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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Magnetochiral tunneling in paramagnetic Co 1/3 NbS 2

Electric currents have the intriguing ability to induce magnetization in nonmagnetic crystals with sufficiently low crystallographic symmetry. Some associated phenomena include the non-linear anomalous Hall effect in polar crystals and the nonreciprocal directional dichroism in chiral crystals when magnetic fields are applied. In this work, we demonstrate that the same underlying physics is also manifested in the electronic tunneling process between the surface of a nonmagnetic chiral material and a magnetized scanning probe. In the paramagnetic but chiral metallic compound Co 1/3 NbS 2 , the magnetization induced by the tunneling current is shown to become detectable by its coupling to the magnetization of the tip itself. This results in a contrast across different chiral domains, achieving atomic-scale spatial resolution of structural chirality. To support the proposed mechanism, we used first-principles theory to compute the chirality-dependent current-induced magnetization and Berry curvature in the bulk of the material. Our demonstration of this magnetochiral tunneling effect opens up an avenue for investigating atomic-scale variations in the local crystallographic symmetry and electronic structure across the structural domain boundaries of low-symmetry nonmagnetic crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules ( e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Scattering of lower hybrid radio frequency waves by cylindrical turbulent structures in the plasma edge in tokamaks

Lower hybrid (LH) radio frequency (RF) waves are used in fusion tokamak devices to generate non-inductively toroidal currents. LH waves are effective in imparting toroidal momentum to electrons in the core of the confined plasma. Since the LH waves are generated by wave guide structures near the wall of a tokamak, the waves have to propagate through a turbulent plasma in the edge region before coupling to the core. It is especially important to quantify the effect of this plasma region on the propagation characteristics of the LH waves, since fusion reactors like ITER will have an extended edge region. Structures in the plasma edge like filaments and blobs which have highly varying density fluctuations compared to the background density, span radial spatial scales that are comparable to the LH wavelength. We study the scattering of the LH waves by the filamentary structures using Maxwell's equations, in which the plasma permittivity is given by the cold plasma dispersion tensor. The collisional absorption of LH waves in the edge region is included by a modification to the elements of the dispersion tensor. The filaments are assumed to be cylindrical with the axis predominantly aligned along the direction of the toroidal magnetic field. Our studies are both analytical and numerical [1,2] and show that these structures can lead to reflection, refraction, diffraction, and side-scattering of both an incident LH plane wave and a Gaussian beam. We will present a variety of different density variations and collisional absorption rates in plasmas with filamentary structures of varying sizes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Harnessing structural stochasticity in the computational discovery and design of microstructures

This paper presents a deep generative model-based design methodology for tailoring the structural stochasticity of microstructures. Although numerous methods have been established for designing deterministic (periodic) or stochastic microstructures, a systematic design approach that allows the unified treatment of both deterministic and stochastic microstructure design domains has yet to be created. The proposed methodology resolves this issue by learning a unified feature space that embodies diverse structural patterns with continuously varying stochasticity levels. A highly diverse microstructure database is established to incorporate various types of deterministic and stochastic microstructure patterns. A property-aware deep generative model is proposed to learn a unified feature space of the structural characteristics, as well as the relationship between structure features and properties of interest. Autoencoder (AE), Variational Autoencoder (VAE), and Adversarial Autoencoder (AAE) are compared to understand their relative merits in the property-aware learning of the unified feature space. Microstructural designs with tailorable stochasticity and properties are obtained by searching the unified feature space. Multiple design cases are presented to demonstrate the capability of designing microstructures for structural stochasticity and properties. Furthermore, the proposed method is employed to create stochastically graded structures, which manipulate the mechanical behaviors by varying the local stochasticity of the structure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chiral Kirigami for Bend‐Tolerant Reconfigurable Hologram with Continuously Variable Chirality Measures

Abstract Despite the commonality of static holograms, the holography with multiple information layers and reconfigurable grey‐scale images at communication frequencies remain a confluence of scientific challenges. One well‐known difficulty is the simultaneous modulation of phase and amplitude of electromagnetic wavefronts with a high modulation depth. A less appreciated challenge is scrambling of the information and images with hologram bending. Here, this work shows that chirality‐guided pixelation of plasmonic kirigami sheets enables tunable multiplexed holography at terahertz (THz) frequencies. The convex and concave structures with slanted Au strips exhibit gradual variations in geometries facilitating modulation of light ellipticity reaching 40 deg. Real‐time switching of 3D images of the letter “ M ” and the Mona Lisa demonstrates the possibility of complex grey‐scale information content and importance of continuously variable mirror asymmetry. Microscale chirality measures of each pixel experiences little change with bending while retaining controllable reconfigurability upon stretching, which translates to remarkable resilience of chiral holograms to bending. Simplicity of their design with local chirality measures opens the door to information technologies with fault‐tolerant THz encryption, wearable holographic devices, and new communication technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of dietary fiber fermentation on short‐chain fatty acid production and microbial composition in vitro

