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DOE OSTI2024

High‐speed 4‐dimensional scanning transmission electron microscopy using compressive sensing techniques

Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Robinson, Alex W.↗

NASA NTRS1983

Control of mutual phase locking of monolithically integrated semiconductor lasers

The degree of phase locking between the individual laser apertures is the major issue in phase-locked laser arrays. A description is presented of a series of experiments in which the mutual coherence of two laser apertures is characterized by measuring the visibility of the far-field interference fringes. Attention is given to an approach which makes it possible to control continuously the degree of coherence by means of a separate contact configuration. An investigation was conducted of the far-field radiation patterns of pairs of lasers obtained under various conditions. The results of the present study demonstrate the feasibility of controlling the mutual phase locking between semiconductor lasers by varying the gain distribution between their pumped stripes.

Kapon, E.↗

DOE OSTI2023

Machine Learning Automated Analysis of Enormous Synchrotron X-ray Diffraction Datasets

X-ray diffraction (XRD) data analysis can be a time-consuming and laborious task. Deep neural network (DNN) based models trained with synthetic XRD patterns have been proven to be a highly efficient, accurate, and automated method for analyzing common XRD data collected from solid samples in ambient environments. However, it remains unclear whether synthetic XRD-based models can be effective in solving micro(μ)-XRD mapping data for in situ experiments involving liquid phases, which always have lower quality and significant artifacts. In this study, we collected μ-XRD mapping data from a LaCl 3 -calcite hydrothermal fluid system and trained two categories of models to analyze the experimental XRD patterns. Here, the models trained solely with synthetic XRD patterns showed low accuracy (as low as 64%) when solving experimental μ-XRD mapping data. However, the accuracy of the DNN models significantly improved (90% or above) when we trained them with a data set containing both synthetic and a small number of labeled experimental μ-XRD patterns. This study highlights the importance of labeled experimental patterns in training DNN models to solve μ-XRD mapping data from in situ experiments involving liquid phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mapping causal patterns in crystalline solids

The evolution of the atomic structures of the combinatorial library of Sm-substituted thin film BiFeO 3 along the phase transition boundary from the ferroelectric rhombohedral phase to the non-ferroelectric orthorhombic phase is explored using scanning transmission electron microscopy. Localized properties, including polarization, lattice parameter, and chemical composition, are parameterized from atomic-scale imaging, and their causal relationships are reconstructed using a linear non-Gaussian acyclic model. This approach is further extended to explore the spatial variability of the causal coupling using the sliding window transform method, which revealed that new causal relationships emerged at both the expected locations, such as domain walls and interfaces, and at additional regions forming clusters in the vicinity of the walls or spatially distributed features. While the exact physical origins of these relationships are unclear, they likely represent nanophase-separated regions in the morphotropic phase boundaries. Overall, we posit that an in-depth understanding of complex disordered materials away from thermodynamic equilibrium necessitates understanding not only the generative processes that can lead to observed microscopic states but also the causal links between multiple interacting subsystems.

Causal inference↗

DOE OSTI2025

Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

CMIP6↗

NASA NTRS1975

A study of phase transitions in lead difluoride by use of polychromatic X-ray diffraction

A polychromatic X-ray diffraction technique was used to obtain patterns of alpha-PbF2 and beta-PbF2. The results obtained at room temperature and 314 C at 1 atm, and at room temperature at 5.5 kbar, are in good agreement with published data. The advantages of the technique for high-temperature and high-pressure work are discussed.

Mahajan, V. K.↗

NASA NTRS1987

Dynamic characteristics of far-field radiation of current modulated phase-locked diode laser arrays

A versatile and powerful streak camera/frame grabber system for studying the evolution of the near and far field radiation patterns of diode lasers was assembled and tested. Software needed to analyze and display the data acquired with the steak camera/frame grabber system was written and the total package used to record and perform preliminary analyses on the behavior of two types of laser, a ten emitter gain guided array and a flared waveguide Y-coupled array. Examples of the information which can be gathered with this system are presented.

Elliott, R. A.↗

DOE OSTI2024

Theoretical and experimental analysis of the modulated phase grating X-ray interferometer

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated phase grating (MPG) interferometer is a recently developed grating interferometry system capable of generating a directly resolvable interference pattern using a relatively large period grating envelope function that is sampled at a pitch that is small enough that X-ray spatial coherence can be achieved by using a microfocus X-ray source or G0 grating. We present the theory of the MPG interferometry system for a 2-dimensional staggered grating, derived using Fourier optics, and we compare the theoretical predictions with experiments we have performed with a microfocus X-ray system at Pennington Biomedical Research Center, LSU. The theoretical and experimental fringe visibility is evaluated as a function of grating-to-detector distance. Additionally, quantitative experiments are performed with porous carbon and alumina compounds, and the mean normalized dark-field signal is compared with independent porosimetry measurements. Qualitative analysis of attenuation and dark-field images of a dried anchovy are shown.

