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At least 1,531 records · Page 85

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DOE OSTI2022

Tunable angle-dependent electrochemistry at twisted bilayer graphene with moiré flat bands

Tailoring electron transfer dynamics across solid–liquid interfaces is fundamental to the interconversion of electrical and chemical energy. Stacking atomically thin layers with a small azimuthal misorientation to produce moiré superlattices enables the controlled engineering of electronic band structures and the formation of extremely flat electronic bands. Here, we report a strong twist-angle dependence of heterogeneous charge transfer kinetics at twisted bilayer graphene electrodes with the greatest enhancement observed near the ‘magic angle’ (~1.1°). Furthermore, this effect is driven by the angle-dependent tuning of moiré-derived flat bands that modulate electron transfer processes with the solution-phase redox couple. Combined experimental and computational analysis reveals that the variation in electrochemical activity with moiré angle is controlled by a structural relaxation of the moiré superlattice at twist angles of <2°, and ‘topological defect’ AA stacking regions, where flat bands are localized, produce a large anomalous local electrochemical enhancement that cannot be accounted for by the elevated local density of states alone.

36 MATERIALS SCIENCE↗

NASA NTRS1988

Structural assessment of a space station solar dynamic heat receiver thermal energy storage canister

The structural performance of a space station thermal energy storage (TES) canister subject to orbital solar flux variation and engine cold start up operating conditions was assessed. The impact of working fluid temperature and salt-void distribution on the canister structure are assessed. Both analytical and experimental studies were conducted to determine the temperature distribution of the canister. Subsequent finite element structural analyses of the canister were performed using both analytically and experimentally obtained temperatures. The Arrhenius creep law was incorporated into the procedure, using secondary creep data for the canister material, Haynes 188 alloy. The predicted cyclic creep strain accumulations at the hot spot were used to assess the structural performance of the canister. In addition, the structural performance of the canister based on the analytically determined temperature was compared with that based on the experimentally measured temperature data.

Thompson, R. L.↗

NASA NTRS1983

Long-lived particulate or gaseous structure in Saturn's outer magnetosphere

Voyager 1 and 2 and Pioneer 11 data on the variations in the number density of low-energy plasma ions in the outer Saturn magnetosphere are discussed. Low and high latitude observations are compared in reference to the position of the spacecraft crossing of the field line. Abrupt decreases in the number density interrupted the tendancy for the number density to increase with spacecraft approach to Saturn. All three spacecraft are concluded to have encountered the same magnetospheric structure in the field line, with absorbers being present in the equatorial plane. The absorbers are suggested to be either gas or debris, which may be detectable visibly or with occultation techniques.

Lazarus, A. J.↗

NASA NTRS1980

Effects of granular convection in the response of C I 5380 A to solar luminosity variations

The response of the weak solar photospheric neutral carbon line at 5380.3 A to percolations of photospheric granulation and the five-minute solar oscillations is investigated in order to calibrate the sensitivity of the line to temporal variations in solar luminosity. Line strength variations and simultaneous continuum variations in two granular regions were observed at 30 sec intervals using a 25-cm coude spectrograph. The response of line equivalent width to continuum intensity variations is found to be essentially uniform at time scales ranging from 5 min to 2 hr independently of whether the variations arise from granular convection or velocity field oscillations. The extent to which line strength varies with luminosity (sensitivity) is observed to be significantly smaller than estimates based on models of the perturbed Harvard-Smithsonian Reference Atmosphere of Gingerich et al. (1970), and it is proposed that the structure of the solar granulation is a major factor determining local luminosity variations and line sensitivity.

