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At least 55 records · Page 3

Deep learning Hamiltonians from disordered image data in quantum materials

The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length- and timescales. Many such materials feature inhomogeneous electronic properties with intricate pattern formation on the observable surface. This rich spatial structure contains information about interactions, dimensionality, and disorder—a spatial encoding of the Hamiltonian driving the pattern formation. Image recognition techniques from machine learning are an excellent tool for interpreting information encoded in the spatial relationships in such images. Here, we develop a deep learning framework for using the rich information available in these spatial correlations in order to discover the underlying Hamiltonian driving the patterns. We first vet the method on a known case, scanning near-field optical microscopy on a thin film of V⁢O 2 . We then apply our trained convolutional neural network architecture to new optical microscope images of a different V⁢O 2 film as it goes through the metal-insulator transition. We find that a two-dimensional Hamiltonian with both interactions and random field disorder is required to explain the intricate, fractal intertwining of metal and insulator domains during the transition. This detailed knowledge about the underlying Hamiltonian paves the way for using the model to control the pattern formation via, e.g., tailored hysteresis protocols. Finally, we also introduce a distribution-based confidence measure on the results of a multilabel classifier, which does not rely on adversarial training. In addition, we propose a machine-learning-based criterion for diagnosing a physical system's proximity to criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Physics-assisted generative adversarial network for X-ray tomography

X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively, with applications in biomedical imaging, materials science, electronic inspection, and other fields. The reconstruction process can be an ill-conditioned inverse problem, requiring regularization to obtain satisfactory results. Recently, deep learning has been adopted for tomographic reconstruction. Unlike iterative algorithms which require a distribution that is known a priori , deep reconstruction networks can learn a prior distribution through sampling the training distributions. In this work, we develop a Physics-assisted Generative Adversarial Network (PGAN), a two-step algorithm for tomographic reconstruction. In contrast to previous efforts, our PGAN utilizes maximum-likelihood estimates derived from the measurements to regularize the reconstruction with both known physics and the learned prior. Compared with methods with less physics assisting in training, PGAN can reduce the photon requirement with limited projection angles to achieve a given error rate. The advantages of using a physics-assisted learned prior in X-ray tomography may further enable low-photon nanoscale imaging.

47 OTHER INSTRUMENTATION↗

A Method of Poisson's Ration Imaging Within a Material Part

The present invention is directed to a method of displaying the Poisson's ratio image of a material part. In the present invention, longitudinal data is produced using a longitudinal wave transducer and shear wave data is produced using a shear wave transducer. The respective data is then used to calculate the Poisson's ratio for the entire material part. The Poisson's ratio approximations are then used to display the data.

Roth, Don J.↗

Parallel high-frequency magnetic sensing with an array of flux transformers and multi-channel optically pumped magnetometer for hand MRI application

Here, we investigate an approach for parallel high-frequency magnetic sensing based on a multi-channel radio frequency (RF) optically pumped magnetometer (OPM) coupled to multiple flux transformers (FTs) with a focus on hand magnetic resonance imaging (MRI) application at ultra-low field (ULF). Multiple RF OPM sensing channels are realized by using a single large-area alkali-metal vapor cell and two laser beams for pumping and probing, shared for all the channels. This design leads to significant cost reduction when multi-channel sensing is desirable, as in the case of ULF MRI. The FT, composed of two connected coils, serves as a transmitter of a target magnetic field to the OPM, while decoupling the OPM from untargeted magnetic fields in the sensing area that can limit the OPM performance. For hand MRI application, theoretical and numerical analysis is performed to determine an optimal geometry for the FT array that could improve signal-to-noise ratio (SNR) and sufficiently reduce crosstalk between FTs. We estimate that the optimized multi-channel FT-OPM sensor can achieve a magnetic field sensitivity of the order of 1 fT / Hz 1 / 2 above 100 kHz, which would be sufficient for 1 mm resolution MRI. In general, the multi-channel capability enables simultaneous magnetic measurements, thus reducing the sensing time and improving the SNR, and we anticipate many applications of the multi-channel FT-OPM sensor beyond the targeted here hand MRI: anatomical parallel ULF MRI of the human brain and other parts of the body, airport security screening, magnetic material imaging, and many others.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis

