., Garcia, A. (2014). IEEE Aerospace Conference, 3-7 March 2014, Big Sky, MT, U.S.A.

X-ray diffraction↗

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗

First Examination of Irradiated Fuel with Pulsed Neutrons at LANSCE (Preliminary Results)

We present preliminary results on the characterization of an irradiated U-lOZr-lPd fuel sample that was prepared from the irradiated AFC-3A-R5A sample. U-lOZr metallic fuels are researched as host materials for potential transmutation fuels and the addition of palladium strives to bind lanthanides, thus preventing fuel-cladding chemical interactions (FCCI). These interactions limit the lifetime of metallic fuels and are caused by migration of lanthanide fission products to the periphery of the fuel slug, where they start to interact with the D9 or HT9 steel cladding, ultimately leading to failure of the mechanical integrity of the cladding. Neutrons offer bulk characterization of irradiated materials for which X-ray tomography methods are not suitable due to the immense gamma background emitted from the samples. In particular pulsed neutrons provide information from the ability to resolve the neutron energy using their time-of-flight and thus the potential to utilize neutron absorption resonance to characterize the spatial distribution of isotopes. This, in turn, may allow to characterize the distribution of fission and neutron capture products non-destructively and may ultimately be applied to the bulk of an irradiation capsule prior to destructive post-irradiation examination to identify regions of interest. To allow the characterization of entire irradiation capsules, a cask is under development in the advanced post-irradiation work package at LANL and progress on this development was reported elsewhere. In parallel, an irradiated U-lOZr-lPd sample cut from the AFC-3AR5A irradiation was shipped to LANL and will be fully characterized with an NSUF funded rapid turnaround experiment (RTE) in the 2020 LANSCE run cycle. The sample emits at a dose rate of ~3R/hr on contact and is therefore manageable with remote handling, without requiring a cask. The disk-shaped material is larger than samples prepared for analysis using electron or X-ray methods and is therefore an intermediate step towards characterization of bulk samples at LANSCE. However, since it covers the full diameter of the irradiated fuel slug, some insight on redistribution of elements, spatially resolved information on microstructure, e.g. phase composition and texture, will be possible using the pulsed neutron-based methods developed for fuel characterization at LANSCE. This report describes the development of procedures to handle the sample at LANSCE as well as preliminary data and results from tests conducted in December 2019 on the energy-resolved neutron imaging (ERNI) beam line at flight path 5 and the high pressure-preferred orientation diffractometer (HIPPO) at LANSCE. This effort is a collaboration between LANL, INL, and ORNL. To compare our capabilities with prior work, we present an overview of previously reported bulk characterization of irradiated or spent fuels. The overview addresses neutron diffraction and neutron absorption resonance spectroscopy, both of which have only few reported applications on irradiated or spent nuclear fuel, as well as neutron radiography. This literature review was already described in a previous report but is repeated here to put our current efforts in context of previous work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

XRF Characterization of MMOD Impact Damage

Introduction The Hypervelocity Impact Technology (HVIT) Group at the NASA Johnson Space Center (JSC) has performed over 150 post flight MMOD inspections on returned space-ex-posed hardware and collected over 1,600 samples. Determination of the impactor source typically requires an analysis of the projectile residue in the damage feature. At this time, about 20% of the samples have been processed. Types of Samples Samples in the HVIT group collection can be classified into two types. Indirect (non-destructive) samples are produced when a pliable material (e.g., adhesive tape or dental mold) is inserted into an impact feature. With this type of sampling technique, crater material and (hopefully) projectile residue material is embedded in the sample media and can detected using further chemical characterizing techniques. Direct (destructive) sampling involves the in-tact extraction of material from the spacecraft and is done in a manner that the entire impact feature can be excised intact. This technique provides the greatest chance of successfully determining impactor source due to the entirety of the projectile remnants being present within the collected sample. Updated Projectile Residue Detection Techniques Previous assessments of projectile provenance have involved the use of samples that are first mounted in epoxy, sectioned to expose the crater interior, imaged with a scanning electron microscope (SEM), then any observed impactor residue was then analyzed using an energy dispersive spectrometer (EDS). This technique, while proven, may be supplemented with other types of elemental analysis techniques that can observe major element chemistry, in order to improve throughput of sample analysis. The Astromaterials Research and Exploration Science (ARES) Division at JSC, for example, operates a Bruker M4 Tornado micro-X-Ray fluorescence (XRF) spectrometer, capable of creating elemental maps of areas around these small impact features in a couple of hours, with a spot size <20 μm. The potential advantage with this technique lies in sample preparation, as no polishing or conductive coatings are needed. Early trials attempted to deter-mine impactor composition by collecting spectra from intact samples by aiming the X-Rays directly into the impact feature, but the signal:noise ratio was too low for confident material identification. Sample preparation for XRF then relies on sectioning the samples parallel to the impactor trajectory in order to expose the largest area of subsurface damage possible, thus maximizing the signal from any small impactor remnants. Complementary to the use of XRF for sample analysis, ARES also houses a Nikon XTH 320 micro-X-Ray computed tomography (XCT). This instrument can be used to create 3D visualizations of impact damage for the determination of crater volumes and dimensions, as well as for the determination of the best place to section each sample for the subsequent XRF analysis.

