Search NASA⌕ Search

SEARCH · Search NASA

Results for “Texture prediction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Characterization of MoS 2 films via simultaneous grazing incidence X-ray diffraction and grazing incidence X-ray fluorescence (GIXRD/GIXRF)

Physical vapor deposited (PVD) molybdenum disulfide (nominal composition MoS 2 ) is employed as a thin film solid lubricant for extreme environments where liquid lubricants are not viable. The tribological properties of MoS 2 are highly dependent on morphological attributes such as film thickness, orientation, crystallinity, film density, and stoichiometry. These structural characteristics are controlled by tuning the PVD process parameters, yet undesirable alterations in the structure often occur due to process variations between deposition runs. Nondestructive film diagnostics can enable improved yield and serve as a means of tuning a deposition process, thus enabling quality control and materials exploration. Grazing incidence X-ray diffraction (GIXRD) for MoS 2 film characterization provides valuable information about film density and grain orientation (texture). However, the determination of film stoichiometry can only be indirectly inferred via GIXRD. The combination of density and microstructure via GIXRD with chemical composition via grazing incidence X-ray fluorescence (GIXRF) enables the isolation and decoupling of film density, composition, and microstructure and their ultimate impact on film layer thickness, thereby improving coating thickness predictions via X-ray fluorescence. We have augmented an existing GIXRD instrument with an additional X-ray detector for the simultaneous measurement of energy-dispersive X-ray fluorescence spectra during the GIXRD analysis. This combined GIXRD/GIXRF analysis has proven synergetic for correlating chemical composition to the structural aspects of MoS 2 films provided by GIXRD. We present the usefulness of the combined diagnostic technique via exemplar MoS 2 film samples and provide a discussion regarding data extraction techniques of grazing angle series measurements.

MoS2↗

3D hydrogeophysical characterization of managed aquifer recharge basins

Aquifers are increasingly stressed. Managed aquifer recharge provides a potential solution to mitigate this stress and provide sustainable groundwater resources. Subsurface properties are known to have a strong control on the infiltration rates that can be achieved. However, these properties are often highly heterogeneous and difficult to assess with conventional probing techniques. Here, we show the application of 3D geophysical imaging to assess the recharge potential and its variation across several basins used for managed aquifer recharge. We link in-situ measurements of saturated hydraulic conductivity with the electrical resistivity of the subsurface to establish petrophysical relationships and use those relationships to estimate the distribution of hydraulic conductivity throughout the five recharge basins. Our results show a considerable variability in the hydraulic properties, i.e., soil texture and saturated hydraulic conductivity, that have a direct impact on potential infiltration rates. We use the 3D hydraulic property distributions to model groundwater recharge and provide estimates for infiltration rates and volumes, and use this approach to assess the impact of management activities on groundwater recharge performance. Having such data not only enables us to predict infiltration rates, but also provides means for optimizing such water infrastructure.

54 ENVIRONMENTAL SCIENCES↗

Experimental characterization and atomistic simulation of grain boundary segregation in Mg-Y alloys

As a rare earth solute element in Mg alloys, Y has the beneficial effects of increasing both the strength and the ductility as well as weakening the crystallographic texture. To achieve a more fundamental understanding on how Y addition affects the microstructural evolution and mechanical properties, the Y segregation behavior at grain boundaries was investigated in Mg-1wt.%Y and Mg-7wt.%Y alloys at different conditions. The segregation intensity and its dependence on the grain boundary misorientation angle were experimentally characterized and computationally predicted. Strong segregation at grain boundaries was observed in both low and high Y-containing alloys. Y segregation was found to remain in alloy Mg-7Y after high-temperature annealing heat treatment at 540 °C. No direct correlation between the Y segregation intensity and the grain boundary misorientation angle could be established based on either the experimental characterization or the atomistic simulation with a spectral model. We thus conclude that grain boundary segregation of Y is independent of grain boundary misorientation angle.

