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At least 145 records · Page 8

Measurement of phonon angular momentum

In condensed matter, angular momentum is intimately related to the emergence of topological quantum states, including chiral superconductivity, quantum spin liquids and various chiral quasiparticles. Recently, it has been predicted that microscopic lattice excitations, known as phonons, can carry finite angular momentum, leading to specific physical properties of materials. However, phonon angular momentum has not yet been observed directly. Here, in this study, we demonstrate that angular momentum conservation results in a macroscopic mechanical torque when applying a time-reversal symmetry-breaking thermal gradient along the chiral axis of single-crystal tellurium. We probe this torque using a cantilever-based device and establish that it changes sign by flipping the chirality or thermal gradient. This behavior disappears in polycrystalline samples that lack a preferred chirality. Our experimental results align well with theoretical calculations. We provide compelling evidence for phonon angular momentum, which might enable quantum states with potential applications in microelectronics.

36 MATERIALS SCIENCE↗

Copper migration and surface oxidation of CuxBi2Se3 in ambient pressure environments

Abstract Chemical modifications such as intercalation can be used to modify surface properties or to further functionalize the surface states of topological insulators (TIs). Using ambient pressure x-ray photoelectron spectroscopy, we report copper migration in C u x B i 2 S e 3 , which occurs on a timescale of hours to days after initial surface cleaving. The increase in near-surface copper proceeds along with the oxidation of the sample surface and large changes in the selenium content. These complex changes are further modeled with core-level spectroscopy simulations, which suggest a composition gradient near the surface which develops with oxygen exposure. Our results shed light on a new phenomenon that must be considered for intercalated TIs—and intercalated materials in general—that surface chemical composition can change when specimens are exposed to ambient conditions.

36 MATERIALS SCIENCE↗

SCF Framework, HF Stability, and RPA Correlation for Jordan–Wigner-Transformed Spin Hamiltonians on Arbitrary Coupling Topologies

Mapping spins to fermions via the Jordan–Wigner (JW) transformation can render mean-field (Hartree–Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is not limited by the nonlocal structure of JW strings or by site ordering because string operators can be absorbed into Thouless rotations of a Slater determinant, and the variational optimization of a unitary Lie-algebraic similarity transformation removes any ordering dependence. Leveraging these ideas, we develop a self-consistent field (SCF) scheme that expresses the mean-field energy as a functional of the single-particle density matrix, providing an alternative to gradient-based optimization of Thouless parameters. We derive the analytical orbital Hessian to diagnose HF stability and compute the ground-state correlation energy through the random-phase approximation (RPA). Benchmark results for the XXZ and J 1 –J 2 model on one- and two-dimensional lattices demonstrate that RPA significantly improves mean-field accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Anomalous Retrograde Drifts in Obstructed Magnetron Microdischarges: a Consequence of a Field Reversal in the Anode Sheath?

The goal of this project was to carry out experiments at the Plasma Collaborative Research Facility (Princeton Plasma Physics Laboratory) aimed at confirming or refuting the hypothesis that an electric field reversal occurs in the near-anode region of a strongly obstructed planar magnetron microdischarges. Magnetron discharges are magnetized plasmas with E x B field topologies, and variants of such discharges are widely used in materials processing. The topologies are also similar to that of Hall thrusters used in space propulsion. Understanding the structure of these discharges will aid in developing reliable simulations that are intended to facilitate the further development of such technologies, as the field reversals, presumed to be due to strong axial-driven electron transport, provides further insight into transport properties. The possible existence of such a field reversal is hinted at because of the retrograde-propagating (i.e., negative E x B) spokes or gradient-driven drift instabilities seen in the high speed videos and segmented anode probing of the plasma. The presence of this field reversal should be reflected in the ion dynamics, particularly, in an ion drift towards the anode. The proposed experiments to be conducted at the PCRF are to characterize this anode-directed ion drift using state-of-the-art laser-induced fluorescence velocimetry. In particular, we seek to see if the near-anode ion velocity reverses direction when the external circuit is varied to alter the electron current demand imposed at the anode. Such an ion velocity reversal would confirm the mechanism, which is that the highly obstructed (small gapped) discharge produces strong axial gradients in plasma density, driving more electrons towards the anode then that demanded by the external circuit.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enabling On-Demand Aerospace Component Manufacturing: Topology Optimization of GE Engine Bracket and Fabrication Using Metal FFF

Additive Manufacturing (AM) offers advantages over conventional manufacturing processes, particularly by reducing the number of parts produced through multistage combined technologies, but these often result in low manufacturing yields or require post-processing. AM facilitates the production of complex geometries with fine features, overhangs, and lattice structures. For instance, Laser Powder Bed Fusion (LPBF) technology enables the fabrication of intricate parts that can be easily post-processed by removing residual powder. Laser powder bed AM technologies are widely discussed in the literature due to their design freedom in creating complex geometries, with and without the need for support generation. However, rapid solidification due to a thermal gradient in the build direction, which leads to the formation of columnar grains and warpage, is one of the challenges. To address this challenge, we propose layer-by-layer metal FFF technology, followed by the debinding and sintering process, as an alternative to powder- and laser-based approaches. Furthermore, design for additive manufacturing (DfAM) principles are discussed to minimize the need for support generation and enable easy post-processing, thereby improving surface finish to meet high tolerances in fabricating components for aerospace and healthcare applications.

