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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Developing an ELM Ecosystem Dynamics Model on GPU with OpenACC

Porting a complex scientific code, such as the E3SM land model (ELM), onto a new computing architecture is challenging. The paper presents design strategies and technical approaches to develop an ELM ecosystem dynamics model with compiler directives (OpenACC) on NVIDIA GPUs. The code has been refactored with advanced OpenACC features (such as deepcopy and routine directives) to reduce memory consumption and to increase the levels of parallelism through parallel loop reconstruction and new data structures. As a result, the optimized parallel implementation achieved more than a 140-time speedup (50 ms vs 7600 ms), compared to a naive implementation that uses OpenACC routine directive and parallelizes the code across existing loops on a single NVIDIA V100. On a fully loaded computing node with 44 CPUs and 6 GPUs, the code achieved over a 3.0-times speedup, compared to the original code on the CPU. Furthermore, the memory footprint of the optimized parallel implementation is 300 MB, which is around 15% of the 2.15 GB of memory consumed by a naive implementation. This study is the first effort to develop the ELM component on GPUs efficiently to support ultra-high-resolution land simulations at continental scales.

Schwartz, Peter↗
DOE OSTI2023

Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering

Myelinated axons (nerve fibers) efficiently transmit signals throughout the brain via action potentials. Multiple methods that are sensitive to axon orientations, from microscopy to magnetic resonance imaging, aim to reconstruct the brain's structural connectome. As billions of nerve fibers traverse the brain with various possible geometries at each point, resolving fiber crossings is necessary to generate accurate structural connectivity maps. However, doing so with specificity is a challenging task because signals originating from oriented fibers can be influenced by brain (micro)structures unrelated to myelinated axons. X-ray scattering can specifically probe myelinated axons due to the periodicity of the myelin sheath, which yields distinct peaks in the scattering pattern. Here, in this work, we show that small-angle X-ray scattering (SAXS) can be used to detect myelinated, axon-specific fiber crossings. We first demonstrate the capability using strips of human corpus callosum to create artificial double- and triple-crossing fiber geometries, and we then apply the method in mouse, pig, vervet monkey, and human brains. We compare results to polarized light imaging (3D-PLI), tracer experiments, and to outputs from diffusion MRI that sometimes fails to detect crossings. Given its specificity, capability of 3-dimensional sampling and high resolution, SAXS could serve as a ground truth for validating fiber orientations derived using diffusion MRI as well as microscopy-based methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding Instability in Formamidinium Lead Halide Perovskites: Kinetics of Transformative Reactions at Grain and Subgrain Boundaries

Transformative and reconstructive reactions impart significant structural changes at particle boundaries of hybrid perovskites, which influence environmental stability and optoelectronic properties of these materials. Here, we investigate the moisture-induced transformative reactions in formamidinium based perovskites FAPbX 3 (X=I, Br) and show that the ambient stability of these materials can be adjusted from a few hours to several months. For FAPbI 3 , roles of water vapor, particle size, and light illumination on the kinetic pathways of the cubic (a) transformation to the hexagonal (d) phase are analyzed by X-ray diffraction, optical microscopy, photoluminescence and solid-state NMR spectroscopy techniques. The grain and sub-grain boundaries exhibit different α→δ-FAPbI 3 phase transformation kinetics. Our study suggests that the dynamic transformation involves the local water-induced dissolution of the cubic phase occurring at the crystal surfaces followed by precipitation of the hexagonal phase. Insights into structures and dynamics of a kinetically trapped α-|δ-FAPbI 3 are obtained by 1 H, 2 H, and 207 Pb ssNMR spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep learning-based segmentation of lithium-ion battery microstructures enhanced by artificially generated electrodes

Accurate 3D representations of lithium-ion battery electrodes, in which the active particles, binder and pore phases are distinguished and labeled, can assist in understanding and ultimately improving battery performance. Here, we demonstrate a methodology for using deep-learning tools to achieve reliable segmentations of volumetric images of electrodes on which standard segmentation approaches fail due to insufficient contrast. We implement the 3D U-Net architecture for segmentation, and, to overcome the limitations of training data obtained experimentally through imaging, we show how synthetic learning data, consisting of realistic artificial electrode structures and their tomographic reconstructions, can be generated and used to enhance network performance. We apply our method to segment x-ray tomographic microscopy images of graphite-silicon composite electrodes and show it is accurate across standard metrics. We then apply it to obtain a statistically meaningful analysis of the microstructural evolution of the carbon-black and binder domain during battery operation.