We present a novel unsupervised machine learning method for quantitative representation of scanning electron micrographs and its applications and performance for nuclear forensic analysis of uranium ore concentrates. The method uses a vector quantizing variational autoencoder followed by a histogram operation to encode a micrograph into a single dimensional representation, called the latent vector. The method requires no extant labeling of the data and can be applied over large datasets of micrographs with minimal human interaction. The representations generated are broadly descriptive of each micrograph and the microstructure of the material imaged. In the case of uranium ore concentrate analysis, the representations were amenable to processing reagent and ore concentrate species classification with accuracy of 81:8%, which is competitive with state-of-the-art supervised networks. The representations were also used to classify previously unseen processing routes, were able to classify imaging parameters such as magnification (to 76:0% accuracy), were able to classify fine grained process parameters such as calcining temperature (to 74:4% accuracy), and their informatic properties indicate that they are generally descriptive of the image represented. This method can be applied across microstructure analysis fields to perform quantitative analysis without the need for labor intensive and possibly biased human analysis.

Scanning Electron Microscopy, Vector Quantizing Va↗

Source of Bright Near-Infrared Luminescence in Gold Nanoclusters

Gold nanoclusters with near-infrared (NIR) photoluminescence (PL) have great potential as sensing and imaging materials in biomedical and bioimaging applications. In this work, Au 21 (S-Adm) 15 and Au 38 S 2 (S-Adm) 20 are used to unravel the underlying mechanisms for the improved quantum yields (QY), large Stokes shifts and long PL lifetimes in gold nanoclusters. Both nanoclusters show decent PL QY. In particular, the Au 38 S 2 (S-Adm) 20 nanocluster shows a bright NIR PL at 900 nm with QY up to 15% in normal solvents (such as toluene) at ambient conditions. The relatively lower QY for Au 21 (S-Adm) 15 (4%) compared to Au 38 S 2 (S-Adm) 20 is attributed to the lowest-lying excited state being symmetry-disallowed, as evidenced by the pressure-dependent anti-spectral shift of the absorption spectra compared to PL. Yet, Au 21 (S-Adm) 15 maintains some emissive properties due to a nearby symmetry-allowed excited state. Furthermore, our results show that suppression of non-radiative decay due to the surface “lock rings” which encircle the Au kernel and the surface “lock atoms” which bridge the fundamental Au-kernel units (e.g., tetrahedra, icosahedra, etc.) is the key to obtain high QYs in gold nanoclusters. Here, the complicated excited-state processes and the small absorption coefficient of the band-edge transition lead to the large Stokes shifts and the long PL lifetimes that are widely observed in gold nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strong Upper-Plate Heterogeneity at the Hikurangi Subduction Margin (North Island, New Zealand) Imaged by Adjoint Tomography

We use earthquake-based adjoint tomography to invert for three-dimensional structure of the North Island, New Zealand, and the adjacent Hikurangi subduction zone. The study area, having a shallow depth to the plate interface below the North Island, offers a rare opportunity for imaging material properties at an active subduction zone using land-based measurements. Starting from an initial model derived using ray tomography, we perform iterative model updates using spectral element and adjoint simulations to fit waveforms with periods ranging from 4–30 s. We perform 28 model updates using an L-BFGS optimization algorithm, improving data fit and introducing P- and S-wave velocity changes of up to ±30%. Resolution analysis using point spread functions show that our measurements are most sensitive to heterogeneities in the upper 30 km. The most striking velocity changes coincide with areas related to the active Hikurangi subduction zone. Lateral velocity structures in the upper 5 km correlate well with New Zealand geology. Here, the inversion reveals increased along-strike heterogeneity on the margin. In Cook Strait we observe a low-velocity zone interpreted as deep sedimentary basins. In the central North Island, low-velocity anomalies are linked to surface geology, and we relate velocity structures at depth to crustal magmatic activity below the Taupō Volcanic Zone.