47 OTHER INSTRUMENTATION↗

NASA NTRS2012

Low-Gain Circularly Polarized Antenna with Torus-Shaped Pattern

The Juno mission to Jupiter requires an antenna with a torus-shaped antenna pattern with approximately 6 dBic gain and circular polarization over the Deep Space Network (DSN) 7-GHz transmit frequency and the 8-GHz receive frequency. Given the large distances that accumulate en-route to Jupiter and the limited power afforded by the solar-powered vehicle, this toroidal low-gain antenna requires as much gain as possible while maintaining a beam width that could facilitate a +/-10deg edge of coverage. The natural antenna that produces a toroidal antenna pattern is the dipole, but the limited approx. = 2.2 dB peak gain would be insufficient. Here a shaped variation of the standard bicone antenna is proposed that could achieve the required gains and bandwidths while maintaining a size that was not excessive. The final geometry that was settled on consisted of a corrugated, shaped bicone, which is fed by a WR112 waveguide-to-coaxial- waveguide transition. This toroidal low-gain antenna (TLGA) geometry produced the requisite gain, moderate sidelobes, and the torus-shaped antenna pattern while maintaining a very good match over the entire required frequency range. Its "horn" geometry is also low-loss and capable of handling higher powers with large margins against multipactor breakdown. The final requirement for the antenna was to link with the DSN with circular polarization. A four-layer meander-line array polarizer was implemented; an approach that was fairly well suited to the TLGA geometry. The principal development of this work was to adapt the standard linear bicone such that its aperture could be increased in order to increase the available gain of the antenna. As one increases the aperture of a standard bicone, the phase variation across the aperture begins to increase, so the larger the aperture becomes, the greater the phase variation. In order to maximize the gain from any aperture antenna, the phase should be kept as uniform as possible. Thus, as the standard bicone fs aperture increases, the gain increase becomes less until one reaches a point of diminishing returns. In order to overcome this problem, a shaped aperture is used. Rather than the standard linear bicone, a parabolic bicone was found to reduce the amount of phase variation as the aperture increases. In fact, the phase variation is half of the standard linear bicone, which leads to higher gain with smaller aperture sizes. The antenna pattern radiated from this parabolic-shaped bicone antenna has fairly high side lobes. The Juno project requested that these sidelobes be minimized. This was accomplished by adding corrugations to the parabolic shape. This corrugated-shaped bicone antenna had reasonably low sidelobes, and the appropriate gain and beamwidth to meet project requirements.

Amaro, Luis R.↗

DOE OSTI2022

Charge-ordered state satisfying the Anderson condition in LiRh 2 O 4 arising from local dimer order

Here we report on the charge-ordered structure of LiRh 2 O 4 arising below the metal-insulator transition at 170 K. Structural studies using synchrotron x rays have revealed that the charge-ordered states of Rh 3+ and Rh 4+ with dimerization are realized in the low-temperature phase below 170 K. Although the low-temperature ground state resembles that of CuIr 2 S 4 , a charge-ordering pattern satisfying the Anderson condition is realized in LiRh 2 O 4 . Based on structural information such as the short-range order of dimers appearing above the transition temperature and the weakening of the correlation between rhodium one-dimensional chains appearing in the crystal structure, we argue that the Coulomb interaction plays an important role in determining the charge-ordering patterns.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Analysis of the Amplitude Response of a Two-Point and a Multi-Point Focused Laser Differential Interferometer

Experiments were performed with two different focused laser differential interferometer (FLDI) instruments to assess the relative amplitude response of each instrument to a traveling shockwave generated by a laser spark in air. The first FLDI instrument generated two slightly-separated measurement points, with each measurement point providing sensitivity to density fluctuations induced by the shockwave. By performing a cross-correlation between the signals obtained from each measurement point, the phase velocity of density fluctuations can be obtained. The second FLDI instrument generated a measurement line that was oriented parallel to the shockwave direction of travel with the resulting interference pattern sampled at multiple equally-spaced points along the line. As a result, this instrument provides density fluctuation measurement capability at multiple points simultaneously. When the measurement line is oriented parallel to the shockwave direction of travel, the phase velocity, rate of change of the phase velocity, and acceleration of density fluctuations traveling along each line can be obtained by performing a cross-correlation between points along the line. Numerical computations of the shockwave generated by the laser spark are used to simulate the response of each instrument and are compared to the experimental results. High-speed schlieren imaging has also been performed and is compared with the FLDI measurements and computational results.

