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At least 811 records · Page 45

Metrology of Time-Domain Soft X-Ray Attosecond Pulses and Reevaluation of Pulse Durations of Three Recent Experiments

Attosecond pulses in the soft x-ray (SXR) to water-window energy region offer the tools for creating and studying target-specific localized inner-shell electrons or holes in materials, enabling monitoring or controlling charge and energy flows in a dynamic system on attosecond timescales. Recently, a number of laboratories have reported generation of continuum harmonics in the hundred-electron-volt to kilovolt region with few-cycle long-wavelength mid-infrared lasers. These harmonics have the bandwidth to support pulses with durations of a few to a few-ten attoseconds. But harmonics generated in a gas medium have attochirps that cannot be fully compensated by materials over a broad spectral range; thus, realistically what are the typical shortest attosecond pulses that one can generate? To answer this question, it is essential that the temporal attosecond pulses be accurately characterized. By reanalyzing the soft x-ray attosecond metrology reported in three recent experiments using a newly developed broadband phase retrieval algorithm, we demonstrate here that the generated attosecond pulses in the first two papers have durations of about 60 as, longer than what they have reported. Similarly, the duration from the third experiment is retrieved to be about half of the 322-as upper limit cited in that work. We also introduce the autocorrelation (AC) of the streaking spectrogram. By comparing the ACs from the experiments and from the retrieved SXR pulses, the accuracy of the retrieved results can be directly visualized. Our retrieval method is fast and accurate, and it shall provide a powerful tool for the metrology of the emerging few-ten-attosecond pulses.

74 ATOMIC AND MOLECULAR PHYSICS↗

Structure and electronic tunability of acene alkylamine based layered hybrid organic-inorganic perovskites from first principles

Twelve layered hybrid organic-inorganic perovskites combining oligoacene derivatives [phenylmethylammonium (PMA), naphthylmethylammonium (NMA), anthrylmethylammonium (AMA), and tetrylmethylammonium (TMA)] and lead halides (Cl - , Br - , and I - anions) are investigated by first-principles density functional theory (DFT), showing broad, rational tunability of band gap, quantum well type, and spin-dependent energy band properties. Six compounds are known from previous syntheses and are used to devise a computational search space for likely low-energy structures. Among the six known compounds, a refined structure is identified for (NMA) 2 ⁢ PbCl 4 and a new, lower-energy structure is suggested for (AMA) 2 ⁢PbCl 4 . The DFT based search methodology is next applied to predict the likely structures for the six unknown compounds. Computationally predicted energy levels for all 12 compounds from spin-orbit coupled hybrid DFT reveal tunable type I quantum well alignments, with frontier orbitals located on the inorganic component, on the organic component, or on both, as controlled by cation and anion selection. In conclusion, several structures spontaneously break local and global inversion symmetry, causing strong spin splitting of the conduction bands [up to 0.12 eV for (PMA) 2 ⁢PbCl 4 ] and showing potential for spin-dependent transport properties and future spintronic and tunable chiroptical applications.

36 MATERIALS SCIENCE↗

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗

An optimization-based strategy for peridynamic-FEM coupling and for the prescription of nonlocal boundary conditions

We develop and analyze an optimization-based method for the coupling of a static peridynamic (PD) model and a static classical elasticity model. The approach formulates the coupling as a control problem in which the states are the solutions of the PD and classical equations, the objective is to minimize their mismatch on an overlap of the PD and classical domains, and the controls are virtual volume constraints and boundary conditions applied at the local-nonlocal interface. Our numerical tests performed on three-dimensional geometries illustrate the consistency and accuracy of our method, its numerical convergence, and its applicability to realistic engineering geometries. We demonstrate the coupling strategy as a means to reduce computational expense by confining the nonlocal model to a subdomain of interest, and as a means to transmit local (e.g., traction) boundary conditions applied at a surface to a nonlocal model in the bulk of the domain.