Lindsey, C. A.↗

DOE OSTI2023

Property-Graded Stainless Steel 316L by Selective Laser Melting: Characterization & Design

Abstract The purpose of this research work is to characterize and inform the design of (mechanical) property-graded bulk structures made from a single metallic alloy via a laser powder bed fusion (LPBF) process, with an end goal of creating repeatable/reproducible functionally-graded additively manufactured (FGAM) parts. This paper specifically investigates the manufacture of stainless steel (SS) 316L structures via a pulsed selective laser melting (SLM) process, and the underlying causes of property variations (within a functionally-acceptable range) through various material characterization techniques. For this, a design of experiments spanning the volumetric energy density (VED) based process parameter design space was utilized to investigate the range of functionally-acceptable physical/mechanical properties achievable in SS 316L. Five sample conditions (made via different process parameter combinations) were down-selected for in-depth microstructure analysis and mechanical/physical property characterization; these were suitably selected to impart a wide and controllable property range (209–318 HV hardness, 90–99.9% relative density, and 154–211 GPa modulus). It was observed that property variations resulted from combinations of porosity types/amounts, martensitic phase fractions, and grain sizes. Based on these findings, property-graded standard test specimens were designed and manufactured for further investigation—tensile specimens having a monotonic hardness change along its gauge length, four-point bending specimens with varying elastic moduli as a function of the distance from the neutral axis, and Moore’s rotating beam fatigue specimens with moduli variations based on the distance from the center. Altogether, this work lays the foundation for understanding and designing the local and global mechanical performance of FGAM bulk structures.

Engineering↗

DOE OSTI2025

Autonomous Nanoparticle Synthesis Guided by In Situ Multiscale Structural Characterization

Autonomous synthesis platforms promise rapid exploration of vast parameter spaces; yet, integrating in situ structural characterization in closed-loop synthesis optimization remains challenging. We demonstrate a realization of such a closed-loop platform coupled with a droplet-flow microreactor, in situ X-ray scattering methods (SAXS/WAXS), and Gaussian process optimization to synthesize citrate-reduced Au nanoparticles with targeted characteristics. The system efficiently explored ∼19,000 synthesis recipes through 365 experiments, achieving precise control over size (4–60 nm) and polydispersity (σ < 0.11) across large citrate/gold ratios, exceeding traditional synthesis boundaries (1–10). Beyond confirming classical Turkevich–Frens trends, partial-dependence analysis revealed strong nonlinear coupling among precursor, citrate, and pH effects. Combining quantitative SAXS/WAXS analysis with electron microscopy characterization, we uncovered that crystallite size (d c ) and particle size (d) follow d c = 0.18d + β, where synthesis chemistry controls the intercept β while maintaining a universal slope. This parallel-band structure enables independent tuning of crystallite domain size at fixed particle diameter through a combination of chloride, gold precursor, citrate, and pH contributions (cross-validated Spearman ρ = 0.7 ± 0.1). High-resolution electron microscopy shows multiple lattice-fringe orientations within single particles, directly confirming polycrystalline domains and the ability to tune d c at the fixed d. The platform’s validation includes indistinguishable static versus flowing measurements, stable droplet transport at 100 °C, and <5% run-to-run variation, establishing a robust framework for mapping and controlling multiscale nanoparticle structure across expansive chemical spaces. In conclusion, the developed closed-loop platform can be applied to a borad range of nanosyntheis processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model

