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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Real-space imaging of periodic nanotextures in thin films via phasing of diffraction data

New properties and exotic quantum phenomena can form due to periodic nanotextures, including Moire patterns, ferroic domains, and topologically protected magnetization and polarization textures. Despite the availability of powerful tools to characterize the atomic crystal structure, the visualization of nanoscale strain-modulated structural motifs remains challenging. Here, we develop nondestructive real-space imaging of periodic lattice distortions in thin epitaxial films and report an emergent periodic nanotexture in a Mott insulator. Specifically, we combine iterative phase retrieval with unsupervised machine learning to invert the diffuse scattering pattern from conventional X-ray reciprocal-space maps into real-space images of crystalline displacements. Our imaging in PbTiO 3 /SrTiO 3 superlattices exhibiting checkerboard strain modulation substantiates published phase-field model calculations. Furthermore, the imaging of biaxially strained Mott insulator Ca 2 RuO 4 reveals a strain-induced nanotexture comprised of nanometer-thin metallic-structure wires separated by nanometer-thin Mott-insulating-structure walls, as confirmed by cryogenic scanning transmission electron microscopy (cryo-STEM). The nanotexture in Ca 2 RuO 4 film is induced by the metal-to-insulator transition and has not been reported in bulk crystals. We expect the phasing of diffuse X-ray scattering from thin crystalline films in combination with cryo-STEM to open a powerful avenue for discovering, visualizing, and quantifying the periodic strain-modulated structures in quantum materials.

Science & Technology - Other Topics↗
DOE OSTI2021

Real Space Imaging of Spin Stripe Domain Fluctuations in a Complex Oxide

Understanding the formation and dynamics of charge and spin-ordered states in low-dimensional transition metal oxide materials is crucial to understanding unconventional high-temperature superconductivity. La 2-x Sr x NiO 4+δ (LSNO) has attracted much attention due to its interesting spin dynamics. Recent x-ray photon correlation spectroscopy studies have revealed slow dynamics of the spin order (SO) stripes in LSNO. Here, we applied resonant soft x-ray ptychography to map the spatial distribution of the SO stripe domain inhomogeneity in real space. The reconstructed images show the SO domains are spatially anisotropic, in agreement with previous diffraction studies. For the SO stripe domains, it is found that the correlation lengths along different directions are strongly coupled in space. Surprisingly, fluctuations were observed in the real space amplitude signal, rather than the phase or position. Overall, we attribute the observed slow dynamics of the stripe domains in LSNO to thermal fluctuations of the SO domain boundaries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Real-Space Imaging of the Tailored Plasmons in Twisted Bilayer Graphene

Here, we report a systematic plasmonic study of twisted bilayer graphene (TBLG)—two graphene layers stacked with a twist angle. Through real-space nanoimaging of TBLG single crystals with a wide distribution of twist angles, we find that TBLG supports confined infrared plasmons that are sensitively dependent on the twist angle. At small twist angles, TBLG has a plasmon wavelength comparable to that of single-layer graphene. At larger twist angles, the plasmon wavelength of TBLG increases significantly with apparently lower damping. Further analysis and modeling indicate that the observed twist-angle dependence of TBLG plasmons in the Dirac linear regime is mainly due to the Fermi-velocity renormalization, a direct consequence of interlayer electronic coupling. Our work unveils the tailored plasmonic characteristics of TBLG and deepens our understanding of the intriguing nano-optical physics in novel van der Waals coupled two-dimensional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Reciprocal space imaging of ionic correlations in intercalation compounds

The intercalation of alkali ions into layered materials has played an indispensable role in battery technology since the development of the first lithium-ion electrodes. Coulomb repulsion between the intercalants leads to ordering of the intercalant sublattice, which hinders ionic diffusion and impacts battery performance. While conventional diffraction can identify the long-range order that can occur at discrete intercalant concentrations during the charging cycle, it cannot determine short-range order at other concentrations that also disrupt ionic mobility. In this Article, we show that the use of real-space transforms of single-crystal diffuse scattering, measured with high-energy synchrotron X-rays, allows a model-independent measurement of the temperature dependence of the length scale of ionic correlations along each of the crystallographic axes in sodium-intercalated V 2 O 5 . The techniques described here provide a new way of probing the evolution of structural ordering in crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Real-space imaging of the electron-pair density hole in molecular Auger–Meitner decay