97 MATHEMATICS AND COMPUTING↗

Using Deep Mutational Data and Machine Learning to Guide Outbreak and Pandemic Response

A significant fraction of pathogens known to infect humans originate in non-human (zoonotic) hosts (Taylor, Latham, and Woolhouse 2001), and new and emerging pathogens continue to spill over into the human population more frequently at an alarming rate (e.g., SARS, MERS, Cholera, etc.). The recent outbreaks of Ebola virus in West Africa and the ongoing SARS-CoV-2 pandemic demonstrate the need for rapid and reliable assessments of viral phenotype information to help inform scientists and policy makers how best to control the spread of disease. Further understanding of the virus pathogenic evolutionary space and potential trajectory could guide appropriate control measures to limit the spread of a new virus throughout the local and global human population.

59 BASIC BIOLOGICAL SCIENCES↗

QPress: Quantum Press for Next-Generation Quantum Information Platforms

Quantum information science (QIS) holds promise for revolutionizing computation, communication, and sensing. Of course, realizing this promise requires material platforms that can host quantum bits with pre-assigned characteristics that are uniquely attuned to such functionalities. For example, quantum bits for computation should be as immune as possible to any external perturbation, controllable on short time scales and scalable. In contrast, quantum bits for local metrology should be as small as possible and sensitive to specific fields of interest. While tremendous advances in QIS have been achieved in recent years, the underlying properties of the materials that host these quantum bits remains one of the key limitations in their performance.

36 MATERIALS SCIENCE↗

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗

FPGA-based computing system for processing data in size, weight, and power constrained environments

Technologies that are well-suited for use in size, weight, and power (SWAP)-constrained environments are described herein. A host controller dispatches data processing instructions to hardware acceleration engines (HAEs) of one or more field programmable gate arrays (FPGAs) and further dispatches data transfer instructions to a memory controller, such that the HAEs perform processing operations on data stored in local memory devices of the HAEs in parallel with other data being transferred from external memory devices coupled to the FPGA(s) to the local memory devices.

Napier, Matthew↗

Near-field-driven radiative thermal dynamics in aperiodic photonic nanostructures

Harnessing structural correlations in near-field plasmonic and polaritonic systems hold untapped potential for controlling light–matter interactions at the nanoscale. By tuning these correlations, one can reshape mode localization, coupling, and spectral distribution which are properties central to manipulating energy transport and field enhancement in nanophotonic platforms. We exploit Vogel spirals, an aperiodic geometry where a single parameter dictates spatial correlations, to show how correlation strength reshapes the modal spectrum and transient dynamics of near-field coupling. As a proof of concept, we demonstrate that aperiodic configurations outperform both uncorrelated (random) and periodic arrays in controlling near-field radiative heat-transfer dynamics. These results establish deterministic aperiodic order as a powerful platform for tailoring correlated electromagnetic responses in next-generation nanophotonic devices.

36 MATERIALS SCIENCE↗

Transition of a network of nonlinear interactions into a regime of strong nonlinear fluctuations: A paradigm for the edge localized mode onset

We study how a network of nonlinear oscillators transits into a regime of strong nonlinear fluctuations when perturbed by a triad. In this regime, most of the potential energy contained in the waves is made available to the system through strong nonlinear fluctuations. This analysis is motivated by recent experimental observations [Dominski and Diallo, Plasma Phys. Control. Fusion 62, 095011 (2020)] where it was found that magnetic fluctuations trigger the onset of edge localized modes by suddenly exciting a network of nonlinear interactions. In our study, we consider the simplest system of many harmonic oscillators that are organized in a network of nonlinear triads. We model and simulate the sudden transition of this network of triads into a regime of strong nonlinear fluctuations—reminiscent of the onset of edge localized modes in tokamaks. This transition is triggered by the activation of a nonlinear perturbation. An abrupt rise of the system's disorder (an entropy-like quantity) is measured during the transition. This transition from weak to strong nonlinear fluctuations is even more abrupt when these fluctuations are chaotic, i.e., when the timescale of the nonlinear interaction is comparable to the timescale of the wave oscillations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Achieving designed texture and flows in bulk active nematics using optimal control theory

Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling optogenetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Furthermore, our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.