25 ENERGY STORAGE↗
DOE OSTI2024

Modeling Si/SiGe quantum dot variability induced by interface disorder reconstructed from multiperspective microscopy

SiGe heteroepitaxial growth yields pristine host material for quantum dot qubits, but residual interface disorder can lead to qubit-to-qubit variability that might pose an obstacle to reliable SiGe-based quantum computing. By convolving data from scanning tunneling microscopy and high-angle annular dark field scanning transmission electron microscopy, we reconstruct 3D interfacial atomic structure and employ an atomistic multi-valley effective mass theory to quantify qubit spectral variability. The results indicate (1) appreciable valley splitting (VS) variability of ~50% owing to alloy disorder and (2) roughness-induced double-dot detuning bias energy variability of order 1–10 meV depending on well thickness. For measured intermixing, atomic steps have negligible influence on VS, and uncorrelated roughness causes spatially fluctuating energy biases in double-dot detunings potentially incorrectly attributed to charge disorder. Our approach yields atomic structure spanning orders of magnitude larger areas than post-growth microscopy or tomography alone, enabling more holistic predictions of disorder-induced qubit variability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Sub-10 second fly-scan nano-tomography using machine learning

Abstract X-ray computed tomography is a versatile technique for 3D structure characterization. However, conventional reconstruction algorithms require that the sample not change throughout the scan, and the timescale of sample dynamics must be longer than the data acquisition time to fulfill the stable sample requirement. Meanwhile, concerns about X-ray-induced parasite reaction and sample damage have driven research efforts to reduce beam dosage. Here, we report a machine-learning-based image processing method that can significantly reduce data acquisition time and X-ray dose, outperforming conventional approaches like Filtered-Back Projection, maximum-likelihood, and model-based maximum-a-posteriori probability. Applying machine learning, we achieve ultrafast nano-tomography with sub-10 second data acquisition time and sub-50 nm pixel resolution in a transmission X-ray microscope. We apply our algorithm to study dynamic morphology changes in a lithium-ion battery cathode under a heating rate of 50 o C min −1 , revealing crack self-healing during thermal annealing. The proposed method can be applied to various tomography modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electronic signatures of successive itinerant, antiferromagnetic transitions in hexagonal La 2 Ni 7

We use high-resolution angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) calculations to study the electronic and magnetic properties of La 2 Ni 7 , an itinerant magnetic system with a series of three magnetic transition temperatures upon cooling, which end in a small moment antiferromagnetic (smAFM) ground state. Our APRES data reveal several electron and hole pockets that have hexagonal symmetry near the Γ point. We observe significant reconstruction of the band structure upon successive magnetic transitions at T 1 ~ 61 K, T 2 ~ 57 K and T 3 ~ 42 K. Several features observed in ARPES data were reasonably well reproduced by DFT calculations, while others were not. In particular, the flat band near E f predicted by DFT in AFM state, was seemingly absent in ARPES data. Our results detail the effects of magnetic ordering on the electronic structure in a Ni-based small moment antiferromagnet and highlight challenges of current computational methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Phase diagram of CeSb 2 from magnetostriction and magnetization measurements: Evidence for ferrimagnetic and antiferromagnetic states

Cerium diantimonide (CeSb 2 ) is one of a family of rare-earth-based magnetic materials that exhibit metamagnetism, enabling control of the magnetic ground state through an applied magnetic field. At low temperatures, CeSb 2 hosts a rich phase diagram with multiple magnetically ordered phases for many of which the order parameter is only poorly understood. In this work, we report a study of its metamagnetic properties by scanning tunneling microscopy (STM) and magnetization measurements. We use STM measurements to characterize the sample magnetostriction with subpicometer resolution from magnetic field and temperature sweeps. This allows us to directly assess the bulk phase diagram as a function of field and temperature and relate spectroscopic features from tunneling spectroscopy to bulk phases. Our magnetostriction and magnetization measurements indicate that the low-temperature ground state at zero field is ferrimagnetic. Quasiparticle interference mapping shows evidence for a reconstruction of the electronic structure close to the Fermi energy upon entering the magnetically ordered phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Reconstructing quintessence

We present an Effective Field Theory based reconstruction of quintessence models of dark energy directly from cosmological data. We show that current cosmological data possess enough constraining power to test several quintessence model properties for redshifts z ϵ [0, 1.5] with no assumptions about the behavior of the scalar field potential. We use measurements of the cosmic microwave background, supernovae distances, and the clustering and lensing of galaxies to constrain the evolution of the dark energy equation of state, Swampland Conjectures, the shape of the scalar field reconstructed potential, and the structure of its phase space. The standard cosmological model still remains favored by data and, within quintessence models, deviations from its expansion history are bounded to be below the 10% level at 95% confidence at any redshift below z = 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

