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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

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗

Topologically trivial gap-filling in superconducting Fe(Se,Te) by one-dimensional defects

Abstract Structural distortions and imperfections are a crucial aspect of materials science, on the macroscopic scale providing strength, but also enhancing corrosion and reducing electrical and thermal conductivity. At the nanometre scale, multi-atom imperfections, such as atomic chains and crystalline domain walls have conversely been proposed as a route to topological superconductivity, whose most prominent characteristic is the emergence of Majorana Fermions that can be used for error-free quantum computing. Here, we shed more light on the nature of purported domain walls in Fe(Se,Te) that may host 1D dispersing Majorana modes. We show that the displacement shift of the atomic lattice at these line-defects results from sub-surface impurities that warp the topmost layer(s). Using the electric field between the tip and sample, we manage to reposition the sub-surface impurities, directly visualizing the displacement shift and the underlying defect-free lattice. These results, combined with observations of a completely different type of 1D defect where superconductivity remains fully gapped, highlight the topologically trivial nature of 1D defects in Fe(Se,Te).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Raman spectroscopy of neutron irradiated silicon carbide

The effects of neutron irradiation on microstructural evolution and the resultant changes in physical and mechanical properties are of critical importance for the development of silicon carbide (SiC) materials for nuclear applications. This study neutron-irradiated βSiC under a wide range of conditions at temperatures between 235 and 750°C and neutron doses of 0.01–11.8 displacements per atom, and then evaluated the effects on the SiC structure using Raman spectroscopy. The SiC optical phonon lines were shifted to lower wavenumbers by irradiation. Correlations were found among the wavenumber of the longitudinal optical phonon line, irradiation-induced swelling, and irradiation temperature. The peak shift also correlated indirectly with decreasing thermal conductivity of irradiated SiC. The irradiation-induced peak shift is explained by combinations of lattice strain, reduction of the elastic modulus, and other factors including decreasing coherent domain size. These findings bridge irradiation-induced microstructural changes and property changes and illustrate how Raman spectroscopy is a useful tool for nondestructively assessing irradiated SiC materials for nuclear applications.

Koyanagi, T.↗

Domaine-Specific Runtime to Orchestrate Computation on Heterogeneous Platforms

Task-based runtime systems in the past have sought to exploit inherent asynchronicity in the application execution to reduce overall runtime. In the last decade focus shifted to supporting the heterogeneity that is increasingly prevalent in high-performance computing systems. However, existing task-based runtime systems, being general, come with a challenging set of issues such as the complexity of abstractions and overheads. And they still leave much of the burden of exposing the parallelism on the application developers who also have to fit their applications to the runtime systems’ interfaces. In this paper we take a different approach for applications to target heterogeneous systems through domain-specific run-times. Our design aspires to leverage the domain-specific knowledge of a focused class of scientific simulations to pragmatically orchestrate computations in the simulations.

97 MATHEMATICS AND COMPUTING↗

Light-induced transitions of polar state and domain morphology of photoferroelectric nanoparticles

Using the Landau-Ginzburg-Devonshire approach, we study light-induced phase transitions, evolution of polar state and domain morphology in photo-ferroelectric nanoparticles (NPs). Light exposure increases the free carrier density near the NP surface and may in turn induce phase transitions from the nonpolar paraelectric to the polar ferroelectric phase. Using the uniaxial photo-ferroelectric Sn 2 P 2 S 6 as an example, here we show that visible light exposure induces the appearance and vanishing of striped, labyrinthine or curled domains and changes in the polarization switching hysteresis loop shape from paraelectric curves to double, pinched and single loops, as well as the shifting in the position of the tricritical point. Furthermore, we demonstrate that an ensemble of non-interacting photo-ferroelectric NPs may exhibit superparaelectric-like features at the tricritical point, such as strongly frequency-dependent giant piezoelectric and dielectric responses, which can potentially be exploited for piezoelectric applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators

We address the challenge of acoustic simulations in three-dimensional (3D) virtual rooms with parametric source positions, which have applications in virtual/augmented reality, game audio, and spatial computing. The wave equation can fully describe wave phenomena such as diffraction and interference. However, conventional numerical discretization methods are computationally expensive when simulating hundreds of source and receiver positions, making simulations with parametric source positions impractical. To overcome this limitation, we propose using deep operator networks to approximate linear wave-equation operators. This enables the rapid prediction of sound propagation in realistic 3D acoustic scenes with parametric source positions, achieving millisecond-scale computations. By learning a compact surrogate model, we avoid the offline calculation and storage of impulse responses for all relevant source/listener pairs. Our experiments, including various complex scene geometries, show good agreement with reference solutions, with root mean squared errors ranging from 0.02 to 0.10 Pa. Notably, our method signifies a paradigm shift as—to our knowledge—no prior machine learning approach has achieved precise predictions of complete wave fields within realistic domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Emulating ab initio computations of infinite nucleonic matter