Quantum simulations offer the potential to predict the structure and dynamics of nuclear many-body systems that are beyond the capabilities of classical computing. Generally, preparing the ground state of strongly-interacting many-body systems relevant to nuclear physics is however inefficient, even using ideal quantum computers. In addition, currently available NISQ-era quantum devices possess modest numbers of qubits, limiting the size of quantum many-body systems that can be simulated. In this context, a reformulation of the quantum many-body problems using truncated model spaces and Hamiltonians is desirable to make them more amenable to near-term quantum computers. The importance of symmetries in low-energy theories, including effective field theories (EFTs), lattice quantum chromodynamics (QCD), and effective model spaces for nuclear systems, in particular their interplay with the reduction of active Hilbert spaces, is well known. Lesser known is the fact that the non-commutivity of some symmetries and truncations of the model space can be profitably combined with variational calculations to rearrange the entanglement into localized structures and enable more efficient simulations. Here, the goal of the present study is to explore and utilize the non-commutivity of symmetries and model-space truncations of quantum many-body systems important to nuclear physics, particularly in combination with variational algorithms for quantum simulations and effective Hamiltonian learning. We introduce an iterative hybrid classical-quantum algorithm, Hamiltonian learning variational quantum eigensolver (HL-VQE), that simultaneously optimizes an effective Hamiltonian, thereby rearranging entanglement into the effective model space, and the associated ground-state wavefunction. Quantum simulations, using classical computers and IBM's superconducting-qubit quantum computers, are performed to demonstrate the HL-VQE algorithm, in the context of the Lipkin-Meshkov-Glick (LMG) model of interacting fermions, where the Hamiltonian transformation corresponds to an orbital rotation. We use a mapping where the number of qubits scales with the $\log$ of the size of the effective model space, rather than the particle number. HL-VQE is found to provide an exponential improvement in LMG-model calculations of the ground-state energy and wavefunction, compared to naive truncations without Hamiltonian learning, throughout a significant fraction of the Hilbert space. In the context of EFT, this corresponds to counterterms scaling exponentially with the cut-off as opposed to power law. Implementations on IBM's QExperience quantum computers and simulators for 1- and 2-qubit effective model spaces are shown to provide accurate and precise results, reproducing classical predictions. For a range of parameters defining the LMG model, the HL-VQE algorithm is found to have better scaling of quantum resources requirements than previously explored algorithms. In particular, the HL-VQE scales efficiently over a large fraction of the model space, in contrast to VQE alone. This work constitutes a step in the development of entanglement-driven quantum algorithms for descriptions of nuclear many-body systems. This, in part, leverages the potential of noisy intermediate-scale quantum (NISQ) devices. The exponential scaling of counterterms observed in this study suggests the possibility of more general applicability to other non-perturbative EFTs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1976

The spiral structure of the interplanetary magnetic field

The Pioneer 10 data concerning the heliocentric radial variation of the interplanetary magnetic field are examined. Incorporating the systematic increase in solar wind velocity observed during the mission leads to much improved agreement between the usual Parker Archimedean spiral and the data. The effects of correlations between short-period fluctuations of speed and azimuthal field are discussed. It is concluded that during the period under study they did not substantially affect the average magnetic field.

Parker, G. D.↗

NASA NTRS1988

The solar origin of long-term variations of the interplanetary magnetic field strength

Using simple models for the coronal field structure, the spacecraft observations of the photospheric field during sunspot cycle 21 were extrapolated for the purpose of modeling quantitatively the long-term behavior of the IMF during the sunspot cycle 21. Results were compared with the measurements of the radial component of the IMF at earth. The results indicate that the solar source of the IMF can be represented to a first approximation by the dipole component of the photospheric field, whose axis is nearly perpendicular to the ecliptic plane around sunspot minimum, but tilts more strongly toward it around sunspot maximum. It was also found that the average radial IMF strength varies with heliographic latitude; around sunspot minimum, the radial IMF is expected to be roughly twice as strong above the sun's poles as near the ecliptic plane. The average strength of the photospheric field above latitude 55 deg is about 10 G around sunspot minimum.