On the holographic dual of a topological symmetry operator

We study the holographic dual of a topological symmetry operator in the context of the AdS/CFT correspondence. Symmetry operators arise from topological field theories localized on a subspace of the boundary conformal field theory spacetime. We use bottom up considerations to construct the topological sector associated with their bulk counterparts. In particular, by exploiting the structure of entanglement wedge reconstruction we argue that the bulk counterpart has a nontopological world volume action, i.e., it describes a dynamical object. As a consequence, we find that there are no global 𝑝-form symmetries for 𝑝 ≥ 0 in asymptotically anti–de Sitter spacetimes, which includes the case of noninvertible symmetries. Provided one has a suitable notion of subregion-subregion duality, our argument for the absence of bulk global symmetries applies to more general spacetimes. These considerations also motivate us to consider for general QFTs (holographic or not) the notion of lower-form symmetries, namely, (−𝑚)-form symmetries for 𝑚 ≥ 2.

quantum gravity↗
DOE OSTI2022

Biochemical and Regulatory Analyses of Xylanolytic Regulons in Caldicellulosiruptor bescii Reveal Genus-Wide Features of Hemicellulose Utilization

Microbial deconstruction of lignocellulose for the production of biofuels and chemicals requires the hydrolysis of heterogeneous hemicelluloses to access the microcrystalline cellulose portion. This work extends previous in vivo and in vitro efforts to characterize hemicellulose utilization by integrating genomic reconstruction, transcriptomic data, operon structures, and biochemical characteristics of key enzymes to understand the deployment and functionality of hemicellulases by the extreme thermophile Caldicellulosiruptor bescii .

Biotechnology & Applied Microbiology↗
DOE OSTI2021

TARDIS. II. Synergistic Density Reconstruction from Lyα Forest and Spectroscopic Galaxy Surveys with Applications to Protoclusters and the Cosmic Web

Looking at this work, we expand upon the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS) in order to include multiple tracers while reconstructing matter density fields at Cosmic Noon (z ~ 2–3). In particular, we jointly reconstruct the underlying density field from simulated Lyα forest observations at z ~ 2.5 and an overlapping galaxy survey. We find that these data are synergistic, with the Lyα forest providing reconstruction of low-density regions and galaxy surveys tracing the density peaks. We find a more accurate power spectra reconstruction going to higher scales when fitting these two data sets simultaneously than when using either one individually. When applied to cosmic web analysis, we find that performing the joint analysis is equivalent to an Lγα survey with significantly increased sight-line spacing. Because we reconstruct the velocity field and matter field jointly, we demonstrate the ability to evolve the mock observed volume further to z = 0, allowing us to create a rigorous definition of a “protocluster” as regions that will evolve into clusters. We apply our reconstructions to study protocluster structure and evolution, finding for realistic survey parameters that we can provide accurate mass estimates of the z ≈ 2 structures and their z = 0 fate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Galaxy–Galaxy Strong Lensing Cross Section and the Internal Distribution of Matter in ΛCDM Substructure

Abstract Strong gravitational lensing offers a powerful probe of the detailed distribution of matter in lenses, while magnifying and bringing faint background sources into view. Observed strong lensing by massive galaxy clusters, which are often in complex dynamical states, has also been used to map their dark matter (DM) substructures on smaller scales. Deep high-resolution imaging has revealed the presence of strong lensing events associated with these substructures, namely galaxy-scale sub-halos. However, an inventory of these observed galaxy–galaxy strong lensing (GGSL) events is noted to be discrepant with state-of-the-art ΛCDM simulations. Cluster sub-halos appear to be over-concentrated compared to their simulated counterparts yielding an order-of-magnitude higher value of GGSL. In this paper, we explore the possibility of resolving this observed discrepancy by redistributing the mass within observed cluster sub-halos in ways that are consistent within the ΛCDM paradigm of structure formation. Lensing mass reconstructions from data provide constraints on the mass enclosed within apertures and are agnostic to the detailed mass profile within them. Therefore, as the detailed density profile within cluster sub-halos currently remains unconstrained by data, we are afforded the freedom to redistribute the enclosed mass. We investigate if rearranging the mass to a more centrally concentrated density profile helps alleviate the GGSL discrepancy. We report that refitting cluster sub-halos to the ubiquitous ΛCDM-motivated Navarro–Frenk–White profile, and further modifying them to include significant baryonic components, does not resolve this tension. A resolution to this persisting GGSL discrepancy may require more careful exploration of alternative DM models.

