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At least 595 records · Page 33

Charge collection and trapping mechanisms in hexagonal boron nitride epilayers

Understanding charge collection and trapping mechanisms is crucial for using hexagonal boron nitride (h-BN) as active layers for many photonic and electronic devices such as deep UV detectors and emitters, neutron detectors, and single photon emitters. Charge collection and trapping mechanisms in h-BN epilayers have been investigated by probing impurity related optical emissions under an applied electrical field. Our results suggested that the existence of oxygen impurities affects the charge collection efficiency and results in an additional emission peak at 3.75 eV, corresponding to a donor-acceptor pair (DAP) recombination involving O N (oxygen residing on the nitrogen site) donors and the V B -H (boron vacancy bonded with hydrogen complex) deep level acceptors. Experimental results further revealed that the applied electric field induces an anti-correlation between the emission intensity of the DAP transition and the charge collection efficiency from which it was shown that it is possible to find an expression to quantitatively measure the maximum charge collection efficiency in h-BN. The results introduce not only a coherent picture for the relationship between common impurities in h-BN and charge collection and trapping mechanisms but also useful insights into possible approaches to improve the quality, purity, and charge collection of the h-BN epilayers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

CYDRES: CYber Defense and REsilient System for securing grid-interactive efficient buildings

Smart buildings, especially Grid-interactive Efficient Buildings (GEBs), suffer from cyber-attacks and physical faults due to the integration of a large number of sensors and controls, connected devices, and associated communication networks. This study demonstrated a real-time advanced building resilient platform, called CYber Defense and REsilient System (CYDRES), which is deployable for existing and emerging Building Automation Systems (BASs). CYDRES aims to empower GEBs with cyber-attack-immune capabilities through multi-layer prevention and adaptation mechanisms to monitor, detect, and respond to cyber-attacks and physical operational faults. CYDRES is demonstrated through real-time experiments in a Hardware-in-the-Loop (HIL) testbed.

Building automation system, Cyber-attacks, Physica↗

Modulating surface acoustic wave generation through superconductivity

Surface acoustic waves (SAWs), with their five orders-of-magnitude slower propagation velocity, allow for considerably shorter wavelengths at the same frequency compared to electromagnetic waves. The short wavelengths allow for device miniaturization and on-chip integration. The generic design of these devices involves piezoelectric substrates with comb-like arrays of Al or Au electrodes known as interdigitated transducers (IDTs) deposited on the surface. However, Al and Au both have shortcomings at the cryogenic temperatures required for quantum applications, namely, the formation of two-level systems and the lack of superconductivity perpetuating Ohmic losses, respectively. In this work, SAWs are generated in the high-MHz to low-GHz range using niobium nitride (NbN) interdigitated transducers and Bragg reflectors. We demonstrate the fabrication of acoustic devices through photolithography and reactive ion etching. The sharp transition between superconducting and normal states and the corresponding change in SAW transmission allows for fine control of the “on” (superconducting) and “off” (normal) states of NbN, with a ΔT = 1 K separating the transmission minimum and maximum. We demonstrate a 16× difference in transmission between the “on” and “off” states of the device. The SAW transmission behavior mirrors the change in resistance of NbN at its T c . These findings open up new possibilities for the integration of NbN SAW resonators into existing quantum architectures based on NbN and a method for adjusting transmission properties independent of applied voltage.

36 MATERIALS SCIENCE↗

Magnetic skyrmion diode: Unidirectional skyrmion motion via symmetry breaking of potential energy barriers

In this work, we realize a magnetic skyrmion diode operated by a unidirectional skyrmion transport that flows in only one direction, which is highly significant for information processing in spintronic and nanoelectronic devices. We easily control the skyrmion transport by engineering asymmetric shapes of geometric structures. Here, we present a simple method to describe the underlying mechanism behind the unidirectional skyrmion transport by characterizing the topography of potential energy surfaces from a purely geometric perspective. Our approach enables a deeper physical insight into skyrmion transport manipulation and efficient design of skyrmion-based devices in geometric structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Momentum-Space Observation of Optically Excited Nonthermal Electrons in Graphene with Persistent Pseudospin Polarization

The unique optical properties of graphene, with broadband absorption and ultrafast response, make it a critical component of optoelectronic and spintronic devices. Using time-resolved momentum microscopy with high data rate and high dynamic range, we report momentum-space measurements of electrons promoted to the graphene conduction band with visible light and their subsequent relaxation. Here, we observe a pronounced nonthermal distribution of nascent photoexcited electrons with lattice pseudospin polarization in remarkable agreement with results of simple tight-binding theory. By varying the excitation fluence, we vary the relative importance of electron-electron vs electron-phonon scattering in the relaxation of the initial distribution. Increasing the excitation fluence results in increased noncollinear electron-electron scattering and reduced pseudospin polarization, although up-scattered electrons retain a degree of polarization. These detailed momentum-resolved electron dynamics in graphene demonstrate the capabilities of high-performance time-resolved momentum microscopy in the study of 2D materials and can inform the design of graphene devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TEAMER Technical Support of Ramboll's for Numerical Modeling of WECs to Support OES Task 10: Cooperative Research and Development (Final Report)

National Technology & Engineering Solutions of Sandia, LLC (NTESS) in collaboration with the National Renewable Energy Laboratory (NREL), and with guidance from Ramboll, will perform fluid dynamics simulations to support of The Ocean Energy Systems (OES) Energy Technology Collaboration Program Task 10 Wave Energy Converters (WEC) Modelling Verification and Validation effort. Specific numerical simulations include the fixed device wave impingement studies to benchmark the performance of simulation techniques against physical testing results.