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for > 10 6 different parametrizations of a chiral interaction model with explicit Δ -isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He 4 , we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Antiphase-Boundary-Engineered Domain Switching in a (110)-Oriented BiFeO 3 Film

A ferroelectric domain wall memory device exploits the presence (or absence) of domain walls as the basis for information storage. Although structural defects strongly influence ferroelectric domain wall nucleation and growth, this correlation is far from being fully understood. For example, a single defect can play opposing roles: it can act as a nucleation site to initiate domain switching or, conversely, serve as a pinning center inhibiting domain wall motion. This is particularly the case for antiphase boundaries (APBs), whose influence on switching remains relatively unexplored despite being ubiquitous in oxide perovskite ferroelectrics. Here, we use aberration-corrected scanning transmission microscopy and in situ transmission electron microscopy under an applied bias to extensively characterize the influence of an APB on the switching behavior in a (110)-oriented BiFeO 3 thin film. We demonstrate that deterministic nucleation occurs in the proximity of a vertically oriented APB, following which domain growth occurs laterally in a symmetric fashion. Atomic-scale structural analysis reveals that the shear operation vector for the APB is 1/2[110]; this half-unit-cell shift extends over a few nanometers, implying that the APB plane is inclined toward the imaging direction. The symmetric switching observation is attributed to local inhomogeneous lattice strain and a reduction of polarization caused by the APB. These results demonstrate that an extended structural defect can be used as an active switching element rather than a stumbling block in reprogrammable domain-wall-based devices. Ultimately, this will expand the capabilities of ferroelectric thin films for future electronic devices based on ferroelectric domain walls.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Trichomonas vaginalis C2-XYPPX-repeat protein with a structured C2 domain displaying dampened flexibility upon binding calcium

C2 domains are ubiquitous membrane-binding modules of ∼130 residues in eukaryotes that are often associated with proteins involved in membrane trafficking and lipid modification. The genome of Trichomonas vaginalis, the most common, non-viral, sexually transmitted human pathogen, encodes eight genes that contain a N-terminal C2 module linked to a XYPPX-repeat domain of more than four XYPPX repeats (C2-XYPPX). While the function of the XYPPX-repeat domain remains unknown, its multiple association with C2 domains in T. vaginalis suggests it is important. Here, the C2 domain from one of these C2-XYPPX-repeat proteins, Tv-C2-1, was structurally and physically characterized using X-ray crystallography and NMR spectroscopy. The crystal structure for Tv-C2-1 shows that this domain shares a fold common to all C2 domains, a compact Greek-key motif composed of eight anti-parallel β-strands in the type-2 topology. An NMR chemical shift perturbation study with Ca 2+ showed that Tv-C2-1 bound two Ca 2+ atoms primarily via two loops (loop-1 and loop-3) on the predicted calcium binding face of the protein with K d s of 58.0 ± 0.1 μM and 232 ± 6 μM. Estimations of the overall rotational correlation time, τ c , in the apo (11.1 ns) and Ca 2+ -bound (9.2 ns) state suggests the protein becomes more compact upon Ca 2+ binding, consistent with a decrease in dynamics in loop-3 and marginally in loop-1 suggested by amide 15 N heteronuclear steady-state { 1 H}- 15 N NOEs. Showing Tv-C2-1 binds calcium and adopts a compact Greek-key motif structure, two primary features of C2 domains, suggests understanding the function of the XYPPX-repeat domain may be warranted.

