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Accurate single-shot full-Stokes detection enabled by heterogeneous grain orientations in polycrystalline films
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Orientation-dependent mutual crystalline and amorphous order in a single phase solid
Amorphous materials distinguish themselves from crystalline materials by lacking long-range order while retaining structural order at the local scale (2–5 Å). However, the complexity in topological and chemical order prevents current characterization tools from fully unveiling the structure in disordered materials. Consequently, the nature of medium-range order in amorphous materials has remained elusive. The Zachariasen and crystal competing models have been proposed to describe disordered phases and have both been verified through synthesis and characterization. The main difference between them is thought to be whether the amorphous phase shows medium-range order. Here we demonstrate a form of organized inorganic matter that is amorphous in two dimensions, while exhibiting long-range order and a high degree of crystallinity in the third. The structure consists of periodically stacked 2-dimensional amorphous Nb-W-O monolayers without long-range in-plane order. The unique periodic and therefore crystalline stacking along one principal axis enables direct imaging and revealed that the amorphous Nb-W-O monolayers formed in agreement with the Zachariasen model for 2 dimensions. Our findings show that the gap between crystalline and amorphous materials does not only depend on medium-range order but can also apply to principal dimensions within the same solid.
Orientation-dependent production of normal Archimedean and dynamical spirals for revealing orbital symmetries in diatomic multi-orbital molecules
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Alignments in the orientation of radio jets from AGN and their host galaxies
It is well established that active galactic nuclei (AGNs) play an important role in the evolution of galaxies. These AGNs can be linked to the accretion processes onto massive black holes and past merger events in their host galaxies, which may lead to different alignments of the jets with respect to the host galaxies. This paper presents a study of the position angle (PA) differences between radio and optical images of radio-AGNs based on the second data release (DR2) of the Low Frequency Array (LOFAR) Two-Meter Sky Survey (LoTSS), theKarl G. JanskyVery Large Array Faint Images of the Radio Sky at Twenty-Centimeters Survey (FIRST), the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, and the Sloan Digital Sky Survey (SDSS). We assessed PA measurement biases in the data and classified the radio-AGNs based on the radio luminosity and infrared colour from the Wide-field Infrared Survey Explorer (WISE). This resulted in the largest sample of radio AGNs with reliable radio and optical PA measurements published to date, with a total of 3682 AGNs. The PA difference (dPA) distributions for the radio-AGN sample show a prominent minor-axis alignment tendency. Based on some simple assumptions, we simulated the projection effect to estimate the intrinsic jet-galaxy alignment. The observed dPA distribution can be well described by a two-component jet-alignment model in which one component is more aligned with the minor axis of the host galaxy than the other. The fitting results indicate that the jet alignment is dependent on radio luminosity and the shape of the host galaxies, with the jets being more likely to be aligned with the minor axis of the galaxy for lower radio luminosity and for optically more elongated radio-AGNs. The minor-axis alignment of the entire sample may suggest a coherent accretion model present in most AGN host galaxies, while a considerable number of luminous radio-AGNs with massive host galaxies might have undergone accretion – according to the chaotic model – or past merger events.
Rotation of electrothermal-instability-driven overheating structure due to helically oriented surface magnetic field on a high-current-density aluminum rod
Experiments on the 1-MA, 100-ns-rise-time Mykonos Facility demonstrate rotation of electrothermal instability (ETI)-driven overheating structure on 1.00-mm-diameter, 10-nm-surface roughness, 99.999%-pure aluminum rods, which are pulsed with helically polarized surface magnetic field. Rods are machined to include pairs of 10-micron-scale quasi-hemispherical voids or “engineered defects (ED)” which provide the dominant current density perturbation from which ETI grows most rapidly. Experiments include an axial magnetic field component through the addition of a helically wound return-current electrode or “helical return can (HRC).” For a given HRC design, azimuthal field (B ɵ ) and axial field (B z ) components rise at a prescribed and fixed ratio, driving an increasing magnetic field of constant polarization at the rod's surface; most experiments generated surface magnetic field at a 15-degree field polarization angle (from horizontal) defined as ɸ B = arctan(B z /B ɵ ). ETI-driven emission patterns from individual ED are observed to rotate along ɸ B , while emission patterns from dielectric-coated ED pairs are shown to elongate and preferentially merge along ɸ B , in qualitative agreement with 3D-magnetohydrodynamic simulations. These data strongly support that for a randomized distribution of current density perturbations on a high-current density conductor, nearby perturbations will favorably merge about ɸ B , with the degree of merging increasing with current. Such observations offer fundamental new understanding of the seeding mechanisms of the helical magneto-Rayleigh Taylor (MRT) instabilities observed from axially magnetized magnetically driven imploding liners.