16 TIDAL AND WAVE POWER↗

PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite

Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.

42 ENGINEERING↗

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future.

Gao, Zhiming↗

Analytical model of plasma response to external magnetic perturbation in absence of no-slip condition

Recent simulation and experimental results suggest that the magnetic island and flow on a resonant surface often do not satisfy the “no-slip” condition in the steady state. A new theoretical model on a nonlinear plasma response to external magnetic perturbation in the absence of a no-slip condition is proposed. The model is composed of the equations for the evolution of both the width and phase of the magnetic island due to forced reconnection driven by the external magnetic perturbation, and the force-balance equation for the plasma flow. When the island width is much less than the resistive layer width, the island growth is governed by the linear Hahm–Kulsrud–Taylor solution in the presence of time-dependent plasma flow. In the other regime when the island width is much larger than the resistive layer width, the evolution of both the island width and phase can be described using the Rutherford theory. The island solution is used to construct the quasilinear electromagnetic force, which, together with the viscous one, contributes to the nonlinear variation in plasma flow. The no-slip condition assumed in the conventional error field theory is not imposed here, where the island oscillation frequency depends on but does not necessarily equal to the plasma flow frequency at the rational surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Autoregressive long-horizon prediction of plasma edge dynamics *

Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data for the KSTAR tokamak, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1–100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.

autoregressive deep learning↗

Ferroic phase transitions and magnetoelectric coupling in cobalt doped BaTiO 3

Magnetoelectric (ME) materials exhibit interesting physics with cross coupling between ferroelectric and magnetic order parameters and thus strong potential to be utilized in memory, spintronics and other multifunctional electronic/magnetic devices. Doping of suitable transition metals in ferroelectrics can induce magnetism and ME coupling and modify the physical properties. Here, we report the structural, electronic, magnetic and ME coupling of 3.5, 5 and 7.5 mol% cobalt doped BaTiO 3 (BTO) ceramics. X-ray diffraction and Raman spectroscopy indicate that the samples are single phase having a tetragonal crystal structure with P4mm symmetry. The tetragonality ratio is found to decrease with increasing cobalt content. We observed a Fano-like asymmetric peak in the [A 1 (LO 1 )] Raman mode at ~173 cm -1 in all the cobalt doped BTO samples. The cobalt dopants are shown to be uniformly distributed throughout the surface of the samples. We observed a lowering of the ferroelectric transition temperature and increasing diffusivity parameter with increasing cobalt concentration. The electrical properties of all the samples have been investigated in detail by impedance spectroscopy and ac conductivity studies before and after the ferroelectric phase transitions. All the samples show hysteretic ferroelectric behavior with a clear saturation state that decreases with increasing cobalt content. The observed ferroelectricity in these samples is intrinsic in nature. The 3.5% cobalt doped BTO sample exhibits paramagnetic behavior whereas the 5 and 7.5% cobalt doped BTO samples show ferromagnetic ordering below 43 K. The 7.5% cobalt doped BTO samples show significant ME coupling.

36 MATERIALS SCIENCE↗

Ultracompact mirror device for forming 20-nm achromatic soft-X-ray focus toward multimodal and multicolor nanoanalyses

Abstract Nanoscale soft-X-ray microscopy is a powerful analysis tool in biological, chemical, and physical sciences. To enhance its probe sensitivity and leverage multimodal soft-X-ray microscopy, precise achromatic focusing devices, which are challenging to fabricate, are essential. Here, we develop an ultracompact Kirkpatrick-Baez (ucKB) mirror, which is ideal for the high-performance nanofocusing of broadband-energy X-rays. We apply our advanced fabrication techniques and short-focal-length strategy to realize diffraction-limited focusing over the entire soft-X-ray range. We achieve a focus size of 20.4 nm at 2 keV, which represents a significant improvement in achromatic soft-X-ray focusing. The ucKB mirror extends soft-X-ray fluorescence microscopy by producing a bicolor nanoprobe with a 1- or 2-keV photon energy. We propose a subcellular chemical mapping method that allows a comprehensive analysis of specimen morphology and the distribution of light elements and metal elements. ucKB mirrors will improve soft-X-ray nanoanalyses by facilitating photon-hungry, multimodal, and polychromatic methods, even with table-top X-ray sources.