Singh, Abhishek [University of Michigan, Ann Arbor↗

On the Use of CAD and Cartesian Methods for Aerodynamic Optimization

The objective for this paper is to present the development of an optimization capability for Curt3D, a Cartesian inviscid-flow analysis package. We present the construction of a new optimization framework and we focus on the following issues: 1) Component-based geometry parameterization approach using parametric-CAD models and CAPRI. A novel geometry server is introduced that addresses the issue of parallel efficiency while only sparingly consuming CAD resources; 2) The use of genetic and gradient-based algorithms for three-dimensional aerodynamic design problems. The influence of noise on the optimization methods is studied. Our goal is to create a responsive and automated framework that efficiently identifies design modifications that result in substantial performance improvements. In addition, we examine the architectural issues associated with the deployment of a CAD-based approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute engines. We demonstrate the effectiveness of the framework for a design problem that features topology changes and complex geometry.

Nemec, M.↗

Aerodynamic Shape Optimization Based on Free-form Deformation

This paper presents a free-form deformation technique suitable for aerodynamic shape optimization. Because the proposed technique is independent of grid topology, we can treat structured and unstructured computational fluid dynamics grids in the same manner. The proposed technique is an alternative shape parameterization technique to a trivariate volume technique. It retains the flexibility and freedom of trivariate volumes for CFD shape optimization, but it uses a bivariate surface representation. This reduces the number of design variables by an order of magnitude, and it provides much better control for surface shape changes. The proposed technique is simple, compact, and efficient. The analytical sensitivity derivatives are independent of the design variables and are easily computed for use in a gradient-based optimization. The paper includes the complete formulation and aerodynamics shape optimization results.

Samareh, Jamshid A.↗

Deformation of the heliospheric current sheet

A kinematic analysis of the previously neglected effect of velocity inhomogeneity on the topology of the heliospheric current sheet in a radially flowing solar wind shows how the originally smooth current sheet becomes 'ruffled'. In the highly idealized case of a totally uniform, radial, steady solar wind, the shape of the current sheet is independent of distance from the sun. However, the real solar wind is inhomogeneous; the velocity varies from point to point along the current sheet, causing a distortion in the current sheet of progressively greater amplitude with increasing distance from the sun. This is true even for purely radial flow. Significant and observable distortion is produced by relatively small gradients in velocity; thus to predict or understand the shape of the heliospheric current sheet it is essential to know the solar wind in which the current sheet is embedded. Examples are given of mild velocity gradients which demonstrate the principles, the magnitude, and the character of the effect; deformation of the actual heliospheric current sheet in the highly variable solar wind is expected to be of far greater amplitude and complexity than in the simplified, tutorial examples. A new expression for the inclination of the current sheet as a function of velocity inhomogeneity and distance from the sun that is easily applied to the interpretation of solar wind data is also derived.

Suess, S. T.↗

Stress studies in EFG

Stress distributions were calculated for a creep law to predict a rate of plastic deformation. The expected reduction in stresses is obtained. Improved schemes for calculating growth system temperature distributions were evaluated. Temperature field modeling examined the possibility of using horizontal temperature gradients to influence stress distribution in ribbon. The defect structure of 10 cm wide ribbon grown in the cartridge system was examined. A new feature is identified from an examination of cross sectional micrographs. It consists of high density dislocation bands extending through the ribbon thickness. A four point bending apparatus was constructed for high temperature study of the creep response of silicon, to be used to generate defects for comparison with as grown defects in ribbon. The feasibility of laser interferometric techniques for sheet residual stress distribution measurement is examined. The mathematical formalism for calculating residual stress from changes in surface topology caused by an applied stress in a rectangular specimen was developed, and the system for laser interferometric measurement to obtain surface topology data was tested on CZ silicon.

Source record↗

HLPW-4: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and LB methods on a complex high-lift configuration across a wide range of angles-of-attack. Analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles-of-attack due to large pressure gradients present on the outboard slat and main element for 𝛼 >17◦(corrected for free-air). While some scatter is reported in pitching moment coefficient at the low-angles of attack (𝛼 <11◦) - excellent agreement is observed between submissions near the 𝐶𝐿,max state. Objective superiority of WMLES methods over RANS can be seen in terms of lack of excess outboard separation; a majority of the WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. The in-tunnel simulations show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of the WMLES submissions over RANS.

