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Results for “diffraction pattern simulation”

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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Thrust #3: Simulation and Measurement of Bio-enabled Lensless Infrared Focusing and Spatially-Controlled Multiwavelength IR reflection

The path to quantitatively characterizing the possible impact of refractive index on the focusing behavior of C. Wailesii diatoms frustules and their replicas first required the careful design of a control experiment that allowed for judicious control of both material and hole pattern variables, which are thought to govern focusing behavior. This was accomplished by FIB-milling synthetic hole patterns with well-controlled dimensions into thin SiO 2 and MgO/Si films. In doing so, an ideal sample is obtained whose pore patterns can be simulated via beam propagation methods and whose relatively simple interference patterns can be measured by far-field diffraction imaging. Together with refractive index measurements via ellipsometry on SiO 2 and MgO/Si thin films, these results showed that the focusing distances at six different wavelengths over 550-1050 nm are strongly correlated with the dispersion of the refractive index in this range. Although assertions have been made to this point in the literature, the results given here presented an improved characterization of the role that refractive index played in focusing behavior in a “diatom-like” hole pattern that otherwise is missing in earlier works due to inadequate characterization of refractive index dispersion and poor control over hole pattern dimensions. These results provided a reference point with which measurements and simulations of diatoms and their replicas can be compared.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Identifying point defects and ordering in the high-entropy layered oxide Li 1.5 MO 3-δ (M=Mn, Al, Fe, Co, Ni) for energy storage applications

High-entropy layered oxides (HELOs) represent a very promising class of next-generation battery cathodes, combining the well-studied properties of layered cathode materials such as LiCoO 2 with the chemical tunability and stability of high-entropy materials. HELO materials often form particles with complex defects and domain structures, complicating accurate characterization of structure and cation mixing. Understanding disorder and order in HELO materials is necessary for understanding their performance and utility as cathodes. Here we demonstrate the characterization of the HELO Li 1.5 MO 3-δ (M = Mn, Al, Fe, Co, Ni), wherein X-ray powder diffraction, transmission electron microscopy imaging, and electron diffraction patterns are analyzed to reveal the presence of ordering in the HELO, with imaging and diffraction simulation employed to compare experimental results to atomic modeling. Finally, without rigorous characterization at the atomic scale, important features such as defect ordering can be easily overlooked and therefore remain unconsidered when interpreting experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate

Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

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.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Simulation and analysis of airborne antenna radiation patterns

The objective is to develop an accurate and efficient analytic solution for predicting high frequency radiation patterns of fuselage-mounted airborne antennas. This is an analytic study of airborne antenna patterns using the Uniform Geometrical Theory of Diffraction (UTD). The aircraft is modeled in its most basic form so that the solution is applicable to general-type aircraft. The fuselage is modeled as a perfectly conducting composite ellipsoid; whereas, the wings, stabilizers, nose, fuel tanks, and engines, are simulated as perfectly conducting flat plates that can be attached to the fuselage and/or to each other. The composite-ellipsoid fuselage model is necessary to successfully simulate the wide variety of real world fuselage shapes. Since the antenna is mounted on the fuselage, it has a dominant effect on the resulting radiation pattern so it must be simulated accurately, especially near the antenna. Various radiation patterns are calculated for commercial, private, and military aircraft, and the Space Shuttle Orbiter. The application of this solution to numerous practical airborne antenna problems illustrates its versatility and design capability. In most cases, the solution accuracy is verified by the comparisons between the calculated and measured data.

Kim, J. J.↗
NASA NTRS2000

Computer Simulations to Study Diffraction Effects of Stacking Faults in Beta-SiC: II. Experimental Verification: Experimental Verification - 2

Earlier results from computer simulation studies suggest a correlation between the spatial distribution of stacking errors in the Beta-SiC structure and features observed in X-ray diffraction patterns of the material. Reported here are experimental results obtained from two types of nominally Beta-SiC specimens, which yield distinct XRD data. These samples were analyzed using high resolution transmission electron microscopy (HRTEM) and the stacking error distribution was directly determined. The HRTEM results compare well to those deduced by matching the XRD data with simulated spectra, confirming the hypothesis that the XRD data is indicative not only of the presence and density of stacking errors, but also that it can yield information regarding their distribution. In addition, the stacking error population in both specimens is related to their synthesis conditions and it appears that it is similar to the relation developed by others to explain the formation of the corresponding polytypes.