Grain boundary↗

Terrestrial Analogs to Wind-Related Features at the Viking and Pathfinder Landing Sites on Mars

Features in the Mojave Desert and Iceland provide insight into the characteristics and origin of Martian wind-related landforms seen by the Viking and Pathfinder landers. The terrestrial sites were chosen because they exhibit diverse wind features that are generally well understood. These features have morphologies comparable to those on Mars and include origins by deposition and erosion, with erosional processes modifying both soils and rocks. Duneforms and drifts are the most common depositional features seen at the Martian landing sites and indicate supplies of sand-sized particles blown by generally unidirectional winds. Erosional features include lag deposits, moat-like depressions around some rocks, and exhumed soil horizons. They indicate that wind can deflate at least some sediments and that this process is particularly effective where the wind interacts with rocks. The formation of ripples and wind tails involves a combination of depositional and erosional processes. Rock erosional features, or ventifacts, are recognized by their overall shapes, erosional flutes, and characteristic surface textures resulting from abrasion by windblown particles. The physics of saltation requires that particles in ripples and duneforms are predominantly sand-sized (60-2000 microns). The orientations of duneforms, wind tails, moats, and ventifacts are correlated with surface winds above particle threshold. Such winds are influenced by local topography and are correlated with winds at higher altitudes predicted by atmospheric models.

Greeley, Ronald↗

Observation of plaid-like spin splitting in a noncoplanar antiferromagnet

Spatial, momentum and energy separation of electronic spins in condensed matter systems guides the development of novel devices where spin-polarized current is generated and manipulated. Recent attention on a set of previously overlooked symmetry operations in magnetic materials leads to the emergence of a new type of spin splitting, enabling giant and momentum-dependent spin polarization of energy bands on selected antiferromagnets. Despite the ever-growing theoretical predictions, the direct spectroscopic proof of such spin splitting is still lacking. Here, we provide solid spectroscopic and computational evidence for the existence of such materials. In the noncoplanar antiferromagnet MnTe 2 , the in-plane components of spin are found to be antisymmetric about the high-symmetry planes of the Brillouin zone, comprising a plaid-like spin texture in the antiferromagnetic (AFM) ground state. Such an unconventional spin pattern, further found to diminish at the high- temperature paramagnetic state, stems from the intrinsic AFM order instead of spin- orbit coupling (SOC). Furthermore, our finding demonstrates a new type of quadratic spin texture induced by time-reversal breaking, placing AFM spintronics on a firm basis and paving the way for studying exotic quantum phenomena in related materials.

Electronic devices↗

A Framework for Inverse Prediction Using Functional Response Data

Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.

42 ENGINEERING↗

Viscoplastic selfconsistent (VPSC) code (version 8, open source)

VPSC is a mean-field polycrystal plasticity code for the prediction of the mechanical response and microstructure evolution of polycrystalline aggregates. The VPSC code is the computational realization of the visco-plastic self-consistent theory of polycrystal deformation. Both the theory and details of its numerical implementation were originally reported by R.A. Lebensohn and C.N. Tomé: "A self-consistent approach for the simulation of plastic deformation and texture development of polycrystals: application to Zirconium alloys", Acta Metallurgica et Materialia 41, 2611 (1993). Since then, the VPSC code has experienced several improvements and extensions and it is nowadays extensively used to simulate plastic deformation of polycrystalline aggregates and to interpret experimental evidence on metals, minerals and polymers.

Lebensohn, Ricardo↗

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization

Photonic surfaces designed with specific optical characteristics are becoming increasingly crucial for novel energy harvesting and storage systems. The design of these surfaces can be achieved by texturing materials using lasers. The optimal adjustment of laser fabrication parameters to achieve target surface optical properties is an open challenge. Thus, we develop a surrogate-based optimization approach. Our framework employs the Random Forest algorithm to model the forward relationship between the laser fabrication parameters and the resulting optical characteristics. During the optimization process, we use a greedy, prediction-based exploration strategy that iteratively selects batches of laser parameters to be used in experimentation by minimizing the predicted discrepancy between the surrogate model’s outputs and the user-defined target optical characteristics. This strategy allows for efficient identification of optimal fabrication parameters without the need to model the error landscape directly. We demonstrate the efficiency and effectiveness of our approach on two synthetic benchmarks and two specific experimental applications of photonic surface inverse design targets. By calculating the average performance of our algorithm compared to other state of the art optimization methods, we show that our algorithm performs, on average, twice as well across all benchmarks. Additionally, a warm starting inverse design technique for changed target optical characteristics enhances the performance of the introduced approach.