NMR spectroscopy↗

Non-conformal interface-cohesive modeling with the shifted boundary method

The accurate simulation of boundary- and interface-dominated problems on complex geometries remains challenging when boundary- or interface-fitted meshes are difficult to generate, particularly for curved boundaries, polycrystalline microstructures, and dense interface networks. The Shifted Boundary Method (SBM) alleviates this meshing burden by shifting the enforcement of boundary conditions from the true boundary to a nearby surrogate boundary and recovering the effect of the true boundary through geometric correction terms, thereby enabling standard finite element spaces on non-boundary-fitted meshes. In this report, we develop a general shiftedboundary and shifted-interface framework within the open-source MOOSE framework. We first present a general SBM implementation for complex geometries on non-boundary-fitted meshes. We then adopt the Shifted Interface Method (SIM) for internal interfaces and develop a unified shifted-interface treatment in which the interface law is enforced on a surrogate interface and the effect of the true interface is recovered through shifted jumps, fluxes, and tractions. This perspective brings scalar thermal-contact and vector-valued cohesive-zone mechanics into a single framework, the latter realized as the Shifted Cohesive Zone Method (SCZM) and coupled with history-dependent constitutive models from NEML2. We further extend the MOOSE mesh infrastructure to support cohesive-zone calculations on distributed meshes. The framework is verified and demonstrated through three progressive studies: Poisson’s equation on a smoothed starshaped domain, a manufactured thermal-contact problem on a non-interface-fitted mesh, and a two-dimensional polycrystalline representative volume element combining crystal plasticity with cohesive grain-boundary interfaces. Across these studies, the shifted formulations reproduce boundary- and interface-fitted reference solutions with high fidelity, indicating that the proposed framework provides an accurate and efficient route to boundary- and interface-dominated simulations on arbitrary geometries without requiring fitted meshes.

Yang, Cheng-Hau↗

Direct aromatization of CO 2 via combined CO 2 hydrogenation and zeolite-based acid catalysis

Aromatics, including benzene, toluene, and xylenes (BTX), are essential chemical building blocks and are widely used as solvents, fuel additives, and polymers. With the recent development in CO 2 capture technologies and the progress made in producing H 2 using renewable energy, direct hydrogenation of CO 2 to aromatics via heterogeneous catalysis has emerged as a promising pathway to accomplish the production of aromatics with simultaneous utilization of waste CO 2 . In this review, we focus on recent advances in the nascent field of direct CO 2 aromatization, whereby tandem catalysts composed of CO 2 hydrogenation and aromatization functionalities are designed and deployed. We review two categories of tandem catalysts: catalysts integrating Fe-based/H-ZSM-5 components following RWGS (reverse water-gas shift of CO 2 to CO)-FT (Fischer-Tropsch synthesis of lower olefins)-aromatization pathways, and catalysts combining metal oxide/H-ZSM-5 domains following CO 2 to methanolaromatization pathways. The key parameters that determine the catalytic performance, such as the composition and structure of the Fe-based or metal oxide-based CO 2 conversion catalysts, the properties of H-ZSM-5, and the synergy between the two components, are analyzed to provide insights for the design of efficient tandem catalysts for CO 2 aromatization. In parallel, thermodynamic analyses, mechanistic studies, and density functional theory (DFT) computations for the relevant reaction routes and pathways are discussed to offer improved understanding of CO 2 activation, reaction intermediates, and product formation. In closing, the challenges and prospects for these tandem reactions are addressed to provide suggested paths forward for future research.

10 SYNTHETIC FUELS↗

Calibration of Distributed Temperature Sensors Using Commercially Available SMF-28 Optical Fiber From 22 °C to 1000 °C

Optical frequency domain reflectometry (OFDR) is a family of optical techniques which can be used to produce distributed temperature measurements from the spectral shift of an interference pattern based on the Rayleigh backscatter signature of an optical fiber. Adaptive signal processing techniques have recently been used with OFDR to record meaningful spectral shift data from commercially available SMF-28 optical fibers heated beyond 950 °C. Furthermore, a correlation between the measured spectral shift and temperature has not yet been developed at these high temperatures. To extend the measurable temperature range of OFDR in SMF-28, this work describes the development of such a correlation from room temperature (22 °C) to 1000 °C. The relationship between spectral shift and temperature change over this range was found to be best characterized by the fourth-order polynomial ΔT=(-4.241 * 10 -11 )S 4 + (-2.017 * 10 -7 )S 3 + (-3.677 * 10 -4 )S 2 + (-0.8057)S, where ΔT represents the temperature difference compared to the reference temperature, and S represents the spectral shift measured by the fibers. The calibration developed in this work assumes that the fiber has been fully annealed by heating the fiber to 1000 °C for a few hours. This paper is the first to demonstrate the calibration and use of SMF-28 distributed optical fiber sensors up to 1000 °C, enabled using adaptive OFDR-based signal processing.

47 OTHER INSTRUMENTATION↗

Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern evades antibody-mediated immunity that comes from vaccination or infection with earlier variants due to accumulation of numerous spike mutations. To understand the Omicron antigenic shift, we determined cryo–electron microscopy and x-ray crystal structures of the spike protein and the receptor-binding domain bound to the broadly neutralizing sarbecovirus monoclonal antibody (mAb) S309 (the parent mAb of sotrovimab) and to the human ACE2 receptor. We provide a blueprint for understanding the marked reduction of binding of other therapeutic mAbs that leads to dampened neutralizing activity. Remodeling of interactions between the Omicron receptor-binding domain and human ACE2 likely explains the enhanced affinity for the host receptor relative to the ancestral virus.

