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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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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Operando neutron diffraction reveals mechanisms for controlled strain evolution in 3D printing

Abstract Residual stresses affect the performance and reliability of most manufactured goods and are prevalent in casting, welding, and additive manufacturing (AM, 3D printing). Residual stresses are associated with plastic strain gradients accrued due to transient thermal stress. Complex thermal conditions in AM produce similarly complex residual stress patterns. However, measuring real-time effects of processing on stress evolution is not possible with conventional techniques. Here we use operando neutron diffraction to characterize transient phase transformations and lattice strain evolution during AM of a low-temperature transformation steel. Combining diffraction, infrared and simulation data reveals that elastic and plastic strain distributions are controlled by motion of the face-centered cubic and body-centered cubic phase boundary. Our results provide a new pathway to design residual stress states and property distributions within additively manufactured components. These findings will enable control of residual stress distributions for advantages such as improved fatigue life or resistance to stress-corrosion cracking.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Learning diffractive optical communication around arbitrary opaque occlusions

Abstract Free-space optical communication becomes challenging when an occlusion blocks the light path. Here, we demonstrate a direct communication scheme, passing optical information around a fully opaque, arbitrarily shaped occlusion that partially or entirely occludes the transmitter’s field-of-view. In this scheme, an electronic neural network encoder and a passive, all-optical diffractive network-based decoder are jointly trained using deep learning to transfer the optical information of interest around the opaque occlusion of an arbitrary shape. Following its training, the encoder-decoder pair can communicate any arbitrary optical information around opaque occlusions, where the information decoding occurs at the speed of light propagation through passive light-matter interactions, with resilience against various unknown changes in the occlusion shape and size. We also validate this framework experimentally in the terahertz spectrum using a 3D-printed diffractive decoder. Scalable for operation in any wavelength regime, this scheme could be particularly useful in emerging high data-rate free-space communication systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diffractive optical computing in free space

Abstract Structured optical materials create new computing paradigms using photons, with transformative impact on various fields, including machine learning, computer vision, imaging, telecommunications, and sensing. This Perspective sheds light on the potential of free-space optical systems based on engineered surfaces for advancing optical computing. Manipulating light in unprecedented ways, emerging structured surfaces enable all-optical implementation of various mathematical functions and machine learning tasks. Diffractive networks, in particular, bring deep-learning principles into the design and operation of free-space optical systems to create new functionalities. Metasurfaces consisting of deeply subwavelength units are achieving exotic optical responses that provide independent control over different properties of light and can bring major advances in computational throughput and data-transfer bandwidth of free-space optical processors. Unlike integrated photonics-based optoelectronic systems that demand preprocessed inputs, free-space optical processors have direct access to all the optical degrees of freedom that carry information about an input scene/object without needing digital recovery or preprocessing of information. To realize the full potential of free-space optical computing architectures, diffractive surfaces and metasurfaces need to advance symbiotically and co-evolve in their designs, 3D fabrication/integration, cascadability, and computing accuracy to serve the needs of next-generation machine vision, computational imaging, mathematical computing, and telecommunication technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonlinear reversal of photoexcitation on the attosecond time scale improves ultrafast X-ray diffraction images

The complex refractive index of a material governs its light-matter interactions, with intense light fields enabling tailored nonlinear optical responses. In the X-ray regime, rapid photoionization limits the potential of nonlinear techniques by inducing irreversible electronic damage. Here we demonstrate that intense, sub-femtosecond X-ray pulses, shorter than typical Auger decay times, can partially reverse photoexcitation via stimulated emission near atomic resonances. By analyzing thousands of coherent diffraction patterns and ion spectra from neon nanoparticles exposed to sub-fs and 15-fs pulses, we observe enhanced X-ray diffraction alongside reduced energy absorption for sub-fs pulses. Theoretical modeling attributes this to dynamics akin to Rabi flopping that prolong the lifetime of resonant states and suppress electronic bleaching. These findings suggest that ultrashort, intense X-ray pulses enable active control of X-ray refractive index and damage pathways, opening avenues for improved high-resolution imaging and nonlinear spectroscopy in complex nanoscale systems.