Wang, Y.-M.↗

DOE OSTI2024

Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries

The rapid growth of automated and autonomous instrumentation brings forth opportunities for the co-orchestration of multimodal tools that are equipped with multiple sequential detection methods or several characterization techniques to explore identical samples. This is exemplified by combinatorial libraries that can be explored in multiple locations via multiple tools simultaneously or downstream characterization in automated synthesis systems. In co-orchestration approaches, information gained in one modality should accelerate the discovery of other modalities. Correspondingly, an orchestrating agent should select the measurement modality based on the anticipated knowledge gain and measurement cost. Herein, we propose and implement a co-orchestration approach for conducting measurements with complex observables, such as spectra or images. The method relies on combining dimensionality reduction by variational autoencoders with representation learning for control over the latent space structure and integration into an iterative workflow via multi-task Gaussian Processes (GPs). This approach further allows for the native incorporation of the system's physics via a probabilistic model as a mean function of the GPs. We illustrate this method for different modes of piezoresponse force microscopy and micro-Raman spectroscopy on a combinatorial Sm-BiFeO3 library. However, the proposed framework is general and can be extended to multiple measurement modalities and arbitrary dimensionality of the measured signals.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Unraveling the structural dependency of Weyl nodes in Co 2 MnGa

Conventionally, the modulation of the intrinsic Weyl nodes in Weyl semimetals is challenging, due to topological protection. Here we report the structural dependence of the Weyl nodes in a Co2⁢MnGa Heusler thin film via a temperature-dependent tetragonal distortion. The ability to manipulate these Weyl nodes allows for the control of the intrinsic electromagnetic properties. Temperature-dependent x-ray diffraction (XRD) measurements identify a compressive tetragonal distortion with decreasing temperature from 300 to 20 K. The calculated Weyl properties can be directly compared with experimental parameters through the temperature-dependent XRD measurements which show the intrinsic correlation between Weyl properties and important magnetic parameters. Further, the microscopic momentum space properties of Weyl nodes such as the distance (d W ), solid angle (Ω W ), tilt (φ W ), and nodal point energy (E W ) directly affect the macroscopic observable properties such as exchange stiffness (A), magnetization (M), and effective anisotropy field $H^{eff}_{K}$, as shown via structure-dependent density functional theory calculations. These predictions are experimentally observed as large variations in the bulk magnetization and effective anisotropy field as a function of temperature. These results highlight a unique degree of freedom in the control of macroscopic magnetic properties via the modulation of the intrinsic properties of Weyl nodes through structural distortions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Spike-and-Slab Shrinkage Priors for Structurally Sparse Bayesian Neural Networks

Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a sparse representation of the underlying target function by reducing heavily overparameterized deep neural networks. Specifically, deep neural architectures compressed via structured sparsity (e.g., node sparsity) provide low-latency inference, higher data throughput, and reduced energy consumption. In this article, we explore two well-established shrinkage techniques, Lasso and Horseshoe, for model compression in Bayesian neural networks (BNNs). To this end, we propose structurally sparse BNNs, which systematically prune excessive nodes with the following: 1) spike-and-slab group Lasso (SS-GL) and 2) SS group Horseshoe (SS-GHS) priors, and develop computationally tractable variational inference, including continuous relaxation of Bernoulli variables. We establish the contraction rates of the variational posterior of our proposed models as a function of the network topology, layerwise node cardinalities, and bounds on the network weights. Furthermore, we empirically demonstrate the competitive performance of our models compared with the baseline models in prediction accuracy, model compression, and inference latency.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Analytical displacements and vibrations of cantilevered unsymmetric fiber composite laminates

A fiber composite flat cantilever plate that has symmetric and nonsymmetric laminate configurations is theoretically investigated to determine its static and dynamic structural response. The finite element analysis method used includes a unique triangular finite element developed at Lewis for the analysis of fiber composite airfoils. The various responses investigated include tip displacements, natural frequencies, and fundamental mode shapes. The results show that laminate configurations may be selected for a cantilever such that when the tip at the leading edge is loaded normal to the plane of the plate, the tip at the trailing edge can (1) deflect in the opposite direction, (2) deflect about the same, or (3) deflect more than the tip at the leading edge. This variation in response can be utilized to provide built-in structural damping to resist flutter.