MS-POFT: multiscale phase-orientation guided feature transform for multi-modal image matching
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Electron Beam-Induced Phase Transformations in Different Crystal Orientations of a 2D van der Waals Magnet
To control materials properties at the nanoscale, the well-focused electron beam of the scanning transmission electron microscope (STEM) can be used as a tool to engineer structure with atomic precision. For 2D magnets, especially the highly anisotropic materials AgCrP2S6 and CrSBr, we find here that the STEM serves as a powerful tool for sculpting the arrangement of atoms, with the potential to modulate local magnetic properties.
Controlling Deformation in Al/Ti: How Interface Roughness and Orientation Drive Bimetal Mechanics
The microstructural characteristics and morphology of interfaces in metals can be crucial in governing the initiation of plasticity and early deformation mechanisms under extreme conditions. During high-strain-rate deformation, these interfaces significantly affect dislocation nucleation, twinning, and other mechanisms that directly impact material strength and failure. Despite their importance, a substantial knowledge gap remains between the observed macroscopic material behavior and the underlying role of bimetal interfaces in plasticity initiation. Here, to address this gap, large-scale molecular dynamics simulations are performed on Al/Ti bimetal structures to examine the effect of interface characteristics on the onset of plasticity under uniaxial compression. Specifically, this study investigates how interface roughness (flat vs waveform interfaces) modifies the initiation of plastic events in the microstructure. Atomistic simulations indicate that interface roughness (a microscopic behavior) reduces the stress required for dislocation nucleation, thereby reducing the peak stress relative to a flat interface. For the square interface, the step height strongly influences plasticity initiation by setting the separation of locally flat regions. Varying the interface rotation relative to the loading direction (macroscopic behavior) reveals that the peak stress for both flat and waveform interfaces initially decreases and then increases with rotation, accompanied by a shift in dominant mechanisms—from Al twinning (flat) to interface sliding and Ti-dominated phase transformation and twinning at lower angles. The change in the stress-strain slope during initial compression reflects how rotation alters the resolved shear stress and activates different slip systems. Overall, the study provides valuable insights into the role of bimetal interfaces in controlling plasticity initiation and early deformation pathways for Al/Ti under extreme loading conditions.
Improved Snow Loss Modeling Accounting for the Orientation of Modules
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Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration
This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.
Object-Oriented Controllable High-Resolution Residential Energy (OCHRE) (TM) Model
This presentation describes the OCHRE model as part of NREL's Powered By webinar series. OCHRE is a building energy modeling tool designed to model flexible loads in residential buildings. OCHRE includes detailed models and controls for flexible devices including HVAC equipment, water heaters, electric vehicles, solar PV, and batteries. It is designed to run in co-simulation with custom controllers, aggregators, and grid models.
Scalable, Trustworthy, Agile, Goal-oriented, Efficient, and Data-assimilated Data-Driven Closure Models (STAGED DDCMs)
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Scalable Application-Oriented Benchmarking of Quantum Computers
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Data-Enhanced, Resilience-Oriented Community Microgrid Planning and Operations [Slides]
This presentation is for a DOE workshop hosted by New York University and Northeastern University on "Unleashing the Power of Data and AI In Distribution Grid Operation and DER Management". I presented the work conducted under a SETO-funded project and an OE-funded project.
Discrete Goal-Oriented Error Estimation and Mesh Adaptation for Finite Deformation Elastoplasticity
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Developing Techniques for Focused Ion Beam Milling and In-Situ Micro-Compression to Characterize Orientation-Dependent Mechanical Properties of Molecular Crystals
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