97 MATHEMATICS AND COMPUTING↗

Femtosecond temperature measurements of laser-shocked copper deduced from the intensity of the x-ray thermal diffuse scattering

We present 50-fs, single-shot measurements of the x-ray thermal diffuse scattering (TDS) from copper foils that have been shocked via nanosecond laser ablation up to pressures above ∼135 GPa. We hence deduce the x-ray Debye–Waller factor, providing a temperature measurement. The targets were laser-shocked with the DiPOLE 100-X laser at the High Energy Density endstation of the European X-ray Free-Electron Laser. Single x-ray pulses, with a photon energy of 18 keV, were scattered from the samples and recorded on Varex detectors. Despite the targets being highly textured (as evinced by large variations in the elastic scattering) and with such texture changing upon compression, the absolute intensity of the azimuthally averaged inelastic TDS between the Bragg peaks is largely insensitive to these changes, and allowing for both Compton scattering and the low-level scattering from a sacrificial ablator layer provides a reliable measurement of $T/Θ^2_D$, where Θ D is the Debye temperature. We compare our results with the predictions of the SESAME 3336 and LEOS 290 equations of state for copper and find good agreement within experimental errors. We, thus, demonstrate that single-shot temperature measurements of dynamically compressed materials can be made via thermal diffuse scattering of XFEL radiation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Large Rashba spin splittings in bulk and monolayer of BiAs

There is great interest in developing new materials with Rashba split bands near the Fermi level for spintronics. Here, using first-principles calculations, we predict BiAs as a semiconductor with large Rashba splitting in bulk and monolayer forms. Bulk BiAs has a layered crystal structure with two atoms in a rhombohedral primitive cell, derived from the structure of the parent Bi and As elemental phases. It is a narrow band gap semiconductor, and it shows a combination of Rashba and Dresselhaus spin splitting with a characteristic spin texture around the L point in the Brillouin zone of the hexagonal conventional unit cell. It has sizable Rashba energies and Rashba coupling constants in the valence and conduction bands at the band edges. The 2D monolayer of BiAs has a much larger band gap at Γ, with a circular spin texture characteristic of a pure Rashba effect. The Rashba energy and Rashba coupling constant of monolayer BiAs are large compared to other known 2D materials and rapidly increase under biaxial tensile strain.

36 MATERIALS SCIENCE↗

High-pressure melt dynamics in shock-compressed titanium

In this work we study the high-pressure melting behavior of titanium using laser-driven shock compression with in situ femtosecond x-ray diffraction and molecular-dynamics simulations based on a machine-learned interatomic potential. The MD simulations predict the solid-liquid coexistence on the Hugoniot in the ∼111−124GPa range. Experimentally, we observe the first evidence of liquid at 86 GPa. We also observe pronounced microstructural changes with pressure, with strong grain refinement associated with the emergence of liquid, within the solid-liquid coexistence (∼110−126GPa). Above 126 GPa, we observe the persistence of residual levels of highly textured crystalline Ti to ∼180GPa, well above the expected melt completion pressure. We discuss the accuracy that current laser-shock experimental platforms have at determining the melt onset and completion pressures.

36 MATERIALS SCIENCE↗

Low Earth Orbital Atomic Oxygen Interactions With Spacecraft Materials

Atomic oxygen, formed in Earth s thermosphere, interacts readily with many materials on spacecraft flying in low Earth orbit (LEO). All hydrocarbon based polymers and graphite are easily oxidized upon the impact of approx.4.5 eV atomic oxygen as the spacecraft ram into the residual atmosphere. The resulting interactions can change the morphology and reduce the thickness of these materials. Directed atomic oxygen erosion will result in the development of textured surfaces on all materials with volatile oxidation products. Examples from space flight samples are provided. As a result of the erosive properties of atomic oxygen on polymers and composites, protective coatings have been developed and are used to increase the functional life of polymer films and composites that are exposed to the LEO environment. The atomic oxygen erosion yields for actual and predicted LEO exposure of numerous materials are presented. Results of in-space exposure of vacuum deposited aluminum protective coatings on polyimide Kapton indicate high rates of degradation are associated with aluminum coatings on both surfaces of the Kapton. Computational modeling predictions indicate that less trapping of the atomic oxygen occurs, with less resulting damage, if only the space-exposed surface is coated with vapor deposited aluminum rather than having both surfaces coated.