Complex systems theory↗

Laser-induced digital oxidation for copper-based flexible photodetectors

Copper oxide compounds (Cu x O) with bandgaps of 1.3–2.1 eV (CuO) and 2.1–2.6 eV (Cu 2 O) have been investigated as promising p-type semiconducting materials. Cu x O is generally obtained by deposition or thermal oxidation, but those methods are not optimal for flexible substrates. Furthermore, additional patterning steps are required to fabricate devices. In this work, we present an easy, controllable method to fabricate a metal-semiconductor-metal (MSM) photodetector using laser-induced oxidation of a thin Cu film. After laser irradiation, the Cu film is heated under ambient conditions, and this leads to a thermal oxidation reaction, in which Cu oxide is monolithically formed in the Cu film and a Cu-Cu x O-Cu MSM structure is produced. Since the laser offers localized heating, an arbitrary CuxO pattern can be written in the Cu film by spatially controlled heating. In addition, by optimizing the heating time, the laser-induced oxidation can be successfully performed even on a flexible substrate. To study the laser-induced oxidation, we examined the correlation between laser parameters and the oxidation pattern and analyzed the composition using scanning electron microscopy, Raman spectroscopy, and X-ray photoemission spectroscopy. Furthermore, we measured the transient photoresponse and employed scanning photocurrent microscopy to investigate the mechanism of carrier transport behavior.

36 MATERIALS SCIENCE↗

Adaptive Model-Free Vehicle Path-Tracking via Fast-Converging Prescribed-Time Newton-Based Extremum-Seeking Control

Model-free control (MFC) offers a simple and effective approach to automated vehicle path-tracking without requiring an explicit plant model for control law design. However, gain tuning in MFC is typically carried out through trial-and-error, which can be time-consuming and may lead to suboptimal performance. To address this limitation, extremum-seeking-based adaptive MFC has shown promise by enabling real-time adaptation of control gains, without relying on a predefined vehicle model. Nonetheless, existing ESC approaches often suffer from slow convergence. This paper integrates MFC, employing longitudinal and lateral ultra-local models of a rear-wheel-drive vehicle, with a novel prescribed-time (PT) Newton-based extremum-seeking control (ESC) strategy that ensures rapid convergence of control gains within the prescribed time. Unlike conventional gradient-based ESC methods, the PT Newton-based ESC leverages artificial delays and time-periodic gains, not only to guarantee convergence within the specified time, but also to compensate for feedback delays. Simulation results demonstrate that the proposed approach significantly improves gain adaptation speed and tracking accuracy. This work advances adaptive model-free vehicle control by offering a high-performance, delay-resilient alternative to existing ESCMFC frameworks.

Waleed khan, Muhammad [The University of Texas at ↗

Nanoscale Imaging and Control of Volatile and Non-Volatile Resistive Switching in VO 2

Control of the metal-insulator phase transition is vital for emerging neuromorphic and memristive technologies. The ability to alter the electrically driven transition between volatile and non-volatile states is particularly important for quantum-materials-based emulation of neurons and synapses. The major challenge of this implementation is to understand and control the nanoscale mechanisms behind these two fundamental switching modalities. In this study, in situ X-ray nanoimaging is used to follow the evolution of the nanostructure and disorder in the archetypal Mott insulator VO 2 during an electrically driven transition. Our findings demonstrate selective and reversible stabilization of either the insulating or metallic phases achieved by manipulating the defect concentration. This mechanism enables us to alter the local switching response between volatile and persistent regimes and demonstrates a new possibility for nanoscale control of the resistive switching in Mott materials.

36 MATERIALS SCIENCE↗

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗

Star-forming S0 Galaxies in SDSS-MaNGA: fading spirals or rejuvenated S0s?