J L Hyde↗

NIRDye 812: A molecular platform tailored for multimodal bioimaging applications of targeted fluorescence- and photoacoustic-guided surgery

The primary treatment for malignant tumors remains to be surgical removal of the diseased tissue. The presence or absence of residual diseased tissue at the tumor margin is the strongest predictor of postoperative prognosis and recurrence. Accordingly, reliance on the ability of surgeons to visually distinguish diseased tissue from healthy tissue unambiguously in real time is crucial. Near infrared-I (NIRsingle bondI) fluorescence-emitting targeting biomolecular constructs such as anticancer antibody-fluorophore conjugates, namely cetuximab-IRDye® 800CW (CTB-IRDye® 800CW), are FDA-approved for clinical trial usage in the fluorescence-guided resection of diseased tissue due to affording improved direct visualization of tumor tissue when compared to the use of either the unaided eye under standard white light illumination (WLI) surgical techniques or non-targeting fluorophores. Unfortunately, though helpful, CTB-IRDye® 800CW affords limited (i) identification of diseased tissue and (ii) tumor margin delineation, because the immunoconjugate generates suboptimal tumor-to-background ratios (TBRs) as a result of its spectral/photophysical profiles poorly aligning with the fixed optical windows of pre-/clinical setups. As such, CTB-IRDye® 800CW is more prone to affording incomplete resection compared to if TBRs were higher due to otherwise. Here, to aid in accurately identifying deep-seated diseased tissue, photoacoustic (PA) tomography has been implemented alongside CTB-IRDye® 800CW to achieve PA signals that could result in higher TBRs. However, in clinical trial practice, using IRDye® 800CW for PA imaging also yields subpar TBRs due to it affording low PA signals. To overcome such limitations, we developed NIRDye 812, a structurally-modified topological equivalent of IRDye® 800CW, to confer it the capability to yield both higher TBRs and superior PA signal than that of the equivalent CTB-conjugate and fluorophore IRDye® 800CW itself, respectively. To do so, we substituted the oxygen atom at its meso-position with a sulfur atom. CTB-NIRDye 812 demonstrated a red-shifted absorption wavelength at 796 nm and a peak NIR-I fluorescence emission wavelength at 820 nm, which better dovetails with the fixed windows of preinstalled fixed emission filters within commercial pre-/clinical NIR-I fluorescence imaging instruments. Overall, CTB-NIRDye 812 provided a ~ 2-fold increase in TBRs compared to those of CTB-IRDye® 800CW in vivo. Also, NIRDye 812 displayed an ~60% higher PA signal than that of IRDye® 800CW. Collectively, we achieved our goal of improving upon the spectral/photophysical and PA properties of IRDye® 800CW via introducing a subtle modification to its electronic core such that its CTB immunoconjugate could potentially allow for fast track or breakthrough designation by the FDA due to its near-identical structure displaying considerably improved efficacy.

59 BASIC BIOLOGICAL SCIENCES↗

First experimental study of multiple orientation muon tomography, with image optimization in sparse data environments

Due to the high penetrating power of cosmic ray muons, they can be used to probe very thick and dense objects. As charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object, particle direction changes can be used to extract scattering information within an object. This can be used to produce a scattering intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies have been published with multi-orientation tomography, which can form a three-dimensional representation faster than a single orientation view. In this work we present the first experimental multiple orientation muon tomography study. Experimental muon-scatter based tomography was performed using a concrete filled steel drum with several different metal wedges inside, between detector planes. Data was collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were then combined using two different tomographic methods. Results showed that using a combination of multiple depth-of-field reconstructions, rather than a traditional inverse Radon transform approach used for CT, resulted in more useful images for sparser data. As cosmic ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedge compositions.

Applied Physics (physics.app-ph)↗

Second Annual Progress Report on Correlation Between Microstructure and Mechanical Properties of Neutron-Irradiated Ferritic-Martensitic and Austenitic Steels