Pujar, Vijay V.↗
DOE OSTI2016

A comprehensive simulation model of the performance of photochromic films in absorbance-modulation-optical-lithography

Optical lithography is the most prevalent method of fabricating micro-and nano-scale structures in the semiconductor industry due to the fact that patterning using photons is fast, accurate and provides high throughput. However, the resolution of this technique is inherently limited by the physical phenomenon of diffraction. Absorbance-Modulation-Optical Lithography (AMOL), a recently developed technique has been successfully demonstrated to be able to circumvent this diffraction limit. AMOL employs a dual-wavelength exposure system in conjunction with spectrally selective reversible photo-transitions in thin films of photochromic molecules to achieve patterning of features with sizes beyond the far-field diffraction limit. We have developed a finite-element-method based full-electromagnetic-wave solution model that simulates the photo-chemical processes that occur within the thin film of the photochromic molecules under illumination by the exposure and confining wavelengths in AMOL. This model allows us to understand how the material characteristics influence the confinement to sub-diffraction dimensions, of the transmitted point spread function (PSF) of the exposure wavelength inside the recording medium. The model reported here provides the most comprehensive analysis of the AMOL process to-date, and the results show that the most important factors that govern the process, are the polarization of the two beams, the ratio of the intensities of the two wavelengths, the relative absorption coefficients and the concentration of the photochromic species, the thickness of the photochromic layer and the quantum yields of the photoreactions at the two wavelengths. The aim of this work is to elucidate the requirements of AMOL in successfully circumventing the far-field diffraction limit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Comprehensive characterization of ball-milled powders simulating a tribofilm system

A model system was used to simulate the properties of tribofilms which form during automotive braking. The model system was prepared by ball milling of a blend of 70 vol.% iron oxides, 15 vol.% molybdenum disulfide and 15 vol.% graphite. The resulting mixture was characterized by X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and various transmission electron microscopic (TEM) methods, including energy dispersive X-ray spectroscopy (EDXS), high resolution investigations (HRTEM) with corresponding simulation of the HRTEM images, diffraction methods such as scanning nano-beam electron diffraction (SNBED) and selected area electron diffraction (SAED). It could be shown that the ball milling caused a reduction of the grain size of the initial components to the nanometer range. Sometimes even amorphization or partial break-down of the crystal structure was observed for MoS{sub 2} and graphite. Moreover, chemical reactions lead to a formation of surface coverings of the nanoparticles by amorphous material, molybdenum oxides, and iron sulfates as derived from XPS. - Highlights: • Ball milling of iron oxides, MoS{sub 2}, and graphite to simulate a tribofilm • Increasing coefficient of friction after ball milling of the model blend • Drastically change of the diffraction pattern of the powder mixture • TEM & XPS showed the components of the milled mixture and the process during milling. • MoS{sub 2} and graphite suffered a loss in translation symmetry or became amorphous.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Simulations of X-ray diffraction of shock-compressed single-crystal tantalum with synchrotron undulator sources

Polychromatic synchrotron undulator X-ray sources are useful for ultrafast single-crystal diffraction under shock compression. Here, simulations of X-ray diffraction of shock-compressed single-crystal tantalum with realistic undulator sources are reported, based on large-scale molecular dynamics simulations. Purely elastic deformation, elastic–plastic two-wave structure, and severe plastic deformation under different impact velocities are explored, as well as an edge release case. Transmission-mode diffraction simulations consider crystallographic orientation, loading direction, incident beam direction, X-ray spectrum bandwidth and realistic detector size. Diffraction patterns and reciprocal space nodes are obtained from atomic configurations for different loading (elastic and plastic) and detection conditions, and interpretation of the diffraction patterns is discussed.

Tang, M. X.↗
NASA NTRS2005

Processing of Lunar Soil Simulant for Space Exploration Applications

NASA's long-term vision for space exploration includes developing human habitats and conducting scientific investigations on planetary bodies, especially on Moon and Mars. To reduce the level of up-mass processing and utilization of planetary in-situ resources is recognized as an important element of this vision. Within this scope and context, we have undertaken a general effort aimed primarily at extracting and refining metals, developing glass, glass-ceramic, or traditional ceramic type materials using lunar soil simulants. In this paper we will present preliminary results on our effort on carbothermal reduction of oxides for elemental extraction and zone refining for obtaining high purity metals. In additions we will demonstrate the possibility of developing glasses from lunar soil simulant for fixing nuclear waste from potential nuclear power generators on planetary bodies. Compositional analysis, x-ray diffraction patterns and differential thermal analysis of processed samples will be presented.