Ulmer, Anatoli [Universität Hamburg (Germany)] (OR↗
DOE OSTI2021

Deep learning for visualization and novelty detection in large X-ray diffraction datasets

Abstract We apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations learned by a VAE reveal latent information, such as the structural similarity of textured diffraction patterns. While other artificial intelligence (AI) agents are effective at classifying XRD data into known phases, a similarly conditioned VAE is uniquely effective at knowing what it doesn’t know: it can rapidly identify data outside the distribution it was trained on, such as novel phases and mixtures. These capabilities demonstrate that a VAE is a valuable AI agent for aiding materials discovery and understanding XRD measurements both ‘on-the-fly’ and during post hoc analysis.

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↗
DOE OSTI2024

Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction

Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in a low signal-to-noise ratio and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O 3 . Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Laguerre–Gauss and Hermite–Gauss soft X-ray states generated using diffractive optics

Light’s capacity to carry angular momentum is integral to our knowledge of physics and ability to probe matter. In addition to spin, photons can occupy free-space orbital angular momentum eigenstates. Visible light orbital angular momentum is used in quantum information experiments, super-resolution microscopy, optical tweezers and angular momentum transfer to atoms in optical lattices. Soft X-ray orbital angular momentum applications, slowed by the lack of suitable optics and the rarity of coherent X-ray sources, could enable the direct alteration of atomic states through orbital angular momentum exchange, and methods to study the electronic properties of quantum materials. We have made soft X-ray diffractive optics that generate single Laguerre–Gauss modes, observed carrying up to 30$\hbar$ angular momentum per photon, or their superpositions. We also present Hermite–Gauss diffractive optics and a soft X-ray orbital angular momentum analyser. Finally, these tools could enable both the manipulation and finer characterization of topologically complex electronic matter, such as magnetic skyrmions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Diffraction data from aerosolized Coliphage PR772 virus particles imaged with the Linac Coherent Light Source

Single Particle Imaging (SPI) with intense coherent X-ray pulses from X-ray free-electron lasers (XFELs) has the potential to produce molecular structures without the need for crystallization or freezing. Here we present a dataset of 285,944 diffraction patterns from aerosolized Coliphage PR772 virus particles injected into the femtosecond X-ray pulses of the Linac Coherent Light Source (LCLS). Additional exposures with background information are also deposited. The diffraction data were collected at the Atomic, Molecular and Optical Science Instrument (AMO) of the LCLS in 4 experimental beam times during a period of four years. The photon energy was either 1.2 or 1.7 keV and the pulse energy was between 2 and 4 mJ in a focal spot of about 1.3 μm x 1.7 μm full width at half maximum (FWHM). The X-ray laser pulses captured the particles in random orientations. The data offer insight into aerosolised virus particles in the gas phase, contain information relevant to improving experimental parameters, and provide a basis for developing algorithms for image analysis and reconstruction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Single-shot structural analysis by high-energy X-ray diffraction using an ultrashort all-optical source

High-energy X-rays (HEX-rays) with photon energies on order of 100 keV have attractive characteristics, such as comparably low absorption, high spatial resolution and the ability to access inner-shell states of heavy atoms. These properties are advantageous for many applications ranging from studies of bulk materials to the investigation of materials in extreme conditions. Ultrafast X-ray diffraction allows the direct imaging of atomic dynamics simultaneously on its natural time and length scale. However, using HEX-rays for ultrafast studies has been limited due to the lack of sources that can generate pulses of sufficiently short (femtosecond) duration in this wavelength range. Here we show single-crystal diffraction using ultrashort ~90 keV HEX-ray pulses generated by an all-optical source based on inverse Compton scattering. We also demonstrate a method for measuring the crystal lattice spacing in a single shot that contains only ~10 5 photons in a spectral bandwidth of ~50% full width at half maximum (FWHM). Our approach allows us to obtain structural information from the full X-ray spectrum. As target we use a cylindrically bent Ge crystal in Laue transmission geometry. As a result, this experiment constitutes a first step towards measurements of ultrafast atomic dynamics using femtosecond HEX-ray pulses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Sparse recovery of undersampled intensity patterns for coherent diffraction imaging at high X-ray energies

