Browse Articles

Structural uniformity and grain formation in inch-scale few-layer YBa2Cu3O7 <b>−</b> <i>x</i> epitaxial films on MgO

Here, we report a systematic study of structural uniformity and grain formation in the initial layers of epitaxial YBa2Cu3O7−x (YBCO) films grown on MgO substrates by pulsed laser deposition. On a 2-in. YBCO film, we performed synchrotron x-ray crystal truncation rod measurements and three-dimensional reciprocal space mapping to assess the spatial homogeneity and grain texture across the entire 2-in. film. The results reveal an obvious film quality variation from center to edge, with significantly better crystallinity and atomic coverage near the center. More importantly, we find that the ultra-thin YBCO film is predominantly composed of c-axis-oriented R0° grains. The extracted lattice parameters are close to those of bulk YBCO, indicating that substrate-induced strain is largely relaxed within the initial few unit cells. These findings strongly suggest that the formation of R0° grains at the early growth stage is primarily governed by interfacial effects at the YBCO/MgO interface, whereas the emergence of R45° grains in thicker films is driven mainly by the film growth specifics. Our insights provide critical guidelines for further optimizing the fabrication of the large-area YBCO film on MgO for applications in ultra-low-loss superconducting microwave devices.

Symbiosis collapses during development of asexual offspring in the absence of heterotrophic feeding in a model cnidarian–algal symbiosis

Non-pinched hysteresis in CrO <i>x</i> /TiO <i>y</i> -based memristive devices: Modeling and analysis

Transition-metal oxide memristors are promising for neuromorphic computing, yet most SPICE models overlook material-specific effects such as oxygen stoichiometry and non-pinched hysteresis. Here, we systematically study CrOx/TiOy memristors fabricated under controlled oxygen concentrations (10%–50%) and propose an improved SPICE-compatible model. The devices exhibit oxygen-dependent resistive switching, retention, and pulse-driven plasticity, with optimal performance at 40% oxygen. Our model explicitly reproduces the non-pinched hysteresis observed in I–V curves, consistent with behaviors such as ion immigration, charge trapping, and remnant polarization, and achieves close agreement with experiments across multiple stoichiometries. Validation includes endurance, retention, and synaptic functions such as long-term potentiation/depression and spike-number/amplitude-dependent plasticity. Finally, the model is extended from single devices to a 4 × 4 crossbar array, demonstrating its scalability for artificial neural network simulations. These results emphasize the critical role of oxygen stoichiometry in CrOx/TiOy memristors and introduce a modeling framework that bridges experimental device physics with circuit-level neuromorphic applications.

SleepPACNet: new convolutional neural network considering phase-amplitude coupling for automatic sleep stage classification using single-channel electroencephalogram

Stabilizing direct laser acceleration with long-scale-length plasma targets

We investigate the influence of plasma scale length on electron beam stability in direct laser acceleration (DLA) using a series of experiments on multiple laser systems with peak power spanning from 20 to 140 TW. An ultrashort, relativistic-intensity laser pulse interacts with a pre-expanded near-critical-density plasma formed by a nanosecond pre-pulse. We show that plasma expansion times of tens of nanoseconds, corresponding to long, shallow density gradients, result in electron beam pointing stability below 1° (RMS). Two-dimensional particle-in-cell simulations reveal that extended scale lengths suppress laser-driven filamentation and promote sustained self-focusing, leading to a stable acceleration channel. These results establish long-scale-length plasma targets as a robust route to improving beam stability in DLA, specifically when applied as laser-driven electron and neutron sources. Using this electron source, we demonstrated photoneutron generation with up to 9.1×107 neutrons per shot.

ZuraNet: a hybrid rule-based intrusion detection system with deep learning for securing SCADA-driven cyber-physical systems

Water‐Cluster–Mediated Amorphous‐to‐Crystalline Transition Enables Scalable Fabrication of Stable Surfactant‐Free MOF Nanocatalyst

ABSTRACT Metal–organic framework (MOF) nanocatalysts are promising for solar‐to‐chemical conversion but often suffer hydrolytic degradation, especially in surfactant‐free, highly surface‐active forms. Here, we report a dual‐functional design that integrates amorphous nanostructuring with water‐triggered self‐coordinated crystallization to produce scalable, stable surfactant‐free MOF nanocatalysts. An amorphous pyridyl‐porphyrinic precursor is first prepared as hexagonal nanosheets via an ultrasonic‐assisted process. Upon exposure to water, cyclic hexameric water clusters bind pyridyl sites and drive reorganization into a corner‐sharing porphyrinic‐hexagon 3D honeycomb lattice, yielding robust hexagonal nanorods. Confined water clusters stabilize the lattice for &gt;2 months and generate a pronounced potential gradient that promotes charge separation. The resulting nanocatalysts achieve a hydrogen evolution rate of 223.81 mmol g −1 h −1 , representing one of the better values reported for molecular photocatalysts. This work introduces water‐cluster–induced amorphous‐to‐crystalline self‐assembly as a versatile strategy for stabilizing surfactant‐free MOF nanophotocatalysts.