ABSTRACT We investigate the origin of rare star formation in an otherwise red-and-dead population of S0 galaxies, using spatially resolved spectroscopy. Our sample consists of 120 low redshift (z < 0.1) star-forming S0 (SF-S0) galaxies from the SDSS-IV MaNGA DR15. We have selected this sample after a visual inspection of deep images from the DESI Legacy Imaging Surveys DR9 and the Subaru/HSC-SSP survey PDR3 to remove contamination from spiral galaxies. We also construct two control samples of star-forming spirals (SF-Sps) and quenched S0s (Q-S0s) to explore their evolutionary link with the star-forming S0s. To study star formation at resolved scales, we use dust-corrected H α luminosity and stellar density (Σ⋆) maps to construct radial profiles of star formation rate (SFR) surface density (ΣSFR) and specific SFR (sSFR). Examining these radial profiles, we find that star formation in SF-S0s is centrally dominated as opposed to disc-dominated star formation in spirals. We also compared various global (size–mass relation, bulge-to-total luminosity ratio) and local (central stellar velocity dispersion) properties of SF-S0s to those of the control sample galaxies. We find that SF-S0s are structurally similar to the quenched S0s and are different from star-forming spirals. We infer that SF-S0s are unlikely to be fading spirals. Inspecting stellar and gas velocity maps, we find that more than $50{{\ \rm per\ cent}}$ of the SF-S0 sample shows signs of recent galaxy interactions such as kinematic misalignment, counter-rotation, and unsettled kinematics. Based on these results, we conclude that in our sample of SF-S0s, star formation has been rejuvenated, with minor mergers likely to be a major driver.

79 ASTRONOMY AND ASTROPHYSICS↗

Terahertz-polarizing effect based on geometric anisotropy of Ti 3 C 2 T x MXene nanosheets

Two-dimensional (2D) nanomaterials have garnered considerable attention due to their unique properties, such as thinness and excellent electronic properties. The inherent anisotropy of 2D nanomaterials, which is characterized by their high aspect ratio, can maximize the directional functionality to enhance the conductivity and utilization of edges. Here, we demonstrate how to utilize the edges of titanium carbide (Ti 3 C 2 T x ) MXene nanosheet to control the linear polarization in the terahertz (THz) frequency range. By a simple and unique vertical alignment exploiting the high surface charge and excellent colloidal dispersibility of MXene nanosheets, MXene nanosheets are vertically oriented along an applied AC electric field. The well-aligned edges justify the THz polarizing effect, revealing outstanding performances such as the broadband coverage in 0.2–1.5 THz and an exceptional extinction ratio reaching 20 dB. Furthermore, we vary the local orientation of the vertical MXene nanosheets by tailoring the applied electric field, enabling spatially controllable polarization capabilities. Our results can provide a generic tool for the utilization of 2D nanomaterials in diverse potential applications in optics and electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoscale reshaping of resonant dielectric microstructures by light-driven explosions

Femtosecond-laser-assisted material restructuring employs extreme optical intensities to localize the ablation regions. To overcome the minimum feature size limit set by the wave nature of photons, there is a need for new approaches to tailored material processing at the nanoscale. Here, we report the formation of deeply-subwavelength features in silicon, enabled by localized laser-induced phase explosions in prefabricated silicon resonators. Using short trains of mid-infrared laser pulses, we demonstrate the controllable formation of high aspect ratio (>10:1) nanotrenches as narrow as ~ $λ / 80$. The trench geometry is shown to be scalable with wavelength, and controlled by multiple parameters of the laser pulse train, such as the intensity and polarization of each laser pulse and their total number. Particle-in-cell simulations reveal localized heating of silicon beyond its boiling point and suggest its subsequent phase explosion on the nanoscale commensurate with the experimental data. The observed femtosecond-laser assisted nanostructuring of engineered microstructures (FLANEM) expands the nanofabrication toolbox and opens exciting opportunities for high-throughput optical methods of nanoscale structuring of solid materials.

42 ENGINEERING↗