Abstract BACKGROUND The efficient utilization of fiber‐rich co‐products is important for optimizing feed resource utilization and animal health. This study was conducted to evaluate the fermentation characteristics of fiber‐rich co‐products, which had equal quantities of total dietary fiber (TDF), at different time points using batch in vitro methods. It considered their gas production, short‐chain fatty acid (SCFA) production, and microbial composition. RESULTS The fermentation of wheat bran (WB) and oat bran (OB) showed higher and faster ( P < 0.05) gas and SCFA production than corn bran (CB), sugar beet pulp (SBP), and soybean hulls (SH). The α ‐diversity was higher in the CB, SBP, and SH groups than in the WB and OB groups ( P < 0.05). At the phylum level, OB and WB fermentation showed lower ( P < 0.05) relative abundance of Actinobacteria than the CB, SBP, and SH groups. At the genus level, OB and WB fermentation increased the Enterococcus population in comparison with the CB, SBP, and SH groups, whereas CB and SBP fermentation improved the relative abundance of the Christensenellaceae R‐7 group more than the WB, OB, and SH groups ( P < 0.05). CONCLUSION Overall, WB and OB were rapidly fermented by fecal microbiota, in contrast with SBP, SH, and CB. Fermentation of different fiber‐rich co‐products with an equal TDF content gives different responses in terms of microbial composition and SCFA production due to variations in their physicochemical properties and molecular structure. © 2020 Society of Chemical Industry

Bai, Yu↗
DOE OSTI2022

Brown-York charges at null boundaries

The Brown-York stress tensor provides a means for defining quasilocal gravitational charges in subregions bounded by a timelike hypersurface. We consider the generalization of this stress tensor to null hypersurfaces. Such a stress tensor can be derived from the on-shell subregion action of general relativity associated with a Dirichlet variational principle, which fixes an induced Carroll structure on the null boundary. The formula for the mixed-index tensor T i j takes a remarkably simple form that is manifestly independent of the choice of auxiliary null vector at the null surface, and we compare this expression to previous proposals for null Brown-York stress tensors. The stress tensor we obtain satisfies a covariant conservation equation with respect to any connection induced from a rigging vector at the hypersurface, as a result of the null constraint equations. For transformations that act covariantly on the boundary structures, the Brown-York charges coincide with canonical charges constructed from a version of the Wald-Zoupas procedure. For anomalous transformations, the charges differ by an intrinsic functional of the boundary geometry, which we explicity verify for a set of symmetries associated with finite null hyper-surfaces. Applications of the null Brown-York stress tensor to symmetries of asymptotically flat spacetimes and celestial holography are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Synthesis, characterization, and thermodynamic study of selected K-based zeolites

Potassium-rich zeolites often occur in cementitious systems, as K{sup +} is widespread in various cementitious materials, such as Portland, blended and alkali-activated cements. The knowledge of their stability and of thermodynamic models for solid solutions with Na{sup +} and Ca{sup 2+} are critical to understand long-term development and durability in such cements. Completing previous studies on Na- and Ca-based zeolites, the current work aims to determine the thermodynamic data of 14 types of K-based zeolites, which could possibly form in cementitious systems. The zeolites were synthesized hydrothermally, exchanged with K{sup +}, and characterized thoroughly with respect to framework structures, elemental compositions, water contents, and bond variations. Their thermodynamic properties were derived from the experimental solubility data, which allowed establishing predominance diagrams in the K{sub 2}O-SiO{sub 2}-Al{sub 2}O{sub 3}-H{sub 2}O system. The K-based zeolites typically showed the lowest solubility between 0 and 100 °C, with the notable exception of Ca-gismondine and two Na-based zeolites: natrolite and Na-mordenite.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding interfacial crystallization dynamics on carbon fiber reinforced polypropylene composite manufacturing