Brett F. Bathel↗

NASA NTRSDate not supplied

Analysis of the Amplitude Response of a Two-Point and a Multi-Point Focused Laser Differential Interferometer

Interferometry↗

NASA NTRSDate not supplied

Quantum-Assisted Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

The quantum computing community has been searching for suitable applications to demonstrate the potential of near-term quantum devices. Quantum machine learning is a potential candidate, particularly using models that cannot be efficiently simulated with classical computers [1, 2]. This work focuses on a transition phase of quantum computers where the quantum machine learning model is still simulable classically but projected not to be simulable as the size of the model grows. Ultimately quantum computers may have advantages for high-dimensional real-world problems. Due to the limited number of qubits in current noisy intermediate-scale quantum (NISQ) devices, the direct application of quantum computers in high dimensional data is not feasible. To remedy this problem, an encoder-decoder architecture can be utilized. The encoder model would transform the high-dimensional data into a compact representation, to a level that small quantum computers can be used today (or in the near future), and the decoder would take the quantum processed outputs back to the high-dimensional space. Addressing the two challenges of quantum machine learning, this work investigates a hybrid supervised generative model with a quantum Ising Born machine embedded as the latent distribution. The model contains four main parts (Figure 1.a.): (1) a U-NET architecture responsible for learning segmentation flow, (2) a Prior network responsible for learning an encoded latent distribution of the input data, (3) a Born machine which represents the latent distribution, and (4) a Posterior network in charge of learning the joint encoded latent distribution of inputs and target data. The initial model, proposed by [3], is optimized by (1) maximizing the overlap of the prior and posterior latent distributions, and (2) minimizing the segmentation loss. The proposed model is designed to be investigated in a simulation environment applied to the real-world application of wildfire segmentation. Specifically, the model is designed to solve the patchy wildfire segmentations of Moderate Resolution Imaging Spectroradiometer (MODIS) by taking the MODIS observations and using Visible Infrared Imaging Radiometer Suite’s (VIIRS) consistent wildfire product as the target. The model solves patchy wildfire segmentations and provides insight into the epistemic errors sourced from model variation. The model utilizes the Born machine as a QUBO solver to represent the latent space as a Bernoulli distribution. The proposed configuration allows the variational segmentation model to leverage the true quantum probabilistic nature and derive a more expressive latent configuration, increasing the model performance in describing wildfire segmentations. The quantum probabilistic information of the Born machine is directly incorporated in the Kullback-Leibler divergence loss in the prior and posterior distributions, forcing the Bernoulli latent distribution to maximize the overlap of input and joint input-target distributions. The proposed model is then trained and compared with a baseline only consisting of direct Bernoulli latent distribution with no Born machine representing the latent space. The models are evaluated based on the segmentation metrics, such as precision, recall, intersect of union, with uncertainty boundaries accounting for the stochastic nature of the model. Our findings show that even in low latent-dimensional space (due to the limit in computational power of the classical quantum simulator), we are able to effectively capture the latent representation and hence the model performs better than the baseline. The findings are a projection for scaling the model into higher dimensional latent space with the Born machine surpassing the baseline performance. Figure 1. Sub-figure (a) demonstrates the architecture for the training phase. The model consists of a Prior and Posterior network that encode inputs and joint input-target data into compact representations, respectively. The Born machine represents the latent distribution, and the U-NET branch learns the segmentation patterns of the data. The stochasticity is introduced to the U-NET through its last layer to create meaningful but stochastic segmentations. Sub-figure (b) represents the inference phase where the model takes the stochastic behavior from the prior network and injects that into the U-NET. Each attempt of inference will generate different but similar segmentations from the same distribution of the wildfire event. REFERENCES [1] Coyle, B., Mills, D., Danos, V., & Kashefi, E. (2020). The Born supremacy: quantum advantage and training of an Ising Born machine. npj Quantum Information, 6(1), 1-11. [2] Liu, J. G., & Wang, L. (2018). Differentiable learning of quantum circuit born machines. Physical Review A, 98(6), 062324. [3] Kohl, S., Romera-Paredes, B., Meyer, C., De Fauw, J., Ledsam, J. R., Maier-Hein, K., ... & Ronneberger, O. (2018). A probabilistic u-net for segmentation of ambiguous images. Advances in neural information processing systems, 31.

quantum machine learning↗

NASA NTRS1985

The development of the new Be phase of 59 Cyg in the visual and in the far UV in 1978-1983

A tentative synthesis of visual and IUE observations of 59 Cyg during 1978-1983 when the new Be phase began to develop is presented. The study reveals correlation between those spectral features originating in the cool H-alpha-emitting envelope and features originating in superionized regions exhibiting C IV and N V lines. The long-term variability patterns of the V/R ratio, the H-alpha emission, and the C IV absorption reveal striking similarities and a close correlation. The early development of the new Be phase is accompanied by remarkably large and striking C IV line-profile changes. It is also suggested that short-term V/R variations at H-alpha may be associated with short-term C IV changes.