Sen, Subhayu↗
NASA NTRS1994

Scattering Effects of Solar Panels on Space Station Antenna Performance

Characterizing the scattering properties of the solar array panels is important in predicting Space Station antenna performance. A series of far-field, near-field, and radar cross section (RCS) scattering measurements were performed at S-Band and Ku-Band microwave frequencies on Space Station solar array panels. Based on investigation of the measured scattering patterns, the solar array panels exhibit similar scattering properties to that of the same size aluminum or copper panel mockup. As a first order approximation, and for worse case interference simulation, the solar array panels may be modeled using perfect reflecting plates. Numerical results obtained using the Geometrical Theory of Diffraction (GTD) modeling technique are presented for Space Station antenna pattern degradation due to solar panel interference. The computational and experimental techniques presented in this paper are applicable for antennas mounted on other platforms such as ship, aircraft, satellite, and space or land vehicle.

Panneton, Robert J.↗
DOE OSTI2015

Tailored multivariate analysis for modulated enhanced diffraction

Modulated enhanced diffraction (MED) is a technique allowing the dynamic structural characterization of crystalline materials subjected to an external stimulus, which is particularly suited for in situ and operando structural investigations at synchrotron sources. Contributions from the (active) part of the crystal system that varies synchronously with the stimulus can be extracted by an offline analysis, which can only be applied in the case of periodic stimuli and linear system responses. In this paper a new decomposition approach based on multivariate analysis is proposed. The standard principal component analysis (PCA) is adapted to treat MED data: specific figures of merit based on their scores and loadings are found, and the directions of the principal components obtained by PCA are modified to maximize such figures of merit. As a result, a general method to decompose MED data, called optimum constrained components rotation (OCCR), is developed, which produces very precise results on simulated data, even in the case of nonperiodic stimuli and/or nonlinear responses. The multivariate analysis approach is able to supply in one shot both the diffraction pattern related to the active atoms (through the OCCR loadings) and the time dependence of the system response (through the OCCR scores). When applied to real data, OCCR was able to supply only the latter information, as the former was hindered by changes in abundances of different crystal phases, which occurred besides structural variations in the specific case considered. To develop a decomposition procedure able to cope with this combined effect represents the next challenge in MED analysis.

Caliandro, Rocco↗
DOE OSTI2018

Welding Defect Classification from Simulated Ultrasonic Signals

Nondestructive testing is widely used to detect and to size up discontinuities embedded in a material. Among the several ultrasonic techniques, time of flight diffraction (TOFD) combines high speed inspection, high sizing reliability and low rate of incorrect results. However, the classification of defects through ultrasound signals acquired by the TOFD technique depends heavily on the knowledge and experience of the operator and thus, this classification is still frequently questioned. Besides, this task requires long processing time due to the large amount of data to be analyzed. Nevertheless, computational tools for pattern recognition can be employed to analyze a high amount of data with large efficiency. In the present work, simulation of ultrasound propagation in two-dimensional media containing, each one, different kinds of modeled discontinuities which mimic defects in welded joints were performed. Clustering (k-means) and classification (principal component analysis and k-nearest neighbors) algorithms were employed to associate each simulated ultrasound signal with its corresponding modeled defects. The results for each method were analyzed, discussed and compared. The results are very promising.

42 ENGINEERING↗
NASA NTRS1987

The focal plane reception pattern calculation for a paraboloidal antenna with a nearby fence

A computer simulation program is described which is used to estimate the effects of a proximate diffraction fence on the performance of paraboloid antennas. The computer program is written in FORTRAN. The physical problem, mathematical formulation and coordinate references are described. The main control structure of the program and the function of the individual subroutines are discussed. The Job Control Language set-up and program instruction are provided in the user's instruction to help users execute the present program. A sample problem with an appropriate output listing is made available as an illustration of the usage of the program.

Schmidt, Richard F.↗
NASA NTRS2006

Characteristics of Double Exponentially Tapered Slot Antenna (DETSA) Conformed in the Longitudinal Direction Around a Cylindrical Structure

The characteristics of a double exponentially tapered slot antenna (DETSA) as a function of the radius that the DETSA is conformed to in the longitudinal direction is presented. It is shown through measurements and simulations that the radiation pattern of the conformed antenna rotates in the direction through which the antenna is curved, and that diffraction affects the radiation pattern if the radius of curvature is too small or the frequency too high. The gain of the antenna degrades by only 1 dB if the radius of curvature is large and more than 2 dB for smaller radii. The main effect due to curving the antenna is an increased cross-polarization in the E-plane.

Ponchak, George E.↗
DOE OSTI2024

Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks

As an optical processor, a diffractive deep neural network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light propagation through thin optical layers. With sufficient degrees of freedom, D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent light. Similarly, D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination; however, under spatially incoherent light, these transformations are nonnegative, acting on diffraction-limited optical intensity patterns at the input field of view. Here, we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent light. Through simulations, we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products, a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent illumination. The findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. Furthermore, the computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