Coherent X-ray photons with energies higher than 50 keV offer new possibilities for imaging nanoscale lattice distortions in bulk crystalline materials using Bragg peak phase retrieval methods. However, the compression of reciprocal space at high energies typically results in poorly resolved fringes on an area detector, rendering the diffraction data unsuitable for the three-dimensional reconstruction of compact crystals. To address this problem, we propose a method by which to recover fine fringe detail in the scattered intensity. This recovery is achieved in two steps: multiple undersampled measurements are made by in-plane sub-pixel motion of the area detector, then this data set is passed to a sparsity-based numerical solver that recovers fringe detail suitable for standard Bragg coherent diffraction imaging (BCDI) reconstruction methods of compact single crystals. The key insight of this paper is that sparsity in a BCDI data set can be enforced by recognising that the signal in the detector, though poorly resolved, is band-limited. This requires fewer in-plane detector translations for complete signal recovery, while adhering to information theory limits. Lastly, we use simulated BCDI data sets to demonstrate the approach, outline our sparse recovery strategy, and comment on future opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Impact and mitigation of angular uncertainties in Bragg coherent x-ray diffraction imaging

Bragg coherent diffraction imaging (BCDI) is a powerful technique to explore the local strain state and morphology of microscale crystals. The method can potentially reach nanometer-scale spatial resolution thanks to the advances in synchrotron design that dramatically increase coherent flux. However, there are experimental bottlenecks that may limit the image reconstruction quality from future high signal-to-noise ratio measurements. In this work we show that angular uncertainty of the sample orientation with respect to a fixed incoming beam is one example of such a factor, and we present a method to mitigate the resulting artifacts. On the basis of an alternative formulation of the forward problem, we design a phase retrieval algorithm which enables the simultaneous reconstruction of the object and determination of the exact angular position corresponding to each diffraction pattern in the data set. We have tested the algorithm performance on simulated data for different degrees of angular uncertainty and signal-to-noise ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Raman and X-ray diffraction study of pressure-induced phase transition in synthetic Mg 2 TiO 4

Synthetic Mg 2 TiO 4 qandilite was investigated to 50 and 40.4 GPa at room temperature using Raman spectroscopy and X-ray diffraction, respectively. The Raman measurements showed that cubic Mg 2 TiO 4 spinel transforms to a high pressure tetragonal (I4 1 /amd, No.141) phase at 14.7 GPa. Owing to sluggish kinetics at room temperature, the spinel phase coexists with the tetragonal phase between 14.7 and 24.3 GPa. In the X-ray diffraction experiment, transformation of the cubic Mg 2 TiO 4 to the tetragonal structure was complete by 29.2 GPa, ~5 GPa higher than the transition pressure obtained by Raman measurements, owing to slow kinetics. The obtained isothermal bulk modulus of Mg 2 TiO 4 spinel is K T0 = 148(3) GPa when K T0 ’ = 6.6, or K T0 = 166(1) GPa when K T0 ’ is fixed at 4. The isothermal bulk modulus of the high-pressure tetragonal phase is calculated to be 209(2) GPa and V 0 = 270(2) Å 3 when K T0 ’ is fixed at 4, and the volume reduction on change from cubic to tetragonal phase is about 9%. The calculated thermal Grüneisen parameters (γ th ) of cubic and tetragonal Mg 2 TiO 4 phases are 1.01 and 0.63. Based on the radii ratio of spinel cations, a simple model is proposed to predict post-spinel structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-beam X-ray ptychography for high-throughput coherent diffraction imaging

X-ray ptychography is a rapidly developing coherent diffraction imaging technique that provides nanoscale resolution on extended field-of-view. However, the requirement of coherence and the scanning mechanism limit the throughput of ptychographic imaging. Herein, we propose X-ray ptychography using multiple illuminations instead of single illumination in conventional ptychography. Multiple locations of the sample are simultaneously imaged by spatially separated X-ray beams, therefore, the obtained field-of-view in one scan can be enlarged by a factor equal to the number of illuminations. We have demonstrated this technique experimentally using two X-ray beams focused by a house-made Fresnel zone plate array. Two areas of the object and corresponding double illuminations were successfully reconstructed from diffraction patterns acquired in one scan, with image quality similar with those obtained by conventional single-beam ptychography in sequence. Multi-beam ptychography approach increases the imaging speed, providing an efficient way for high-resolution imaging of large extended specimens.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Correlating work hardening with co-activation of stacking fault strengthening and transformation in a high entropy alloy using in-situ neutron diffraction