Electrons in matter can rearrange extremely quickly under external perturbations, underpinning subsequent structural and chemical transformations. Coulomb interactions between neighbouring electrons often shape this response, giving rise to correlated motion and strongly affecting the distribution of electrons in the system. Here we show that non-resonant hard X-ray scattering can directly access changes in the radial electron-pair density during the rapid rearrangement of core and valence electrons. We do this by studying sulfur hexafluoride molecules undergoing Auger–Meitner decay. We exploit a second-order interaction between the X-ray photons and the molecules to trigger and probe the decay dynamics with a single pulse, capturing the electron loss and redistribution before the molecules dissociate. The experiment shows that changes in electron-pair densities can be isolated and measured on ultrafast timescales, providing insight into the real-space evolution of highly excited and short-lived electronic states.

Simmermacher, Mats [University of Oxford (United K↗
DOE OSTI2024

Operando real-space imaging of a structural phase transformation in the high-voltage electrode LixNi0.5Mn1.5O4

Abstract Discontinuous solid-solid phase transformations play a pivotal role in determining the properties of rechargeable battery electrodes. By leveraging operando Bragg Coherent Diffractive Imaging (BCDI), we investigate the discontinuous phase transformation in Li x Ni 0.5 Mn 1.5 O 4 within an operational Li metal coin cell. Throughout Li-intercalation, we directly observe the nucleation and growth of the Li-rich phase within the initially charged Li-poor phase in a 500 nm particle. Supported by the microelasticity model, the operando imaging unveils an evolution from a curved coherent to a planar semi-coherent interface driven by dislocation dynamics. Our data indicates negligible kinetic limitations from interface propagation impacting the transformation kinetics, even at a discharge rate of C/2 (80 mA/g). This study highlights BCDI’s capability to decode complex operando diffraction data, offering exciting opportunities to study nanoscale phase transformations with various stimuli.

Sun, Yifei (ORCID:0000000295625120)↗
DOE OSTI2025

Real Space Imaging of Field-Driven Decision-Making in Nanomagnetic Galton Boards

A possible spintronic route to hardware implementation for decision-making involves injecting a domain wall into a bifurcated magnetic nanostrip resembling a Y-shaped junction. A decision is made when the domain wall chooses a particular path through the bifurcation. Recently, it was shown that a structure like a nanomagnetic Galton board, which is essentially an array of interconnected Y-shaped junctions, produces outcomes that are stochastic and therefore relevant to artificial neural networks. However, the exact mechanism leading to the robust nature of randomness is unknown. Here, in this study, we directly image the decision-making process in nanomagnetic Galton boards using Lorentz transmission electron microscopy. We identify that the stochasticity in nanomagnetic Galton boards arises as a culmination of (1) the topology of the injected domain wall, (2) dissimilarly sized vertices, and (3) the strength of the applied field. Our results pave the way to a detailed understanding of stochasticity in nanomagnetic networks.

lorentz microscopy↗
DOE OSTI2019

Design of a free-space image-relay optical time-domain reflectometer to measure fiber-optic time delays at inertial confinement fusion relevant wavelengths

Fiber optics are an integral part of data collection, often used to transport visible and UV light to streaked spectrometers and photodetectors. Precisely measuring fiber-optic time delay (FOTD) is necessary for absolute data timing or fiber replacement. An optical time domain reflectometer (OTDR) can be used to measure the fiber-optic time delay. Commercial OTDR’s measure only the fiber in telecommunications wavelengths in the IR. To measure fibers at relevant wavelengths for inertial confinement fusion experiments, a solution using a free-space image relay was devised at the University of Rochester’s Laboratory for Laser Energetics (LLE), where readily available equipment has been used to measure the FOTD to within 2 ps at 526.5 nm as well as 351 nm, which is an order of magnitude better than the timing jitter between LLE’s Hardware Timing System and second-harmonic (526.5-nm) fiducial laser pulses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Hubble Space Telescope Imaging of Three Isolated Faint Dwarf Galaxies beyond the Local Group: Pavo, Corvus A, and Kamino