Doazan, V.↗

DOE OSTI2022

The Madden–Julian Oscillation in the Energy Exascale Earth System Model Version 1

Abstract The present study examines the characteristics of the Madden–Julian Oscillation (MJO) events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and moist static energy (MSE) anomalies associated with the MJO. As in observations, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MJO MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the precipitation diurnal cycle. On the MJO impact over the midlatitude, E3SMv1 reasonably captures the pattern of the MJO teleconnections across the North Pacific and North America, with improvement in the performance in a high‐resolution version, despite the magnitude being a bit weaker than the observed. Regarding the interannual variability of the MJO, the El Niño‐Southern Oscillation (ENSO) modulation of the zonal extent of MJO’s eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, are well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi‐Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process‐oriented diagnostics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Multiquanta flux jumps in superconducting fractal

We study the magnetic field response of millimeter scale fractal Sierpinski gaskets (SG) assembled of superconducting equilateral triangular patches. Directly imaged quantitative induction maps reveal hierarchical periodic filling of enclosed void areas with multiquanta magnetic flux, which jumps inside the voids in repeating bundles of individual flux quanta Φ 0 . The number N s of entering flux quanta in different triangular voids of the SG is proportional to the linear size s of the void, while the field periodicity of flux jumps varies as 1/s. We explain this behavior by modeling the triangular voids in the SG with effective superconducting rings and by calculating their response following the London analysis of persistent currents, J s , induced by the applied field H a and by the entering flux. With changing H a , J s reaches a critical value in the vertex joints that connect the triangular superconducting patches and allows the giant flux jumps into the SG voids through phase slips or multiple Abrikosov vortex transfer across the vertices. The unique flux behavior in superconducting SG patterns, may be used to design tunable low-loss resonators with multi-line high-frequency spectrum for microwave technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Moiré commensurability and the quantum anomalous Hall effect in twisted bilayer graphene on hexagonal boron nitride

The quantum anomalous Hall (QAH) effect is sometimes observed in twisted bilayer graphene (tBG) when it is nearly aligned with an encapsulating hexagonal boron nitride (hBN) layer. We propose that the appearance or absence of the QAH effect in individual devices could be related to commensurability between the graphene/graphene and graphene/hBN moiré patterns. We identify a series of points in the (θ GG , θ GBN ) twist-angle space at which the two moiré patterns are commensurate, allowing moiré band theory to be applied, and we show that the band Chern numbers are in this case sensitive to a rigid in-plane hBN displacement. Given this property, we argue that the QAH effect is likely only when (i) the (θ GG , θ GBN ) twist-angle-pair is close enough to a commensurate point that the two moiré patterns yield a supermoiré pattern with a sufficiently long length scale, and (ii) the supermoiré has a percolating topologically nontrivial QAH phase. For twist angles far from commensurability, the hBN layer acts as a source of disorder that can destroy the QAH effect. Our proposal can explain a number of current experimental observations. Finally, further experimental studies that can test this proposal more directly are suggested.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Czochralski growth and characterization of the multicomponent garnet (Lu 1/4 Yb 1/4 Y 1/4 Gd 1/4 ) 3 Al 5 O 12

This work demonstrates the potential for practical scalable growth of complex garnets and evaluates the implications of a multicomponent composition in the optical quality and elemental distribution of a Czochralski-grown crystal. Furthermore, our experimental approach was designed to elucidate the relation between a complex garnet composition ( Lu 1 / 4 Yb 1 / 4 Y 1 / 4 Gd 1 / 4 ) 3 Al 5 O 12 , crystal growth parameters, crystal structural, and elemental homogeneity. Our hypothesis is that combining multiple rare earths (REs) that will fractionally occupy the dodecahedral site in the aluminum garnet structure will result in a stable, single garnet compound that can be grown by the Czochralski method. Single-crystal and powder x-ray diffraction indicated a single garnet phase with an increasing unit cell volume from seed to tail. In addition, we propose that the pattern of elemental segregation will be based on the deviation of the ionic radius of each constituent RE from the average RE ionic radius of the multicomponent garnet. Electron probe microanalysis revealed that ions that are smaller than that average ( Lu 3 + and Yb 3 + ) are preferentially incorporated in the crystal, while elements that are larger than that average ( Gd 3 + ) are rejected. The ionic radius of Y 3 + is close to that average and yttrium segregation was minimal. The concentrations of the four REs are closer to stoichiometric on the tail end of the boule. Scanning electron microscopy and energy-dispersive x-ray spectroscopy analysis reveal Gd-rich inclusions with eutectic microstructures in the tail end of the boule.

36 MATERIALS SCIENCE↗