Minich, M. D.↗

NASA NTRS1982

Short-term EUV flux variations from AE-E He/+/ abundances

The ionization rate of helium in the thermosphere is inferred from AE-E ion and neutral particle composition measurements made on 20 days from January 1979 to June 1980. The variations in the inferred rate are consistent with variations in the UV flux measured during the same period by the AE-E UV spectrometer. The approximately 27-day modulation of the calculated ionization rate is the result of cyclical variations in the UV flux, which are in turn coupled to the rotation period of the sun. Results indicate that the ionization structure of helium in the thermosphere is closely coupled to both the long and short term EUV flux variations.

Sternberg, A.↗

DOE OSTI2021

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Overdestabilization vs Overstabilization in the Theoretical Analysis of f-Orbital Covalency

The complex nature of the f-orbital electronic structures and their interaction with the chemical environment pose significant computational challenges. Advanced computational techniques that variationally include scalar relativities and spin–orbit coupling directly at the molecular orbital level have been developed to address this complexity. Among these, variational relativistic multiconfigurational multireference methods stand out for their high accuracy and systematic improvement in studies of f-block complexes. Additionally, these advanced methods offer the potential for calibrating low-scaling electronic structure methods such as density functional theory. However, studies on the Cl K-edge X-ray absorption spectra of the [Ce(III)Cl 6 ] 3– and [Ce(IV)Cl 6 ] 2– complexes show that time-dependent density functional theory with approximate exchange–correlation kernels can lead to inaccuracies, resulting in an overstabilization of 4f orbitals and incorrect assessments of covalency. In contrast, approaches utilizing small active space wave function methods may understate the stability of these orbitals. The results herein demonstrate the need for large active space, multireference, and variational relativistic methods in studying f-block complexes.

chemical calculations↗

DOE OSTI2025

Structure evolution and tin redistribution during oxidation of Zircaloy-4 at 500°C

Zirconium (Zr) alloys are widely used as fuel cladding in nuclear power reactors due to their thermal stability, mechanical durability, corrosion resistance, and low neutron absorption cross-section. However, their performance is challenged by oxidation in reactor environments, making the study of Zr alloy corrosion behavior crucial for ensuring the safety, longevity, and economic viability of nuclear power systems. While the oxidation behavior of Zr-based cladding materials has been extensively studied since the 1950s, a mechanistic understanding into the relationship between structure evolution, solute element redistribution, and properties remains elusive. Valuable insights may be obtained through advanced experimental methods, such as in-situ and high resolution microscopy techniques. Here, in this study, the oxidation behavior of Zircaloy-4 at 500 °C in O 2 is characterized using a multimodal advanced characterization approach. Using in-situ X-ray diffraction, the phase evolution from metastable to stable oxides is tracked in real time. Complementary high-resolution techniques, including electron microscopy and atom probe tomography, reveal nanoscale insights into the microstructural changes and solute redistribution across the oxide/metal interface. Nanohardness mapping across the oxide/metal interface highlights localized mechanical property variations that may be linked to changes in microstructure and crystal structure within the oxide layer. These findings offer valuable insights into the microstructure and property evolution of Zircaloy-4 during oxidation, contributing to a better understanding of microstructural changes in Zr-based alloys under oxidative environments.

APT↗

DOE OSTI2024

Exciton Transport in Perovskite Materials

Halide perovskites have emerged as promising materials for a wide variety of optoelectronic applications, including solar cells, light‐emitting devices, photodetectors, and quantum information applications. In addition to their desirable optical and electronic properties, halide perovskites provide tremendous synthetic flexibility through variation of not only their chemical composition but also their structure and morphology. At the heart of their use in optoelectronic technologies is the interaction of light with electronic excitations in the form of excitons. This review discusses the properties and behavior of excitons in halide perovskite materials, with a particular emphasis on low‐dimensional perovskites and the effects of nanoscale morphology on excitonic behavior. The basic theory of excitonic energy migration in semiconductor nanomaterials is introduced, and novel observations in halide perovskite nanomaterials that have evolved our current understanding are explored. Lastly, many important questions that remain unanswered are presented and exciting emerging directions in low‐dimensional perovskite exciton physics are discussed.

2D materials↗