Ferritic-martensitic steels G92-2b (an optimized Grade 92 heat), NF616 and T91, and austenitic stainless steel 800H and its Grain Boundary Engineering (GBE)-treated version 800H-TMP (ThermoMechanical Processing) were irradiated in the High Flux Isotope Reactor (HFIR) of Oak Ridge National Laboratory (ORNL) and the Advanced Test Reactor (ATR) of Idaho National Laboratory (INL). Selected G92-2b samples were irradiated up to 14.66 dpa in the HFIR at two temperature ranges: 400–496.7°C and 683.3– 720°C. NF616 and T91 were irradiated in the ATR up to 8.16 dpa with the irradiation temperatures ranged from 241°C to 447.5°C. Alloy 800H and 800H-TMP samples were irradiated in both the HFIR and the ATR. Selected 800H and 800H-TMP samples had HFIR irradiation to 1.28 dpa at 580°C and ATR irradiation up to 9.12 dpa at 359°C to 431°C. Vickers hardness measurements, fractography, and microstructural characterization were performed on the selected samples in the Low Activation Materials Design and Analysis (LAMDA) laboratory. Radiation-hardening of G92-2b was observed at the lower doses and lower irradiation temperatures (400- 496.7°C), with GB03 (0.52 dpa at 400°C) and GB04 (7.44 dpa at ~490°C) showing ~12% and ~8% hardening, respectively. Softening by ~14% was observed for GB05 (14.66 dpa at 496.7°C). Radiationsoftening of G92-2b was more prevalent at the higher irradiation temperatures (683.3-~720°C), with GB10 (0.46 dpa at 683.3°C), GB11 (7.44 dpa at ~720°C), and GB12 (14.63 dpa at ~720°C) showing ~8%, ~8%, and ~40% softening, respectively. Radiation-hardening of NF616 and T91 was observed with the hardness increased by ~37% to ~65% depending on the irradiation doses and irradiation temperatures. Within the studied irradiation conditions of NF616 and T91, samples with a higher dose had a larger hardness after irradiation. All the tested alloy 800H and 800H-TMP samples in this work showed radiation-hardening by ~96±7% to ~152±10%. Alloy 800H-TMP tended to have slightly smaller radiation-hardening than alloy 800H. The fractography results of G92-2b sample GB03, GB10, and GB11, together with the previously characterized fractography of GB04, GB05, and GB12, indicated that the ductility of G92-2b was maintained up to 14.66 dpa at the lower irradiation temperatures of 400-496.7°C, while some loss of ductility (less necking) was observed for higher doses at the higher irradiation temperatures of 683.3-720°C. This agrees with the previously reported tensile test results of G92-2b, where the elongation of G92-2b was reduced at higher doses at the higher irradiation temperatures. Dimple sizes increased at higher doses, which are more evident at the higher irradiation temperatures of 683.3-~720°C. The fractography of NF616 sample D2 (2.96 dpa at 291.5°C), D4 (5.91 dpa at 359°C), and D6 (8.16 dpa at 431°C) indicated loss of ductility with negligible necking for sample D2, while ductile failure for samples D4 and D6. Fractography of alloy 800H and 800H-TMP samples in various irradiation conditions showed ductile failure with obvious necking. Dimples were observed, with some of them containing large Ti-rich particles, in all the 800H/800H-TMP samples. Electron backscatter diffraction characterization of GB12 indicated the recovery of the lath structure, which was generally replaced by an equiaxed grain structure. Transmission electron microscopy (TEM) characterization showed the presence of frequent M 23 C 6 (M = primarily Cr), MX (M = primarily V), spherical Nb(C,N) precipitates, and occasional Laves phase precipitates in the G92-2b samples. MX precipitates with sizes of 20-30 nm were observed at boundaries of smaller grains, indicating the pinning effect of the V-rich precipitates. The lath structure recovery was more evident at the higher irradiation temperatures (683.3-~720°C), with decreased densities of line dislocations and M23C6 precipitates. The irradiated T91 (TA04) showed the growth of M23C6 precipitates to 101 ± 40 nm from the initial 68 ± 22 nm in the unirradiated condition. Dislocation loops of both {100} and {111} types were present in TA04. TEM characterization was also performed on the irradiated 800H (N4, N5, N6, and AR2) and 800H-TMP (P4, P5, P6, and HG1). Accumulation of M 23 C 6 precipitates at grain boundaries was observed in all the xii 800H/800H-TMP samples, and the presence of Ti(C,N) precipitates at grain boundaries and in the matrix was observed in the irradiated 800H-TMP. Some Ti(C,N) precipitates are embedded in the M 23 C 6 precipitates, maintaining specific orientation relationships between the precipitates and between the precipitate and matrix. In addition, nanoscale Si-rich clusters were observed in the matrix of all the 800H/800H-TMP samples, with EDS Si maps tending to have a lower contrast in 800H-TMP samples. Atom probe tomography was conducted on the same samples, supported by a Rapid Turnaround Examination project under Nuclear Science User Facilities. The results are being analyzed to be integrated with the TEM results for a confident description of the γ’ precipitates. Dislocation loops also formed in all the 800H/800H-TMP samples. The density and the average size of dislocation loops were quantified to be in the order of 10 22 – 10 23 m -3 and 11.7 – 15.9 nm, respectively, in the ATR-irradiated 800H/800H-TMP samples. The loop densities in irradiated 800H were higher than that in irradiated 800H-TMP under the same irradiation conditions. Further systematic data analyses, together with some complementary experiments, will be pursued for these samples to foster peer-reviewed journal article publications.

36 MATERIALS SCIENCE↗