Reinforcing polymers with discontinuous fibers improves mechanical properties, such as strength and stiffness, and in some cases achieve isotropic properties, rendering them suitable for various engineering applications. Matrix materials are generally highly engineered thermosets (e.g. crosslinked epoxies), bonded to the fiber periphery by proprietary surface and sizing chemistries. Semicrystalline thermoplastic matrices are less utilized due to poor fiber-matrix bonding resulting in inefficient interfacial load-transfer in reinforced composites. However, flexibility with melt-processing or molding conditions can be leveraged to promote non-covalent interfacial bonding between matrix and fiber via crystallization of the matrix onto fiber surface. In the present study, we utilize a co-mingle chopped carbon and isotactic polypropylene fibers to form isotropic composites, tailoring interfacial immobilized matrix or interphase morphology to optimize performance through precise control of thermal processing/molding windows. Calorimetry and optical microscopy were employed to investigate the impact of carbon fiber at various volume fractions (10, 20, and 30 %) on isotactic polypropylene crystallization and mechanical performance. Variations in mechanical properties correspond to the structural evolution of the interfacial region and are correlated to underlying microstructural attributes using wide-angle X-ray scattering, thermal analysis, and low-field nuclear magnetic resonance spectroscopy. These results provide a practical framework for the manufacturing of thermoplastic matrix composites. In conclusion, the results presented provide a guide for the strategic optimization of interphase design, showcasing tailorable tensile strengths which outperform any isotactic polypropylene carbon fiber composites previously reported in literature.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoscale Photoexcited Carrier Dynamics in Perovskites

The optoelectronic properties of lead halide perovskite thin films can be tuned through compositional variations and strain, but the associated nanocrystalline structure makes it difficult to untangle the link between composition, processing conditions, and ultimately material properties and degradation. Here, we study the effect of processing conditions and degradation on the local photoconductivity dynamics in [(CsPbI 3 ) 0.05 (FAPbI 3 ) 0.85 (MAPbBr 3 ) 0.15 ] and (FA 0.7 Cs 0.3 PbI 3 ) perovskite thin films using temporally and spectrally resolved microwave near-field microscopy with a temporal resolution as high as 5 ns and a spatial resolution better than 50 nm. For the latter FACs formulation, we find a clear effect of the process annealing temperature on film morphology, stability, and spatial photoconductivity distribution. After exposure of samples to ambient conditions and illumination, we find spectral evidence of halide segregation-induced degradation below the instrument resolution limit for the mixed halide formulation, while we find a clear spatially inhomogeneous increase in the carrier lifetime for the FACs formulation annealed at 180 degrees C.

14 SOLAR ENERGY↗
DOE OSTI2024

Resolving Nonequilibrium Shape Variations among Millions of Gold Nanoparticles

Nanoparticles, exhibiting functionally relevant structural heterogeneity, are at the forefront of cutting-edge research. Now, high-throughput single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) creates opportunities for recovering the shape distributions of millions of particles that exhibit functionally relevant structural heterogeneity. To realize this potential, three challenges have to be overcome: (1) simultaneous parametrization of structural variability in real and reciprocal spaces; (2) efficiently inferring the latent parameters of each SPI measurement; (3) scaling up comparisons between 10 5 structural models and 10 6 XFEL-SPI measurements. Here, we describe how we overcame these three challenges to resolve the nonequilibrium shape distributions within millions of gold nanoparticles imaged at the European XFEL. These shape distributions allowed us to quantify the degree of asymmetry in these particles, discover a relatively stable “shape envelope” among nanoparticles, discern finite-size effects related to shape-controlling surfactants, and extrapolate nanoparticles’ shapes to their idealized thermodynamic limit. Ultimately, these demonstrations show that XFEL SPI can help transform nanoparticle shape characterization from anecdotally interesting to statistically meaningful.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Investigation of Site Amplifications Using Ambient-Noise-Derived Shallow Velocity Structures Under a Dense Array in Oklahoma

The shear-wave velocity (V S ) structure plays an important role in characterizing site amplification. The Large-n Seismic Survey in Oklahoma (LASSO; 1820 stations) revealed large vertical ground-motion variability in a 25 km × 32 km area in northern Oklahoma. The LASSO array has a relatively simple and flat topography, typical in a sedimentary basin environment in the central United States. In this study, we use the dense array to investigate the velocity structure under the LASSO array and how vertical ground motions relate to the shallow-to-deep structures. We extract the fundamental-mode Rayleigh wave by cross-correlating one month of ambient noise (0.7–5 Hz). We use double-beamforming to measure the group and phase velocities and anisotropy. By jointly inverting the group and phase velocities, we obtain the V S structure. Here, we observe correlations between V S at depths of 0.1–1.5 km and vertical ground motions using sites on the stiffer Permian formations. The shallow Quaternary alluvium and terrace deposits can amplify vertical ground motions by a factor of 2–4.5 between 2 and 25 Hz and attenuate signals above 25 Hz. We use 1D V S profiles to simulate the SV-wave transfer functions. An average V S of 250 m/s in the upper 20–40 m may cause the observed amplification between 2 and 40 Hz. V S estimated by topographic slopes cannot predict the relative amplification. Our results highlight the large variability of site-dependent ground motion in a small local region and the importance of characterizing shallow structures to estimate seismic hazards. Small thickness variations of the shallow formation can significantly change the resonance amplitude and frequency, which likely reduces the coherency of the Rayleigh waves extracted from ambient noise.