Banks, Bruce A.↗

Crack tip microplasticity mediated by microstructure gradients

Abstract Traditional fracture theories infer damage at cracks (local field) by surveying loading conditions away from cracks (far field). This approach has been successful in predicting ductile fracture, but it normally assumes isotropic and homogeneous materials. However, myriads of manufacturing procedures induce heterogeneous microstructural gradients that can affect the accuracy of traditional fracture models. This work presents a microstructure‐sensitive finite element approach to explore the shielding effects of grain size and crystallographic orientation gradients on crack tip microplasticity and blunting. A dislocation density‐based crystal plasticity model conveys texture evolution, grain size effects, and directional hardening by computing the constraint from dislocation structures. The results demonstrate that the microstructure can act as a buffer between the local and far fields that affects the crack tip microplasticity variability. For nominal opening loading, grain size and texture affect the local ductility and induce a non‐negligible multiaxial plastic deformation. Furthermore, driving forces based on measuring displacements away from the crack tip are less affected by the microstructure, which suggests that traditional experimental methods smear out important crack tip variability.

Castelluccio, Gustavo M.↗

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response

Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To predict the performance of particular microstructural configuration and thereby overall performance, constitutive models of materials with microstructure are needed. In this work we provide neural network architectures that provide effective homogenization models of materials with anisotropic components. These models satisfy equivariance and material symmetry principles inherently through a combination of equivariant and tensor basis operations. We demonstrate them on datasets of stochastic volume elements with different textures and phases where the material undergoes elastic and plastic deformation, and show that the these network architectures provide significant performance improvements.

anisotropy↗

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗

A scene-analysis approach to remote sensing

The author has identified the following significant results. Geometric correspondance between a sensed image and a symbolic map is established in an initial stage of processing by adjusting parameters of a sensed model so that the image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image, what to look for, and how to interpret what is seen. For simple monitoring tasks involving multispectral classification, these constraints significantly reduce computation, simplify interpretation, and improve the utility of the resulting information. Previously intractable tasks requiring spatial and textural analysis may become straightforward in the context established by the map knowledge. The use of map-guided image analysis in monitoring the volume of water in a reservoir, the number of boxcars in a railyard, and the number of ships in a harbor is demonstrated.

Tenenbaum, J. M.↗

Modeling Stress-Induced Pore Water Pressures in The Vadose Zone Beneath a Composite-Lined Landfill - 20029

A finite-element model was developed to evaluate mechanisms contributing to positive pore pressures measured with sealed pressure transducers in the geological buffer beneath the Environmental Management Waste Management Facility, a composite-lined mixed waste disposal facility operated by the US Department of Energy. The geological buffer is a 3-m-thick engineered fine-textured layer directly beneath the Environmental Management Waste Management Facility's composite liner, and above the groundwater table. The model accounts for changes in pore water pressure resulting from (i) loading imposed by waste placed on the overlying liner, (ii) moistening of the geological buffer due to equilibration with the underlying geological materials, and (iii) fluctuations in the elevation of the underlying groundwater table. Pore water pressures predicted by the model are in good agreement with pore water pressures measured in the field. The predictions confirm that positive pore water pressures recorded by the sealed pressure transducers in the geological buffer are excess pore water pressures induced by the vertical normal stress imposed by waste placed on the liner, and are not due to a rise in the groundwater table. Simulations also showed that two additional years of filling would further increase the pore water pressure without any change in elevation of the groundwater table. The geological buffer remained unsaturated during the simulation, with a B-coefficient (parameter indicative of the degree of saturation) similar to that computed from the field-measured pore water pressures and waste filling records. Larger increases in pore water pressure were observed when the geological buffer was assumed to have higher initial saturation, as was observed in the field data. Incorporating seasonal fluctuations in the groundwater table beneath the geological buffer in the model resulted in predictions of small seasonal oscillation in the pore water pressure at the measurement location, similar to seasonal oscillations observed in the field. Predictions made with the model indicate that the dissipation of the excess pore water pressures will occur over decades due to the low hydraulic conductivity of the geological buffer material. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Method and apparatus for predicting the direction of movement in machine vision

A computer-simulated cortical network is presented. The network is capable of computing the visibility of shifts in the direction of movement. Additionally, the network can compute the following: (1) the magnitude of the position difference between the test and background patterns; (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern; and (3) the direction of a test pattern moved relative to a textured background. The direction of movement of an object in the field of view of a robotic vision system is detected in accordance with nonlinear Gabor function algorithms. The movement of objects relative to their background is used to infer the 3-dimensional structure and motion of object surfaces.

Lawton, Teri B.↗