TTT↗

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗

Post-Disaster Microgrid Formation for Enhanced Distribution System Resilience

This paper proposes a deep reinforcement learning (DRL) based approach for post-disaster critical load restoration in active distribution systems to form microgrids through network reconfiguration to minimize critical load curtailments. Distribution networks are represented as graph networks, and optimal network configurations with microgrids are obtained by searching for the optimal spanning forest. The constraints to the research question being explored are the radial topology and power balance. Unlike existing analytical and population-based approaches, which necessitate the repetition of entire analyses and computation for each outage scenario to find the optimal spanning forest, the proposed approach, once properly trained, can quickly determine the optimal, or near-optimal, spanning forest even when outage scenarios change. When multiple lines fail in the system, the proposed approach forms microgrids with distributed energy resources in active distribution systems to reduce critical load curtailment. The proposed DRL-based model learns the action-value function using the REINFORCE algorithm, which is a model-free reinforcement learning technique based on stochastic policy gradients. A case study was conducted on a 33-node distribution test system, demonstrating the effectiveness of the proposed approach for post-disaster critical load restoration.

active distribution systems↗

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗

X-ray phase contrast and absorption imaging for the quantification of transient cavitation in high-speed nozzle flows

In this work, high-flux synchrotron radiation has been employed in a time-resolved manner to characterise the distinct topology features and dynamics of different cavitation regimes arising in a throttle orifice with an abrupt flow-entry contraction. Radiographs obtained though both X-ray phase- contrast and absorption imaging have been captured at 67,890 frames per second. The flow lied in the turbulent regime (Re=35,500), while moderate (CN=2.0) to well-established (CN=6.0) cavitation conditions were examined encompassing the cloud and vortical cavitation regimes with pertinent transient features, such as cloud-cavity shedding. X-ray Phase-Contrast Imaging (XPCI), exploiting the shift in the X-ray wave phase during interactions with matter, offers sharp-refractive index gradients in the interface region. Hence, it is suitable for capturing fine morphological fluctuations of transient cavitation structures. Nevertheless, the technique cannot provide information on the quantity of vapour within the orifice. Such data have been obtained utilising absorption imaging, where beam attenuation is not associated with scattering and refraction events, and hence can be explicitly correlated with the projected vapour thickness in line-of-sight measurements. A combination of the two methods is proposed, as it has been found is capable of quantifying the vapour content arising in the complex nozzle flow, while also faithfully illustrating the dynamics of the highly-transient cavitation features.

42 ENGINEERING↗

Local aging effects in PuB 4 : Growing inhomogeneity and slow dynamics of local field fluctuations probed by 239 Pu NMR

Plutonium-based correlated electron materials host exotic physical phenomena ranging from unconventional heavy-fermion superconductivity to topological Kondo insulating states. Self-irradiation damage can influence many properties of such radioactive materials. Structural disorder effects due to α radiation have been frequently studied using techniques such as transport, thermodynamics, and x-ray diffraction. Here, in this study, we use 239 Pu nuclear magnetic resonance (NMR) to study the long-term influence of self-damage on the lattice and local electronic structures in a single crystal of the candidate topological insulator plutonium tetraboride (PuB 4 ). We first characterize the anisotropy of the 239 Pu resonance and confirm the local axial-site symmetry inferred from previous polycrystalline measurements. Aging effects are then evaluated over the time frame of six years. We find that, though the static 239 Pu NMR spectra show a slight modulation in their shape, their field-rotation pattern reveals no change in 239 Pu local site symmetry over time, suggesting that aging has a surprisingly small impact on the spatial distribution of the static hyperfine field. Further, ligand-site 11 B NMR finds little time-dependent change in the size of electric field gradient around 11 B sites. By contrast, aging has a prominent impact on the 239 Pu NMR relaxation processes and signal intensity. Specifically, aging-induced damage manifests itself as an increase in the spin-lattice relaxation time 𝑇 1 , an increased distribution of 𝑇 1 , and a signal intensity that decreases linearly by 20% per year. An effective spin-spin relaxation time 𝑇 2,eff in the aged sample shortens drastically towards lower temperature, suggesting growth of slow fluctuations of the hyperfine field that are linked to radiation-damage-induced inhomogeneity. Our NMR study sheds light on the interplay of radiation damage and local magnetic interactions in correlated insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning.