58 GEOSCIENCES↗

Deciphering the Conflict Between Ion and Electron Percolating Networks in Solid-State Battery Cathodes

High-energy- and power-density solid state batteries require an optimal cathode composition and microstructural arrangement of cathode active material, solid-state electrolyte, conductive carbon, and binder to simultaneously support lithium-ion transport, electron conduction, and storage capacity. The ion and electron conducting phases in solid-state cathodes counteract each other's percolating networks as their mass ratios increase or decrease relative to each other. Here, we investigate targeted mass ratio variations of argyrodite solid electrolyte and two different types of conductive carbon (particles and fibers) in composite LiNi0.8Mn0.1Co0.1O2 (NMC811) solid-state cathodes to ascertain the ionic-electronic tradeoffs in cathode performance. Through ionic and electronic conductivity measurements on composite cathodes, as well as rate-testing and cycling performance in full cells, it is shown that the conductive carbon fibers form a percolative electronic network within the composite at a lower mass ratio (3-5 wt%) than particulate carbon (>5 wt%). The threshold to achieve electronic percolation coincides with higher accessible capacity in the cathode as the active material particles become electronically connected. However, carbon loadings beyond this percolation threshold lead to increased ion transport resistance, arising from disruptions to ionic conduction pathways and degraded contact at the interface between the electrolyte and active materials. Imaging, spectroscopy, and physics-based models quantitatively describe the relationship between carbon and electrolyte compositions and the cell's capacity and rate performance through percolation theory. This work demonstrates the importance of quantitatively understanding percolating networks in solid-state cells and that strategic engineering of conductive carbon morphologies can further increase the energy- and power-density of solid-state cells.

25 ENERGY STORAGE↗

Reducing Zinc Redistribution and Extending Cycle Life Via Electrochemical Synthesis of Zinc/Zinc Oxide Anodes in Rechargeable Alkaline Batteries

Redistribution of zinc over the electrode surface, also known as shape change, is a major problem and a cause of failure in alkaline zinc anode batteries. To mitigate this phenomenon, we propose a scalable approach based on an in situ formed, highly porous electrochemically synthesized ZnO matrix with uniformly electrodeposited zinc particles. This results in ∼70% improvement in cycle life performance at a rate of 10 mA cm −2 compared to control Zn anodes, which have not gone through the formation process. A quantitative electrolyte analysis revealed under-saturated zincate ion concentration in the electrochemically synthesized ZnO/Zn cells indicating reduced zincate movement. Post mortem analysis of the anodes indicated higher retention of both Zn and ZnO on the electrochemically synthesized ZnO anodes signifying reduced redistribution of active material. Image analysis of the cycled anodes revealed a narrower Zn particle size distribution (62−79 μ m) in contrast to a wider particle size distribution of 51–96 μ m observed in the control anodes. The formation approach results in electrochemically synthesized ZnO/Zn anodes providing a stable ZnO matrix in which Zn particles retain their localized distribution on cycling better than control electrodes conventionally made by pasting zinc particles together with a binder.

Kolhekar, Snehal (ORCID:0000000210321153)↗

Improvements in estimating proportions of objects from multispectral data

Methods for estimating proportions of objects and materials imaged within the instantaneous field of view of a multispectral sensor were developed further. Improvements in the basic proportion estimation algorithm were devised as well as improved alien object detection procedures. Also, a simplified signature set analysis scheme was introduced for determining the adequacy of signature set geometry for satisfactory proportion estimation. Averaging procedures used in conjunction with the mixtures algorithm were examined theoretically and applied to artificially generated multispectral data. A computationally simpler estimator was considered and found unsatisfactory. Experiments conducted to find a suitable procedure for setting the alien object threshold yielded little definitive result. Mixtures procedures were used on a limited amount of ERTS data to estimate wheat proportion in selected areas. Results were unsatisfactory, partly because of the ill-conditioned nature of the pure signature set.