Astronomy & Astrophysics↗
DOE OSTI2025

Dual roles of stepped surfaces: Catalytic initiators and stabilizers of oxygen-induced reconstructions

Understanding surface restructuring under reactive conditions is crucial for designing next-generation catalysts with enhanced activity and selectivity. Here, we employ in situ transmission electron microscopy to directly observe the dynamic behavior of Cu(100) and Cu(410) surfaces under both oxidizing and vacuum annealing conditions, revealing a complex interplay among surface crystallography, local oxygen coverage, Cu atom mobility, and step-edge reactivity. The stepped Cu(410) surface acts as an active site for O 2 dissociation, triggering the oscillatory transformation of the c(2 × 2)–O phase into the more stable (2$\sqrt2$ ×$\sqrt2$)R45°–O missing-row (MR) structure on the adjacent flat Cu(100) terrace. Under subsequent vacuum annealing, this same Cu(410) facet exhibits remarkable structural resilience, preserving the MR reconstruction and chemisorbed oxygen. In contrast, the Cu(100) surface undergoes reversible transitions from the MR structure back to the c(2 × 2)–O phase. These results highlight the critical role of surface morphology in directing both the formation and stability of oxygen-induced reconstructions, demonstrating that stepped surfaces serve dual roles as both catalytic initiators and structural stabilizers. Furthermore, this work offers atomic-level insights into the environment-responsive behavior of copper surfaces, establishing a mechanistic basis for designing Cu-based catalysts through facet-specific control of surface reactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Facile diamond synthesis from lower diamondoids

Carbon-based nanomaterials have exceptional properties that make them attractive for a variety of technological applications. Here, we report on the use of diamondoids (diamond-like, saturated hydrocarbons) as promising precursors for laser-induced high-pressure, high-temperature diamond synthesis. The lowest pressure and temperature $(P-T)$ conditions that yielded diamond were 12 GPa (at ~2000 K) and 900 K (at ~20 GPa), respectively. This represents a substantially reduced transformation barrier compared with diamond synthesis from conventional (hydro)carbon allotropes, owing to the similarities in the structure and full sp 3 hybridization of diamondoids and bulk diamond. At 20 GPa, diamondoid-to-diamond conversion occurs rapidly within <19 μs. Molecular dynamics simulations indicate that once dehydrogenated, the remaining diamondoid carbon cages reconstruct themselves into diamond-like structures at high $P-T$. This study is the first successful mapping of the $P-T$ conditions and onset timing of the diamondoid-to-diamond conversion and elucidates the physical and chemical factors that facilitate diamond synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-Defect Detection in Additively Manufactured Lattice Structures Using 3D Electrical Resistance Tomography

Cellular lattice structures possess high strength-to-weight ratios suitable for advanced lightweight engineering applications. However, their quality and mechanical performance can degrade because of defects introduced during manufacturing or in-service. Their complexity and small length scale features make defects difficult to detect using conventional nondestructive evaluation methods. Here we propose a current injection-based method, electrical resistance tomography (ERT), that can be used to detect damaged struts in conductive cellular lattice structures with their intrinsic electromechanical properties. The reconstructed conductivity distributions from ERT can reveal the severity and location of damaged struts without having to probe each strut. However, the low central sensitivity of ERT may result in image artifacts and inaccurate localization of damaged struts. To address this issue, this study introduces an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT. The algorithm incorporates a strut-based normalized sensitivity map to compensate for lower interior sensitivity and suppresses reconstruction artifacts. Numerical simulations and experiments on fabricated representative cellular lattice structures were performed to verify the ability of ERT to quantitatively identify single and multiple damaged struts. The improved performance of this method compared with classical ERT was observed, based on greatly decreased imaging and reconstructed value errors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles

Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging because of the strong attenuation of the x-ray beam by the uranium core, leading to severe photon starvation in a substantial fraction of the measurements. Furthermore, the overall acquisition time for a high-resolution CT scan can be very long when using conventional laboratory-based x-ray systems and reconstruction algorithms. Specifically, when analytic methods such as the Feldkamp–Davis–Kress (FDK) algorithm are used for reconstruction, it results in severe streak artifacts and noise in the corresponding 3D volume, which makes subsequent analysis of the particles challenging. In this paper, we develop and apply model-based image reconstruction (MBIR) algorithms to improve the quality of CT reconstructions for TRISO particles to facilitate better characterization. We demonstrate that the proposed MBIR algorithms can significantly suppress artifacts with minimal pre-processing compared to conventional approaches. We also demonstrate that the proposed MBIR approach can obtain high-quality reconstruction compared to the FDK approach even when using a fraction of the typically acquired measurements, thereby enabling dramatically faster measurement times for TRISO particles.

Venkatakrishnan, Singanallur↗