Science & Technology - Other Topics↗

Magnetic circuit for Abrikosov vortices: Vortex motion in a periodic labyrinth of magnetic T and I-shaped elements under a superconducting film

Here we explore tailored labyrinth-like vortex motion in a niobium film placed on top of periodic arrays of T and I -shaped permalloy elements by imaging the vortex distribution in magnetic fields applied perpendicular to the superconducting layer under different in-plane polarizations of the TI structure. At low temperatures, we observe pronounced meandering of vortex motion around the TI elements. Remarkably, vortices can easily penetrate the sample along the TI columns even though the average vortex pinning in the patterned area is larger than in a bare niobium film. Accordingly, at temperatures close to the superconducting transition temperature, T c , the voltagecurrent curves in the patterned area show an earlier departure from the zero-resistivity state at small currents, followed by slower growth with increasing current as compared to the un-patterned film. We present a model based on magnetostatic interactions between magnetic charges at the edges of the polarized TI-elements and single magnetic charges of induced vortices to account for this behavior. We expect that similar magnetic structures imposing labyrinth-like vortex motion could be used for collective entanglement of vortices envisioned in quantum circuit operations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Prediction of electric and magnetic fields from spectral data using machine learning algorithms for Doppler-free saturation spectroscopy diagnostics

The prediction of electric and magnetic field amplitudes from atomic spectral data is critical for plasma control in fusion devices such as tokamaks. Conventional approaches that rely on physics-based models are computationally expensive and unsuitable for real-time applications. In this work, we develop and benchmark three machine learning algorithms—simulation-based inference (SBI), fully connected neural networks (FCNN), and histogram-based gradient boosting regression (GBR-Hist)—to infer field intensities directly from Doppler-free saturation spectroscopy (DFSS) spectra. Synthetic datasets of spectra were generated using the EZSSS code and evaluated both with and without added Poisson noise to mimic experimental conditions. We find that SBI achieves the highest accuracy and robustness, FCNN provides a strong balance of accuracy and computational efficiency for real-time applications, and GBR-Hist offers the fastest inference but is more sensitive to noise. Furthermore, these results demonstrate the potential of machine learning to accelerate DFSS analysis and enhance its utility for plasma diagnostics and control.

Doppler-free saturation spectroscopy↗

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

To improve the marketability of novel microreactor designs, there is a need for automated and optimal control of these reactors. This paper presents a methodology for performing multiobjective optimization of control drum operation for a microreactor under normal and off-nominal conditions. Here, two different case studies are used where the control drum configuration is optimized for the reactor to be critical with some desired power distribution that would satisfy peaking limits. A surrogate model for power distribution is developed based on a feedforward neural network. The process for determining weights for scalarization of the multiobjective optimization problem is also detailed. Six optimization algorithms: evolutionary strategies, differential evolution, grey wolf optimization, Harris hawks optimization, moth flame optimization and particle swarm optimization, are all applied to these cases and the results analyzed. Although all these algorithms will demonstrate optima-seeking behavior, for real-time control it is necessary to identify the best algorithm to efficiently provide reasonable optima without operator interference. The moth flame optimization algorithm was found to perform particularly well on both cases. Overall, it was found that the algorithms capable of supplying the best optima were also the most consistent. Finally, the found optima were verified with the original model used to train surrogates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Constrained stellarator coil curvature optimization with FOCUS

Finding less complicated coils that have adequately low field errors is a crucial step in stellarator development. One coil metric that is of high importance is the maximum curvature of the coil centreline, or coil single filament. Conductors cannot be bent below some threshold minimum radius of curvature. High coil curvatures can cause strains to exceed acceptable levels, especially in superconducting coils. We investigate three ways to optimize coil curvature and find that applying penalty functions to the coil curvature solves for coils that have a constrained maximum curvature and low field error. Penalty functions are implemented in FOCUS and coil solutions optimized for an HSX-like ‘plasma boundary’ are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MagNetUS: a magnetized plasma research ecosystem

MagNetUS is a network of scientists and research groups that coordinates and advocates for fundamental magnetized plasma research in the USA. Its primary goal is to bring together a broad community of researchers and the experimental and numerical tools they use in order to facilitate the sharing of ideas, resources and common tasks. Discussed here are the motivation and goals for this network and details of its formation, history and structure. An overview of associated experimental facilities and numerical projects is provided, along with examples of scientific topics investigated therein. Finally, a vision for the future of the organization is given.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Strain-Induced Trapping of Indirect Excitons in MoSe 2 /WSe 2 Heterostructures

Understanding and control of excitons in transition metal dichalcogenide (TMD) materials are essential for the exploration of the rich many-body physics in TMDs and their applications in photonic and optoelectronic devices. Local strain modulation has been utilized as an effective approach for creating potential traps and localizing intralayer excitons in TMD monolayers. Here, we investigate the effect of strains on indirect excitons in TMD heterostructures. The emergence of narrow spectral peaks from the strained sites together with their drastically reduced lifetimes indicates the formation of potential traps in the heterostructures and the trapping of indirect excitons in them. The absence of photon-antibunching from these trapped indirect excitons further reveals their weak localization in the potential traps. Here, our study indicates that, compared to the case of intralayer excitons, narrower potential traps are required for obtaining highly localized indirect excitons due to their unique properties. These findings have important implications for creating long-wavelength quantum emitters in TMD heterostructures and the exploration of indirect exciton condensation and motion in TMDs.

36 MATERIALS SCIENCE↗