Horwitz, H. M.↗

Schlieren optics for leak detection

The purpose of this research was to develop an optical method of leak detection. Various modifications of schlieren optics were explored with initial emphasis on leak detection of the plumbing within the orbital maneuvering system of the space shuttle (OMS pod). The schlieren scheme envisioned for OMS pod leak detection was that of a high contrast pattern on flexible reflecting material imaged onto a negative of the same pattern. We find that the OMS pod geometry constrains the characteristic length scale of the pattern to the order of 0.001 inch. Our experiments suggest that optical modulation transfer efficiency will be very low for such patterns, which will limit the sensitivity of the technique. Optical elements which allow a negative of the scene to be reversibly recorded using light from the scene itself were explored for their potential in adaptive single-ended schlieren systems. Elements studied include photochromic glass, bacteriorhodopsin, and a transmissive liquid crystal display. The dynamics of writing and reading patterns were studied using intensity profiles from recorded images. Schlieren detection of index gradients in air was demonstrated.

Peale, Robert E.↗

Zircon, Baddeleyite, and Reidite Found in Ries Crater Suevite

Introduction: Impact events can generate superheated impact melts and even vapor [1]. In the past decade, evidence of the high temperatures and high pressures of the impact process has been found in the impact melt from terrestrial craters (e.g., Mistastin Lake [2], Meteor Crater [3]) and even on the Moon [4–5]. Often, these studies involve zircon or zirconium-bearing phases. Zircon is a particularly useful mineral, due to its robustness and durability against weathering. It is used principally for chronology, but it has a multitude of geologic applications, including geothermometry and fingerprinting magma sources. Here we focus on its capability of recording impact conditions. Grains of zircon (ZrSiO4) are converted at high temperature and/or pressure during an impact event to reidite (a high-pressure polymorph of ZrSiO4) or to tetragonal-ZrO2 + SiO2 [6]. Reidite and tertragonal-ZrO2 leave identifying relicts in the rocks, markers of the high pressures and/or temperatures these rocks underwent. Ries Crater is a 26-km-diameter peak ring crater in southern Germany that formed approximately 15 Ma [7–9]. Ries is the type locality of the polymict impact breccia known as suevite. Here, we report a microanalytical study of suevite from the Ries impact structure. These analyses are used to inform our understanding of the pressure and temperature conditions involved in creating a polymict impact breccia such as suevite in a peak ring crater. Sample Description: The sample, denoted 16RS08, originates from Otting Quarry, at 48.8777° N, 10.7921° E, approximately 17 km from the center of the Ries Crater in Germany (approximately 4 km outside the crater rim). The material recorded in sample 16RS08 is therefore considered an outer suevite. The outer suevite is a discontinuous layer of polymict impact breccia that occurs outside the central ring of Ries, up to 22 km from the center of the crater [9]. Lithic clasts in the outer suevite consist primarily of crystalline basement rocks (gneiss, granite, amphibolite), with less than 5% of lithic clasts being overlying sedimentary rocks (limestone, sandstone, shale) [9]. The thin section studied contains variably shocked lithic and mineral clasts, impact glass, and interstitial minerals that make up the matrix of the breccia (Fig. 1) [9]. Methods: We used a Cameca SX100 electron probe microanalyzer (EPMA) located in the Kuiper Materials Imaging and Characterization Facility (KMICF) at the University of Arizona to obtain 15 elemental X-ray maps of 16RS08. We next used the JEOL 7900F SEM at the Astromaterials Research & Exploration Science (ARES) at NASA Johnson Space Center (JSC) to obtain electron backscatter diffraction (EBSD) maps and energy dispersive X-ray spectroscopy (EDS) maps of select portions of the section. The EBSD data were collected under beam conditions of 20 kV, and ~9 μA, with step sizes varying from 0.05 to 2 μm. Following EBSD data collection, we processed the data using AZtecCrystal and MTEX, a free MATLAB toolbox. Results: We used the elemental X-ray maps to identify the areas of interest in the section, particularly phosphates and Zr-bearing grains. These areas of interest were then targeted for follow up EBSD and EDS analyses. We have identified, through combined EBSD and EDS analysis, the presence of zircon, reidite, and monoclinic-ZrO2 (baddeleyite) in 16RS08. In 16RS08, we have found singular grains of zircon, zircon with a vermicular baddeleyite halo (Fig. 2a), and granular zircon with reidite (Fig. 2b). The different Zr-rich phases and their corresponding textures signifies that this sample underwent a broad spectrum of pressure and temperature conditions during the impact event. For example, zircons surrounded by a vermicular baddeleyite and SiO2 intergrowth (i.e., Fig. 2a) have been shown to preserve evidence of the extremely high temperatures of impact melt, upwards of 2370 °C [2, 6]. Similarly, reidite and granular zircon (i.e., Fig. 2b) have been shown to preserve evidence of high pressure, as the transition to reidite occurs >30 GPa [3, 6]. Future Work: Next, we will process the EBSD and EDS data for these Zr-rich grains, specifically looking for indicators of cubic- or tetragonal-ZrO2 in the baddeleyite remnants and of shock-precursors to the reidite. To further inform our work, we will also obtain BSE images of these grains using a Hitachi S-4800 SEM in KMICF at the University of Arizona, as well as geochemical spot analyses via EPMA. The data collected will be used to constrain the formation conditions of the Ries Crater outer suevite. Acknowledgments: We thank Ken Domanik and Jerry Chang for their support with data collection. This work was supported by a University of Arizona RII Core Facilities Pilot Program grant and start-up funds to JJB. TME thanks A. Cavosie and N. Timms for assistance during field sampling. We acknowledge support from NASA’s Planetary Science Research program for analysis performed at JSC. References: [1] Melosh H. J. (1989) Oxf. U. Press. [2] Timms et al. (2017) EPSL 477, 52–58. [3] Cavosie et al. (2016) Geology 44:9, 703–706. [4] White et al. (2020) Nature Astr. 4, 974–978. [5] Crow C. A. et al. (2017) GCA 202, 264–284. [6] Timms et al. (2017) Earth-Sci. Rev. 165, 185–202. [7] Schmieder M. et al. (2018) GCA 220, 146–157. [8] Schwarz W. H. et al. (2020) M&PS 55:2, 312–325. [9] Stöffler et al. (2013) M&PS 43:4, 515–589.

Zircon↗

Pink Spinel in Apollo Impact Melt Rock 68815: Implications for Mg-Suite Magmatism