We present new Hubble Space Telescope (HST) imaging of three recently discovered star-forming dwarf galaxies beyond the Local Group: Pavo, Corvus A, and Kamino. The discovery of Kamino is reported here for the first time. They rank among the most isolated faint dwarf galaxies known; hence they provide unique opportunities to study galaxy evolution at the smallest scales, free from the environmental effects of more massive galaxies. Our HST data reach ∼2–4 magnitudes below the tip of the red giant branch (TRGB) for each dwarf, allowing us to measure their distances, structural properties, and recent star formation histories (SFHs). All three galaxies contain a complex stellar population of young and old stars, and are typical of field galaxies in this mass regime (M V = −10.62 ± 0.08 and $D = 2.16_{-0.07}^{+0.08}$ Mpc for Pavo, M V = −10.91 ± 0.10 and D = 3.34 ± 0.11 Mpc for Corvus A, and M V = −12.02 ± 0.12 and $D = 6.50_{-0.11}^{+0.15}$ Mpc for Kamino). Our HST-derived SFHs reveal differences among the three dwarfs: Pavo and Kamino show relatively steady, continuous star formation, while Corvus A formed ∼60% of its stellar mass by 10 Gyr ago. These results align with theoretical predictions of diverse evolutionary pathways for isolated low-mass galaxies.

Mutlu-Pakdil, Burçin [Dartmouth College, Hanover, ↗
DOE OSTI2019

Adaptive Grid Lens Modeling of the Cosmic Horseshoe Using Hubble Space Telescope Imaging

The Cosmic Horseshoe gravitational lensing system is an extraordinary example of strong gravitational lensing both due to the nearly complete Einstein ring formed in this system and due to the star-forming nature of the lensed $z$ = 2.38 Lyman-break galaxy. In this paper, we describe the development of a new lens modeling package and the lens models produced using the Hubble Space Telescope imaging. Our new lens modeling package uses adaptive grid methods, based especially on the algorithm described by Vegetti & Koopmans. The new lens modeling package introduces the K-means method to deal with multiple background sources. We utilize two parameterized models, the singular isothermal ellipsoid and the Navarro–Frenk–White model in order to optimize the Bayesian penalty function. Color–color diagrams show two distinct colors exist in the Einstein ring, which suggests that the Cosmic Horseshoe is formed from two background galaxies or from a highly irregular galaxy. We find that the best lens model includes two components and the total mass within the Einstein ring is $(5.43\pm 0.08)\times {10}^{12}\,{M}_{\odot }$. Furthermore, the background source reconstruction shows two peaks in the source plane and the most probable lens profile is consistent with the light profile of the foreground galaxy when comparing axis ratios and position angles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Anisotropic nano-scale resolution in 3D Bragg coherent diffraction imaging

We demonstrate that the resolution of three-dimensional (3D) real-space images obtained from Bragg coherent x-ray diffraction measurements is direction dependent. We propose and demonstrate the effectiveness of a metric to determine the spatial resolution of images that accounts for the directional dependence. The measured direction dependent resolution of ~4-9 nm is higher than the best previously obtained 3D measurements. Lastly, we quantify the relationship between the resolution of recovered real-space images and dosage and discuss its implications in the light of next generation synchrotrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Low Size, Weight, and Power Space-Based Imaging System

The proposed low-SWAP solution is a FPA focus mechanism which is composed of an actuator motor, attached to a flexure that holds the camera sensor while imaging. The mechanism, while moderately complex, allows for large changes in the focal plane while also maintaining the ability to make small adjustments to produce the best possible data. This solution does the best job at accounting for thermal gradients within the optical components that tend to degrade the image quality.

42 ENGINEERING↗
DOE OSTI2018

High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs

Abstract—Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from spec-imen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of 10 to 103 depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