This paper describes an efficient reverse-mode differentiation algorithm for contraction operations of tensor networks that may have arbitrary and unconventional network topologies. The approach leverages the tensor contraction tree of Evenbly and Pfeifer (2014), which provides an instruction set for the contraction sequence of a network. We show that this tree can be efficiently leveraged for differentiation of a full tensor network contraction using a recursive scheme that exploits (1) the bilinear property of contraction and (2) the property that trees have single path from root to leaves. While differentiation of tensor-tensor contraction is already possible in most automatic differentiation packages, we show that exploiting these two additional properties in the specific context of contraction sequences can improve efficiency. Following a description of the algorithm and computational complexity analysis, we investigate its utility for gradient-based supervised learning for low-rank function recovery and for fitting real-world unstructured datasets. We demonstrate improved performance over alternating least-squares optimization approaches and the capability to handle heterogeneous and arbitrary tensor network formats. When compared to alternating minimization algorithms, we find that the gradient-based approach requires a smaller oversampling ratio (number of samples compared to number model parameters) for recovery. This increased efficiency extends to fitting unstructured data of varying dimensionality and when employing a variety of tensor network formats. Here, we show improved learning using the hierarchical Tucker method over the tensor-train in high-dimensional settings on a number of benchmark problems.

97 MATHEMATICS AND COMPUTING↗

The Dynamics of Miscible Interfaces: A Space Flight Experiment

Experiments as well as accompanying simulations are described that serve in preparation of a space flight experiment to study the dynamics of miscible interfaces. The investigation specifically addresses the importance of both nonsolenoidal effects as well as nonconventional Korteweg stresses in flows that give rise to steep but finite concentration gradients. The investigation focuses on the flow in which a less viscous fluid displaces one of higher viscosity and different density within a narrow capillary tube. The fluids are miscible in all proportions. An intruding finger forms that occupies a fraction of the total tube diameter. Depending on the flow conditions, as expressed by the Peclet number, a dimensionless viscosity ratio, and a gravity parameter, this fraction can vary between approximately 0.9 and 0.2. For large Pe values, a quasi-steady finger forms, which persists for a time of O(Pe) before it starts to decay, and Poiseuille flow and Taylor dispersion are approached asymptotically. Depending on the specific flow conditions, we observe a variety of topologically different streamline patterns, among them some that leak fluid from the finger tip. For small Pe values, the flow decays from the start and asymptotically reaches Taylor dispersion after a time of O(Pe). Comparisons between experiments and numerical simulations based on the 'conventional' assumption of solenoidal velocity fields and without Korteweg stresses yield poor agreement as far as the Pe value is concerned that distinguishes these two regimes. As one possibility, we attribute this lack of agreement to the disregard of these terms. An attempt is made to use scaling arguments in order to evaluate the importance of the Korteweg stresses and of the assumption of solenoidality. While these effects should be strongest in absolute terms when steep concentration fronts exist, i.e., at large Pe, they may be relatively most important at lower values of Pe. We subsequently compare these conventional simulations to more complete simulations that account for nonvanishing divergence as well as Korteweg stresses. While the exact value of the relevant stress coefficients are not known, ballpark numbers do exist, and their use in the simulations indicates that these stresses may indeed be important. We plan to evaluate these issues in detail by means of comparing a space experiment with corresponding simulations, in order to extract more accurate Korteweg stress coefficients, and to confirm or deny the importance of such stresses.

Maxworthy, Tony↗

HLPW-4/GMGW-3: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and Lattice-Boltzmann methods on a complex high-lift configuration across a wide range of angles of attack. Preliminary analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles of attack due to large pressure gradients present on the outboard slat and main element for𝛼 >17◦(corrected for free-air).While some scatter is reported in pitching moments at the low-angles of attack (𝛼 <11◦) - likely caused by differences in flap separation possibly due to low Reynolds number effects - excellent agreement is observed between the submissions near the𝐶𝐿,max state. Objective superiority over steady state RANS can be seen in terms of lack of excess outboard separation; a majority of the good quality WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. Differences in the onset of stall mechanism in the free-air configuration for𝛼 >20◦is reported with two distinct topologies observed. Topology A is characterized by the onset of corner-flow separation which progressively grows to produce a pitch break in free-air with an angle of attack increase from𝛼=20.55◦to𝛼=21.47◦+𝜖where𝜖is a small perturbation (varying between submissions and likely to be within±0.3◦). Topology Bis characterized by boundary layer weakness emanating from the inboard side of the wing-pylon juncture substantially larger than any weakness in the wing-body juncture (due to corner-flow);submissions in this category do not show any tendency for occurrence of a pitch break for the free-air configuration within the vicinity of𝛼=21.47◦. The in-tunnel simulations submitted by3 participants using different discretizations, grids and closure models show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of all 3 WMLES submissions over a single steady state RANS submission to the workshop.

TTT↗