Introduction: Magnesian rocks from the lunar highlands are collectively termed the Mg-suite. Characterized by high (>60) Mg# (molar 100×Mg/[Mg+Fe]) in mafic phases and calcic plagioclase, these rocks are plutonic to hypabyssal in origin, and include a range of bulk mineralogies such as troctolites, dunites, norites, gabbronorites, and spinel troctolites [1]. These Mg-suite lithologies have distinct trace element concentrations and ratios that differentiate them from other lunar rock types. These rocks are ancient, generally dated to between 4.5 and 4.1 Ga, although it is unknown if this represents the full range of Mg-suite ages [1–2]. Among the Mg-suite lithologies, the spinel troctolites are relatively rare, to date only found in polymict breccias [3]. Spinel troctolites, as their name suggests, consist of calcic plagioclase and forsteritic olivine, with minor amounts of spinel (MgAl2O4), ± pyroxene and cordierite [1,4]. This form of spinel is often called ‘pink’ spinel because of its appearance in thin section under plane polarized light (PPL; Fig. 1), due to minor amounts of Cr. Spinel troctolites are generally plutonic or hypabyssal in origin (subsequently exhumed and incorporated into polymict breccias), or formed through impact processes (e.g., crystalline impact melt) [5]. A spinel-rich lithology has also been found in the Moscoviense region of the Moon via the Moon Mineralogy Mapper (M3) and lacks other mafic phases [6]. Finally, while the Mg-suite sampled thus far consists of plutonic (or hypabyssal) rocks, the question remains if such magmas could have erupted on the surface of the Moon [7]. These magmas have much lower density than mare basalts, but little sample or remote sensing evidence has been found to support the idea that extrusive Mg-suite volcanism occurred [7]. Here, we present a coordinated microanalytical study of spinel-bearing lithic and mineral clasts found in Apollo sample 68815. These data will be used to understand their petrogenesis (magmatic or impact) and modification histories, and to shed light on the existence of volcanic Mg-suite rocks. Sample Description: Apollo sample 68815 is a polymict impact melt breccia containing a variety of lithic and mineral fragments embedded in devitrified impact melt. This sample was chipped off the top of a boulder at Station 8 during the Apollo 16 mission and had an original weight of nearly 1.8 kg. In this study, we investigated two polished thin sections of 68815: 68815,17 and 68815,148, both containing spinel. Methods: The thin sections of 68815 were studied using optical light microscopy (PPL, cross-polarized light, and reflected light) with a Keyence VHX-7100 Digital Microscope. Each section was then X-ray mapped for 13–14 elements using a Cameca SX100 electron probe microanalyzer (EPMA) located in the Kuiper Materials Imaging and Characterization Facility (KMICF) at the University of Arizona. We have obtained geochemical information about the phases (olivine, plagioclase, spinel, pyroxene) in the thin sections also using the EPMA. In addition, we have used ThermoScientific Helios NanoLab 660 Focused-Ion-Beam Scanning-Electron Microscope (FIB-SEM) and a Hitachi S-4800 SEM (both in KMICF) to obtain backscattered electron (BSE) images and energy dispersive Xray spectrometry (EDS) maps of areas of interest. Using a JEOL 7900F SEM at the Astromaterials Research & Exploration Science (ARES) at NASA Johnson Space