Transformation induced plasticity (TRIP) leads to enhancements in ductility in low stacking fault energy (SFE) alloys, however to achieve an unconventional increase in strength simultaneously, there must be barriers to dislocation motion. While stacking faults (SFs) contribute to strengthening by impeding dislocation motion, the contribution of SF strengthening to work hardening during deformation is not well understood; as compared to dislocation slip, twinning induced plasticity (TWIP) and TRIP. Thus, we used in-situ neutron diffraction to correlate SF strengthening to work hardening behavior in a low SFE Fe 40 Mn 20 Cr 15 Co 20 Si 5 (at%) high entropy alloy, SFE ~ 6.31 mJ m –2 . Cooperative activation of multiple mechanisms was indicated by increases in SF strengthening and γ-f.c.c. → ε-h.c.p. transformation leading to a simultaneous increase in strength and ductility. The present study demonstrates the application of in-situ, neutron or X-ray, diffraction techniques to correlating SF strengthening to work hardening.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A spatial beam property analyzer based on dispersive crystal diffraction for low-emittance X-ray light sources

Abstract The advent of low-emittance synchrotron X-ray sources and free-electron lasers urges the development of novel diagnostic techniques for measuring and monitoring the spatial source properties, especially the source sizes. This work introduces an X-ray beam property analyzer based on a multi-crystal diffraction geometry, including a crystal-based monochromator and a Laue crystal in a dispersive setting to the monochromator. By measuring the flat beam and the transmitted beam profiles, the system can provide a simultaneous high-sensitivity characterization of the source size, divergence, position, and angle in the diffraction plane of the multi-crystal system. Detailed theoretical modeling predicts the system’s feasibility as a versatile characterization tool for monitoring the X-ray source and beam properties. The experimental validation was conducted at a bending magnet beamline at the Swiss Light Source by varying the machine parameters. A measurement sensitivity of less than 10% of a source size of around 12 µm is demonstrated. The proposed system offers a compact setup with simple X-ray optics and can also be utilized for monitoring the electron source.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor-corresponding to dilation and two potential rigid body rotations of the unit cell. All three components are in principle resolvable through a spatially mapped sample tilt series; however, traditional data analysis is computationally expensive and prone to artifacts. In this study, we implement NanobeamNN, a convolutional neural network specifically tailored to the analysis of scanning probe X-ray microscopy data. NanobeamNN learns lattice strain and rotation angles from simulated diffraction of a focused X-ray nanobeam by an epitaxial thin film and can directly make reasonable predictions on experimental data without the need for additional fine-tuning. We demonstrate that this approach represents a significant advancement in computational speed over conventional methods, as well as a potential improvement in accuracy over the current standard.

Luo, Aileen [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2025

Atomic-scale insights into topotactic transformations in an extra-large-pore zeolite using time-resolved 3D electron diffraction

Understanding the atomic-scale structural dynamics of phase transformations is crucial for developing materials and tailoring their properties. However, many materials are obtained as polycrystalline powders with large unit cells and/or complex structures, making it challenging to investigate detailed structural changes using conventional X-ray diffraction techniques. Here we employ time-resolved three-dimensional electron diffraction to reveal the topotactic reactions and transformations that convert the extra-large-pore silicate zeolite ECNU-45 into ECNU-46. ECNU-45 features three-dimensional interconnecting 24 × 10 × 10-ring channels, while ECNU-46 consists of one-dimensional 24-ring channels connected to 10-ring pockets. ECNU-45 and ECNU-46 are both examples of pure silicate zeolites with pore openings larger than 22-ring. Our findings indicate changes at six distinct tetrahedral silicon sites, involving atom displacement, addition and removal of framework atoms through bond breakage and formation. This work presents the synthesis of zeolites and also provides atomic-level insights into the dynamic processes of topotactic reactions. Our results have implications for advancing materials engineering and understanding complex solid-state reactions at an atomic scale.

Inorganic chemistry↗