Chang, Hilary [Massachusetts Inst. of Technology (↗
DOE OSTI2020

Accuracy of High Explosive Data used for Reactive Burn Model Calibration

Reactive burn models for a high explosive (HE) have three components: an equation of state (EOS) for the products, an EOS for the reactants and a reaction rate. For the products, we discuss the uncertainty in data for the planar detonation state and its release isentrope. For the reactants, the uncertainty in the principal shock locus data is discussed. For the reaction rate, we discuss uncertainties in shock initiation data (distance-of-run to detonation as a function of shock pressure), and curvature effect data (detonation speed as a function of front curvature). An important source of uncertainty for calibrating the reaction rate for a plastic-bonded explosive (PBX) results from variations in heterogeneities; that is the mesoscale structure of HE grains, binder and porosity. This shows up in the scatter of both shock initiation data and curvature effect data with small changes in initial density and initial temperature, and systematic changes with PBX lot. As illustrative examples, we use data for the conventional HMX based PBX 9501 and the insensitive TATB based PBX 9502 since these explosives have been extensively studied and high quality data are readily available in the literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Mirror nucleon removal reactions in p-shell nuclei

Nucleon removal reactions have been shown to be an effective tool for studying the single particle structure of nuclei. This work continues efforts to experimentally probe and benchmark the reaction and structure models used to calculate the removal reaction cross sections when using microscopic nuclear structure inputs. Here, three different single nucleon removal reactions were performed, from p -shell nuclei with masses A = 7, 9, and 10. The residual nuclei from the reactions were detected in coincidence with γ rays to determine partial cross sections to individual final states. The eikonal direct-reaction model is combined with overlap functions and residual nucleus densities from microscopic, variational Monte Carlo calculations to provide consistent nuclear structure input to the partial cross section calculations. Comparisons of measured and calculated cross sections, including for mirror reactions, are presented. The analysis of the partial cross sections leading to the ground states shows a similar behavior to the one observed from analyses of inclusive cross sections using shell model nuclear structure input: the theoretical description of the removal process is in better agreement with the data when removing weakly bound nucleons, than when removing well-bound ones. The two mirror reaction pairs presented here show consistent results between the respective members of the pairs. The results obtained for the population of the excited states, however, show a systematically different trend that appears connected to the structure part of the calculation. Additional cases are needed to better understand the respective roles of structure and dynamical effects in the deviations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

High-resolution analogue of time-domain phonon spectroscopy in the transmission electron microscope

Femtosecond photoexcitation of semiconducting materials leads to the generation of coherent acoustic phonons (CAPs), the behaviours of which are linked to intrinsic and engineered electronic, optical and structural properties. While often studied with pump-probe spectroscopic techniques, the influence of nanoscale structure and morphology on CAP dynamics can be challenging to resolve with these all-optical methods. Here, we used ultrafast electron microscopy (UEM) to resolve variations in CAP dynamics caused by differences in the degree of crystallinity in as-prepared and annealed GaAs lamellae. Following in situ femtosecond photoexcitation, we directly imaged the generation and propagation dynamics of hypersonic CAPs in a mostly amorphous and, following an in situ photothermal anneal, a mostly crystalline lamella. Subtle differences in both the initial hypersonic velocities and the asymptotic relaxation behaviours were resolved via construction of space-time contour plots from phonon wavefronts. Comparison to bulk sound velocities in crystalline and amorphous GaAs reveals the influence of the mixed amorphous-crystalline morphology on CAP dispersion behaviours. Further, an increase in the asymptotic velocity following annealing establishes the sensitivity of quantitative UEM imaging to both structural and compositional variations through differences in bonding and elasticity. Lastly, implications of extending the methods and results reported here to elucidating correlated electronic, optical and structural behaviours in semiconducting materials are discussed.

42 ENGINEERING↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