Center (JSC), we have obtained electron backscatter diffraction (EBSD) maps of the spinel-bearing portions of the thin sections. The EBSD data were collected under beam conditions of 20 kV, and ~90 μA, with step sizes varying from 0.05 to 2 μm. Following EBSD data collection, we processed the data using AZtecCrystal and MTEX, a free MATLAB toolbox. Results: We have found clasts with subophitic textures, that consist of primarily olivine and plagioclase, with minor amounts of pink Mg-Al spinel and pyroxene (Fig. 1). These clasts are up to ~1 mm in length and contain spinels up to 50 μm across. We have additionally identified pink Mg-Al spinels within the impact melt (i.e., not contained in lithic clasts) in both thin sections. In one instance, a single spinel grain is approximately 300 μm across (Fig. 1b, 2). The spinel fragments embedded in impact melt have varying compositions, typically distinct from the compositions of spinels in the lithic clasts. Spinel-Bearing Clasts: Ten lithic clasts with similar textures and mineral compositions were identified between 68815,17 (two clasts) and ,148 (eight clasts). These clasts fall into two groups. The first has skeletal olivine with intergranular plagioclase, with minor amounts of pyroxene and spinel (Fig. 1a, 2c, 2d). The spinel in these clasts are found amid the plagioclase. The second group have an intergranular texture of olivine and plagioclase, again with minor spinel and pyroxene. The second group may contain spinels surrounded by plagioclase, and spinels enclosed in olivine. Spinels located within both clast types range from no apparent Cr zoning, to reverse zoning (Cr-enrichment inward; Fig. 2d), to normal zoning (Cr-enrichment outward). In the clasts thus far investigated with EPMA, plagioclase compositions range from An# (molar 100×Ca/[Ca+Na+K]) 92–96. Olivine Mg# ranged from 77 to 94, while pyroxene had Mg# from 54–84. Spinel in the clasts have Cr# (molar 100×Cr/[Cr+Al]) 2–4 and Mg# 88–91, which is within the range of pristine and plutonic spinel troctolites [8]. Isolated Spinels: These crystals are generally euhedral to subhedral, and can exhibit reverse Cr zoning (Cr enrichment inward) or no apparent Cr zoning. The spinels thus far investigated via EPMA have Cr# 9–14 and Mg# 65–82. The Cr# for these spinels is within the range reported by [8], but have lower Mg#. Future Work: We will continue to process the EBSD data for these lithic and mineral clasts. We will also continue to characterize these clasts using EPMA and SEM. By thoroughly characterizing the various spinels and spinel-bearing clasts, we aim to constrain the petrogenesis of these minerals and rock fragments. Acknowledgments: We thank NASA for the loan of these thin sections. We thank Ken Domanik and Jerry Chang for their support with data collection. Work was supported by a University of Arizona RII Core Facilities Pilot Program grant and start-up funds to JJB. We acknowledge support from NASA’s Planetary Science Research program for analysis performed at JSC. References: [1] Shearer C. K. et al. (2015) Am. Min. 100, 294–325. [2] Borg L. E. et al. (2020) GCA 290, 312–332. [3] Warren P. H. (1993) Am. Min. 78, 360–376. [4] Dymek R. F. et al. (1976) LPS VII, 2335–2378. [5] Treiman et al. (2019) Am. Min. 104, 370–384. [6] Pieters et al. (2011) JGR: Plan. 116:E00G08. [7] Prissel et al. (2016) Icarus 277, 319–329. [8] Prissel et al. (2016) Am. Min. 101, 1624–1635.