A light-switchable polarity retina-inspired phototransistor for adaptive photo-sensing

The limited dynamic range and fixed response polarity of conventional photodetectors pose significant challenges for machine vision in real-world, rapidly changing illumination, leading to either blindness in low light or saturation in glare. We present a retina-inspired phototransistor based on a CdS–MoS2 van der Waals heterojunction that exhibits light-intensity-switchable photo-response polarity, enabled by gate-tunable charge recombination/injection dynamics. The device seamlessly integrates optical encryption and adaptive noise filtering in a single platform, achieving a 94.2% digit recognition accuracy under high glare. This work demonstrates a single-device platform that synergistically integrates adaptive perception, secure communication, and neuromorphic preprocessing, offering a compact and energy-efficient hardware solution for next-generation intelligent vision systems in robotics, surveillance, and human–machine interfaces.

An algorithmic system for arabic fake news detection using neural networks and transformer embeddings with class weighting

Abstract Modern communication technologies have increased the speed of news dissemination. Information can now reach wide audiences almost instantly. At the same time, these technologies can reduce traditional verification mechanisms, contributing to the accelerated spread of false information and posing potential societal and political challenges. While research on fake news detection has increased, Arabic remains under-explored due to limited datasets and the language’s morphological and semantic complexity. We compiled a multi-source Arabic news dataset consisting of 7,474 articles. The dataset was meticulously validated, achieving high labeling quality (Fleiss’ Kappa = 0.80). Preliminary experiments with baseline algorithms indicated that the neural network (NN) consistently outperformed the other models. This supported its selection as the core classifier in the proposed framework. The proposed system integrates an NN classifier with CAMeLBERT embeddings for semantic feature extraction. A comprehensive comparison was conducted with other prominent Arabic Transformers, including AraBERT, AraELECTRA, and MARBERTv2. We then evaluated multiple imbalance-handling techniques, including class weighting, undersampling, oversampling, and SMOTE. Performance was assessed under different configurations, highlighting the benefits of combining contextual embeddings with resampling strategies. Experimental results indicated that the CAMeLBERT-based neural network with class weighting achieves competitive performance across the evaluated configurations, attaining an F1-score of 96.19%, accuracy of 95.52%, precision of 95.48%, and recall of 96.90% in Arabic fake news detection. These findings indicate that the proposed model provides a reliable basis for automated Arabic fact-checking systems. In addition to predictive performance, the study strengthens methodological rigor through the integration of LIME and SHAP-based interpretability analyses. Future work will focus on assessing cross-domain generalization and investigating the feasibility of real-time deployment.

Outside Front Cover: Dibenzazepine Bridged Network Polymeric Phthalocyanines as Degradable Heterogeneous Photocatalysts (Angew. Chem. Int. Ed. 16/2026)

Viscoplastic flow in intersecting fractures

Understanding viscoplastic fluid flow in discrete fracture networks is essential for natural and industrial processes, yet the hydraulic resistance at fracture intersections remains poorly characterized. This study investigates Herschel–Bulkley fluid flow through two intersecting fractures using two approaches: a full Navier–Stokes model and a reduced Hele–Shaw approximation. The Hele–Shaw model accurately predicts hydraulic resistance for Reynolds numbers up to O(10) and Bingham numbers spanning 10−2 to 1. Resistance is largely insensitive to Bingham number for Bn≲0.1, and pressure distributions are well captured by the approximation. The power-law index significantly influences resistance and pressure, with strong shear-thinning behavior increasing resistance variability by an order of magnitude and inducing channelization in the downstream fracture.

An adaptive autoregressive integration model for multi-variate time series analysis of extreme climate events

Correction to “Molecular Customization of Anode‐Electrolyte Interfaces for Enhanced Stability and Reversibility in Aqueous Zinc‐Carbon Capacitors”

High energy storage in tetragonal tungsten bronze ceramics engineered via superparaelectric state

Dielectric energy storage ceramics are critical components in advanced pulsed-power systems. Recently, ceramics with tetragonal tungsten bronze (TTB) structure have gained considerable interest owing to their freedom from volatile elements, which is a distinct advantage over many other widely studied energy storage ceramics. Nevertheless, achieving a simpler composition while maintaining a well-balanced enhancement in energy storage performance remains challenging. In this work, single La3+ ion was introduced into Sr0.6Ba0.4Nb2O6 ceramics, which induces a superparaelectric state at room temperature and effectively lowers the energy barrier for polarization switching. As a result, the obtained ceramic with a simple composition exhibits a high recoverable energy density of 3.48 J/cm3 and an ultrahigh efficiency of 95.4%, along with a notable figure of merit of 75.7. Moreover, the optimized composition demonstrates excellent frequency stability (1–200 Hz) and temperature stability (25–150 °C). This work proposes a feasible strategy for designing high-performance TTB energy storage ceramics, demonstrating the great potential of TTB ceramics in advanced energy storage applications.

