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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Silica aerogel can be used for dust collection and in situ X-ray analysis. Aerogels can be less absorbing than Be, and it is feasible to obtain X-ray transmission factors >50% using typical aerogels together with a 100-micrometer Be backing foil. Additional information is contained in the original extended abstract.
The martian surface has a primarily basaltic composition and is dominated by sedimentary deposits. Ancient layered sedimentary rocks have been identified across the planet from orbit, have been studied in situ by the Mars Exploration Rovers and the Mars Science Laboratory rover, and will be studied by the Mars 2020 rover. These ancient sedimentary rocks were deposited in fluvial, lacustrine, and eolian environments during a warmer and wetter era on Mars. It is important to study the composition of sediments in Mars analog environments to characterize how minerals in basaltic sedimentary systems are sorted and/or aqueously altered. This information can help us better interpret sedimentary processes from similar deposits on Mars and derive information about the igneous source rocks. Sediment sorting has been studied extensively on Earth, but not typically in basaltic environments. Previous work has addressed sorting of basaltic sediments through experimental techniques and in modern eolian basaltic systems and aqueous alteration in subglacial and proglacial environments. We add to this body of research by studying sediment sorting and aqueous alteration in a glacio-fluvio-eolian basaltic system in southwest Iceland.
Curiosity landed in Gale crater in August 2012 and has traversed ~27 km through sedimentary rocks that comprise the lower slopes of a ~5 km-high mound, informally known as Mount Sharp, to investigate depositional/diagenetic environments and potential habitability. Orbital visible/short-wave infrared spectra revealed some strata on lower Mount Sharp contain mineral assemblages that are indicative of water-rock interactions (1-3), with sulfate-bearing units overlying phyllosilicate-bearing units. This mineralogical succession may mark the beginning of the transition from a relatively wet/warm to a very dry/cold Mars (e.g., 1, 4). Curiosity began studying the strata that show mineralogical signatures from orbit in 2018, with the investigation of Vera Rubin ridge. Here, we describe the mineralogical diversity in these strata using X-ray diffraction data collected by the CheMin instrument. We report on the mineral assemblages from the hematite-rich Vera Rubin ridge, the smectite-rich Glen Torridon region, and the transition from the smectite-bearing rocks to the sulfate-bearing unit. We will present hypotheses explaining the changes in mineralogy throughout the strata, including changes in depositional environment, diagenetic reactions with saline groundwater, and groundwater-lake water interactions (e.g., 5-7).
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X-ray diffraction (XRD) data analysis can be a time-consuming and laborious task. Deep neural network (DNN) based models trained with synthetic XRD patterns have been proven to be a highly efficient, accurate, and automated method for analyzing common XRD data collected from solid samples in ambient environments. However, it remains unclear whether synthetic XRD-based models can be effective in solving micro(μ)-XRD mapping data for in situ experiments involving liquid phases, which always have lower quality and significant artifacts. In this study, we collected μ-XRD mapping data from a LaCl 3 -calcite hydrothermal fluid system and trained two categories of models to analyze the experimental XRD patterns. Here, the models trained solely with synthetic XRD patterns showed low accuracy (as low as 64%) when solving experimental μ-XRD mapping data. However, the accuracy of the DNN models significantly improved (90% or above) when we trained them with a data set containing both synthetic and a small number of labeled experimental μ-XRD patterns. This study highlights the importance of labeled experimental patterns in training DNN models to solve μ-XRD mapping data from in situ experiments involving liquid phases.
This dataset from Lawrence Livermore National Laboratory (LLNL) consists of four raw X-ray diffraction (XRD) scans and preliminary results of quantitative XRD analysis. The scanned samples were prepared from four subcores, which came from various depths of the FORGE well 16A(78)-32 core. Desired core lengths were selected from available core photos (on GDR), provided by FORGE personnel, and subcored at LLNL. The XRD scans were collected in May 2023 at LLNL as pre-experimental characterization data for these subcores, which will be used in core-flooding experiments at LLNL and in triaxial direct shear experiments at Los Alamos National Laboratory as part of DOE Project 5-2428. XRD scans are in RAW file format (e.g., FORGE-5477-full.raw) and are suitable for viewing and analysis using open-source quantitative XRD software (e.g., Profex; www.profex-xrd.org ) and/or other proprietary instrument software.
Case studies of 1T-TiSe 2 and YBa 2 Cu 3 O 7-δ have demonstrated that X-ray diffraction (XRD) studies can be used to trace even subtle structural phase transitions which are inherently connected with the onset of superconductivity in these benchmark systems. However, the utility of XRD in the investigation of superconductors like MgB 2 lacking an additional symmetry-breaking structural phase transition is not immediately evident. Nevertheless, high-resolution powder XRD experiments on MgB 2 in combination with maximum entropy method analyses hinted at differences between the electron density distributions at room temperature and 15 K, that is, below the T c of approx. 39 K. The high-resolution single-crystal XRD experiments in combination with multipolar refinements presented here can reproduce these results but show that the observed temperature-dependent density changes are almost entirely due to a decrease of atomic displacement parameters as a natural consequence of a reduced thermal vibration amplitude with decreasing temperature. Our investigations also shed new light on the presence or absence of magnesium vacancies in MgB 2 samples–a defect type claimed to control the superconducting properties of the compound. Here, we propose that previous reports on the tendency of MgB 2 to form non-stoichiometric Mg 1–x B 2 phases (1 – x ~ 0.95) during high-temperature (HT) synthesis might result from the interpretation of XRD data of insufficient resolution and/or usage of inflexible refinement models. Indeed, advanced refinements based on an Extended Hansen–Coppens multipolar model and high-resolution X-ray data, which consider explicitly the contraction of core and valence shells of the magnesium cations, do not provide any significant evidence for the formation of non-stoichiometric Mg 1–x B 2 phases during HT synthesis.
Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.
A combination of in situ small-angle X-ray scattering (SAXS) microstructure characterization over scales ranging from 1 nm to 10 µm and powder X-ray diffraction (XRD) structure characterization under various gas/pressure/temperature conditions with density functional theory (DFT) calculations provides new insights for the CO2 sorption behavior of a one-dimensional porous coordination polymer: catena-bis(dibenzoylmethanato)(4,4′-bipyridyl)nickel(II), denoted NiDBM-Bpy. The NiDBM-Bpy chains are held together by van der Waals forces, but the structure of guest-free NiDBM-Bpy is unsolved due to a lack of suitable crystals and high-quality powder XRD patterns. Nevertheless, SAXS and powder XRD can follow microstructural and structural changes as a function of gas pressure, composition and temperature. Both mixed-gas flow and static supercritical CO2 regimes are explored experimentally. DFT calculations are used to model the structural variation associated with XRD changes and hysteresis in the sorption isotherms. XRD and DFT calculations suggest that an orthorhombic Fddd structure with two CO2 per Ni emerges following a transition from the structure with lower molar volume and symmetry that exists without CO2 present.
Pulsed-power generators using the magnetic loading technique are able to produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects such as dislocations. Here, we present a cost effective, compact X-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically-driven ramp compression of materials with single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials community. The success in fielding this new XRD diagnostic dramatically improves our predictive capability and understanding of rate-dependent behavior at or near phase transition. As Sandia plans the next-generation pulse-power driver platform, a key element needed to deliver new state-of-the-art experiments will be having the necessary diagnostic tools to probe new regimes and phenomena. These diagnostics need to be as versatile, compact, and portable as they are powerful. The development of a platform-independent XRD diagnostic gives Sandia researchers a new window to study the microstructure and phase dynamics of materials under load. This project has paved the way for phase transition research in a variety of materials with mission interest.
The composition and phase fraction of the intergranular phase of 94ND10 ceramic is determined and fabricated ex situ. The fraction of each phase is 85.96 vol% Al 2 O 3 bulk phase, 9.46 vol% Mg-rich intergranular phase, 4.36 vol% Ca/Si-rich intergranular phase, and 0.22 vol% voids. The Ca/Si-rich phase consists of 0.628 at% Mg, 12.59 at% Si, 10.24 at% Ca, 17.23 at% Al, and balance O. The Mgrich phase consists of 14.17 at% Mg, 0.066 at% Si, 0.047 at% Ca, 28.69 at% Al, and balance O. XRD of the ex situ intergranular material made by mixed oxides consisting of the above phase and element fractions yielded 92 vol% MgAl 2 O 4 phase and 8 vol% CaAl 2 Si 2 O 8 phase. The formation of MgAl 2 O 4 phase is consistent with prior XRD of 94ND10, while the CaAl 2 Si 2 O 8 phase may exist in 94ND10 but at a concentration not readily detected with XRD. The MgAl 2 O 4 and CaAl 2 Si 2 O 8 phases determined from XRD are expected to have the elemental compositions for the Mg-rich and Ca/Si-rich phases above by cation substitutions (e.g., some Mg substituted for by Ca in the Mg-rich phase) and impurity phases not detectable with XRD.
The carbon phase diagram is rich with polymorphs which possess very different physical and optical properties ideal for different scientific and engineering applications. An understanding of the dynamically driven phase transitions in carbon is particularly important for applications in inertial confinement fusion, as well as planetary and meteorite impact histories. Experiments on the Z Pulsed Power Facility at Sandia National Laboratories generate dynamically compressed high-pressure states of matter with exceptional uniformity, duration, and size that are ideal for investigations of fundamental material properties. X-ray diffraction (XRD) is an important material physics measurement because it enables direct observation of the strain and compression of the crystal lattice, and it enables the detection and identification of phase transitions. Several unique challenges of dynamic compression experiments on Z prevent using XRD systems typically utilized at other dynamic compression facilities, so novel XRD diagnostics have been designed and implemented. We performed experiments on Z to shock compress carbon (pyrolytic graphite) samples to pressures of 150–320 GPa. The Z-Beamlet Laser generated Mn-Heα (6.2 keV) X-rays to probe the shock-compressed carbon sample, and the new XRD diagnostics measured changes in the diffraction pattern as the carbon transformed into its high-pressure phases. Quantitative analysis of the dynamic XRD patterns in combination with continuum velocimetry information constrained the stability fields and melting of high-pressure carbon polymorphs.
The residual stresses in graphite fiber reinforced aluminum (Gr/Al) composites with various thermal histories are measured using X-ray diffraction (XRD) methods. The XRD stress analysis is based on the determination of lattice strains by precise measurements of the interplanar spacings in different directions of the sample. The sample is a plate consisting of two-ply P 100 Gr/Al 6061 precursor wires and Al 6061 overlayers. Prior to XRD measurement, the 6061 overlayers are electrochemically removed. In order to calibrate the relationship between stress magnitude and lattice spacing shift, samples of Al 6061 are loaded at varying stress levels in a three-point bend fixture, while the stresses are simultaneously determined by XRD and surface-attached strain gages. The stresses determined by XRD closely match those determined by the strain gages. Using these calibrations, the longitudinal residual stresses of P 100 Gr/Al 6061 composites are measured for various heat treatments, and the results are presented.