spinel↗

Speckle contrast from the split-and-delay unit with seeded X-ray pulses of the MID instrument at European XFEL

We report on the coherence properties and characteristics of the split- and-delay unit at the Materials Imaging and Dynamics instrument of the European XFEL under seeded-beam conditions. Our investigation focuses on the speckle contrast extracted from the scattering patterns from static scatterers and pulse splitting characteristics. Seeded-beam operation enabled a high throughput of the split-and-delay unit. We highlight the invaluable potential of the split-and-delay unit for experimental investigations for enhancing our understanding of ultrafast phenomena in molecular liquids, such as water and aqueous solutions.

Fuoss, Paul↗

Toward nonthermal control of excited quantum materials: framework and investigations by ultrafast electron scattering and imaging

Quantum material systems upon applying ultrashort laser pulses provide a rich platform to access excited material phases and their transformations that are not entirely like their equilibrium counterparts. The addressability and potential controls of metastable or long-trapped out-of-equilibrium phases have motivated interests both for the purposes of understanding the nonequilibrium physics and advancing the quantum technologies. Thus far, the dynamical spectroscopic probes eminently focus on microscopic electronic and phonon responses. For characterizing the long-range dynamics, such as order parameter fields and fluctuation effects, the ultrafast scattering probes offer direct sensitivity. Bridging the connections between the microscopic dynamics and macroscopic responses is central toward establishing the nonequilibrium physics behind the light-induced phases. Here, we present a path toward such understanding by cross-examining the structure factors associated with different dynamical states obtained from ultrafast electron scattering, imaging, and modeling. We give the basic theoretical framework on describing the non-equilibrium scattering problems and briefly describe how such framework relates to the out-of-equilibrium phenomena. We give effective models outlining the emergences of nonthermal critical points, hidden phases, and non-equilibrium relaxational responses from vacuum-suspended rare-earth tritellurides, tantalum disulfides thin films, and vanadium dioxide nanocrystalline materials upon light excitations.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantification of morphological change in materials based on image data utilizing machine learning techniques

Computed tomography (CT) resolution has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images visually reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect. Both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