Laser-generated X/InxOy/ZrO2 (X = Ni, Cu) composite catalysts: influence of support structure and in loading on catalytic activity

Orientation-engineered Bi0.5Sb1.5Te3 films with enhanced mobility for high-performance thermoelectric and photothermoelectric energy conversion

Bi2Te3-based thermoelectric films remain leading candidates for near-room-temperature power generation and cooling, yet further enhancement of their performance is required for practical applications. Here, highly oriented Bi0.5Sb1.5Te3 films were prepared by pulsed laser deposition, and carrier mobility was enhanced from 28.4 to 193.8 cm2 V−1 s−1 through orientation engineering. Consequently, a high room-temperature power factor of 56.7 μW cm−1 K−2 was achieved, positioning these films among the state-of-the-art (Bi,Sb)2Te3-based thin films. A corresponding Bi0.5Sb1.5Te3-based thermoelectric generator delivered a power density of 220.0 W m−2 at ΔT = 60 K, exceeding or comparable to those of previously reported thermoelectric film devices. In addition, a photothermoelectric device integrating antireflection and radiative cooling layers exhibited a peak output power of 75 nW under an irradiation intensity of 1.5 kW m−2. These results demonstrate the strong potential of orientation-engineered Bi0.5Sb1.5Te3 films for efficient thermoelectric and photothermoelectric energy conversion, highlighting their applicability in next-generation green energy technologies.

Chaotic Lévy flight Grey wolf optimizer for optimal design and techno-economic assessment of grid-connected solar photovoltaic power plant in Assam

Abstract The northeastern state of Assam possesses significant untapped solar energy potential requiring systematic optimization for effective utilization. This paper presents a novel Chaotic Lévy flight-enhanced Grey wolf optimizer (CLF-GWO) algorithm for multi-objective optimization of grid-connected solar photovoltaic power plants, validated using 36-month meteorological data from Guwahati, Assam. The proposed algorithm integrates logistic chaotic maps for population diversity, tent chaotic maps for adaptive parameter control, and Lévy flight mechanisms for improved escape from local optima. Comprehensive mathematical modeling incorporates temperature-dependent PV characteristics, non-linear inverter efficiency curves, and environmental derating factors specific to subtropical humid climate. The CLF-GWO demonstrates superior convergence, achieving optimal solutions 29.6% faster than standard GWO, 34.2% faster than PSO, and 27.8% faster than differential evolution across 50 independent runs. The optimized 1 MWp solar plant achieves annual energy yield of 1,542 MWh, performance ratio of 79.8%, capacity utilization factor of 17.6%, and levelized cost of energy of ₹ 3.89/kWh, representing improvements of 14.2%, 11.8%, 28.5%, and 23.7%, respectively, compared to the conventional design. Sensitivity analysis confirms system robustness across $$\pm 25\%$$ parameter variations. The proposed methodology establishes a replicable approach for optimal solar power plant design in Assam and similar subtropical regions globally.

Higher-order Weyl semimetals on nonorientable manifolds

Higher-order Weyl semimetals (HOWSMs), characterized by the coexistence of two-dimensional Fermi arc surface states and one-dimensional topological hinge states, establish the fundamental connection between Weyl physics and higher-order topology. However, previous studies have exclusively focused on HOWSMs within orientable manifolds. Here, we report the realization of HOWSMs on nonorientable manifolds through the introduction of Z2 gauge fields. The key feature is that the Fermi arc surface states and higher-order hinge states coexist within identical kz topological regions, which is fundamentally distinct from conventional HOWSMs. At last, we propose an experimental scheme based on acoustic resonator arrays, which may stimulate similar research works in other systems such as circuit, photonic, and cold-atom systems. Our work highlights the subtle yet crucial interplay between HOWSMs and their underlying manifolds.

Short-term trajectories of TyG-WHtR and hs-CRP and their joint impact on stroke risk in early CKM syndrome: evidence from Chinese national cohort

Performance improvement of NiO/β-Ga2O3 heterojunction diodes using ultrathin amorphous BN interfacial layer

In this work, a NiO/β-Ga2O3 heterojunction diode with an ultrathin (∼2 nm) amorphous boron nitride (a-BN) interfacial layer (IL) is presented. The NiO/a-BN/β-Ga2O3 heterojunction diode exhibited a lower turn-on voltage and a higher forward current, thereby reducing the power dissipation, compared to the NiO/β-Ga2O3 diode without an a-BN IL. It is also found that the a-BN IL reduces the interface states, leading to the improvement of the operational reliability after bias stress and reverse blocking characteristics.