60 APPLIED LIFE SCIENCES↗

A weighted Shifted Boundary Method for free surface flow problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods and was recently introduced for the Poisson, linear advection/diffusion, Stokes, Navier-Stokes, acoustics, and shallow-water equations. By reformulating the original boundary value problem over a surrogate (approximate) computational domain, the SBM avoids integration over cut cells and the associated problematic issues regarding numerical stability and matrix conditioning. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. In this article, we extend the SBM to the simulation of incompressible Navier-Stokes flows with moving free-surfaces, by appropriately weighting its variational form with the elemental volume fraction of active fluid. This approach prevents spurious pressure oscillations in time, which would otherwise be produced if the total active fluid volume were to change abruptly over a time step. In fact, the proposed weighted SBM method induces small mass (i.e., volume) conservation errors, which converge quadratically in the case of piecewise-linear finite element interpolations, as the grid is refined. Finally, we present an extensive set of two- and three-dimensional tests to demonstrate the robustness and accuracy of the method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mechanisms of Metal Additive-Induced Ordering During SNIPS Membrane Formation

Isoporous membranes can be fabricated by combining self-assembly with nonsolvent induced phase separation (SNIPS) using an amphiphilic block copolymer like polystyrene-b-poly(4-vinylpyridine) (SV). Poly(4-vinylpyridine) (V) is known to complex with metal salts, which are hypothesized to stabilize solution ordering and preserve structure during casting. We explored how the molar ratio of metal additive to the poly(4-vinylpyridine) block affected the final membrane morphology via scanning electron microscopy (SEM). Dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), and in situ grazing-incidence SAXS were used to track changes in solution ordering and chain conformation as a function of the molar ratio of the additive to the V block. Additives induced aggregation, promoted the formation of more compact conformations in solution, and facilitated micelle ordering onto lattices at optimal ratios. Furthermore, these experimental results were supported by random phase approximation calculations, which helped explain how the thermodynamic order–disorder transition shifts with additive binding strength. Stronger additive–polymer interactions reduced the block copolymer volume fraction required for ordering in solution, allowing ordered domains to form at lower polymer concentrations.

Additives↗

Using Solid-State NMR to Understand the Structure of Plant Cellulose

The structure of plant cellulose microfibrils remains elusive, despite the abundance of cellulose and its utility in industry. Using 2D solid-state NMR of 13 C-labeled never-dried plants, six major glucose environments are resolved, which are common to the cellulose of softwood, hardwood, and grasses. These environments are maintained in isolated holocellulose nanofibrils, allowing more detailed microfibril characterization. We show that there are only two glucose environments that reside within the microfibril core. These have the same NMR 13 C chemical shifts as tunicate cellulose Iβ center and origin chains, with no cellulose Iα being detected. The third major glucose site within spectral domain 1, previously assigned to the crystalline microfibril interior, is in close proximity to water, which could indicate that it is a surface glucose environment. The NMR peak widths of all four surface glucose environments are similar to those of the core, indicating that their glucose local order is comparable; there is no significant “amorphous” cellulose in the microfibrils. Consequently, the ratio of the carbon 4 peaks at ∼89 and ∼84 ppm, which has often provided a sample cellulose crystallinity index, is not a meaningful measure of fibril crystallinity or the interior to surface ratio. The revised ratio for poplar wood microfibrils is estimated to be 1:2, which is consistent with an 18-chain microfibril having 6 core and 12 surface chains, although other microfibril sizes are possible. These advances substantially change both the interpretation of solid-state NMR studies of cellulose and the understanding of cellulose microfibril structure and crystallinity.

carbohydrates↗

Integrating viruses into soil food web biogeochemistry

The soil microbiome is recognized as an essential component of healthy soils. Viruses are also diverse and abundant in soils, but their roles in soil systems remain unclear. Here we argue for the consideration of viruses in soil microbial food webs and describe the impact of viruses on soil biogeochemistry. The soil food web is an intricate series of trophic levels that span from autotrophic microorganisms to plants and animals. Each soil system encompasses contrasting and dynamic physicochemical conditions, with labyrinthine habitats composed of particles. Conditions are prone to shifts in space and time, and this variability can obstruct or facilitate interactions of microorganisms and viruses. Because viruses can infect all domains of life, they must be considered as key regulators of soil food web dynamics and biogeochemical cycling. Finally, we highlight future research avenues that will enable a more robust understanding of the roles of viruses in soil function and health.

59 BASIC BIOLOGICAL SCIENCES↗