Browse Articles

Chromatin- and actin-mediated mitochondrial streaming leads to patterning of mitochondrial distribution in oocytes

Atomic-scale reconstruction of oxide driven by oxygen transfer at AlN-capped GaN interfaces revealed through molecular dynamics simulations

This study reports the elucidation of atomic-scale reconstruction mechanisms at the AlN/GaN interface with native gallium oxide by means of molecular dynamics simulations based on a novel charge-transfer-type interatomic potential for the Ga–Al–O–N quaternary system. Optimized against over 21 000 configurations calculated via density functional theory, this potential accurately describes bond breaking and formation across crystalline and amorphous phases, enabling the analysis of transient interfacial processes that are difficult to resolve experimentally. The reliability of the potential was validated by simulating the initial oxidation of AlN surfaces; molecular dynamics simulations successfully reproduced the orientation-dependent kinetics, yielding ordered Al–O bilayers and O–Al–O trilayers on AlN(0001) that quantitatively match scanning transmission electron microscopy observations. Applying this framework to the AlN/GaOx/GaN interface, we investigated the structural evolution under thermal annealing. Oxygen atoms spontaneously migrate from the native gallium oxide layer to the AlN cap, driven by the thermodynamic stability of Al–O bonds rather than Ga–O bonds. This reaction effectively reduces the residual gallium oxide, transforming the interface into a chemically stable (Ga,Al)NxOy transition layer. These findings provide an atomic-scale depiction of interfacial reactions in AlN-capped GaN metal–oxide–semiconductor field effect transistors, offering mechanistic insights into processes that are not directly accessible by conventional experimental techniques. The insights may also provide guidance for understanding interfacial phenomena in other heterogeneous material systems.

Experimental and numerical investigation of the axial compressive behavior of GFRP-reinforced concrete walls under concentric and eccentric loading

Abstract This study investigates the axial compressive behavior of reinforced concrete (RC) walls reinforced with glass fiber–reinforced polymer (GFRP) bars under concentric and eccentric loading through a combined experimental and numerical approach. The six RC wall specimens with dimensions of 1000 × 800 × 150 mm were tested and divided into two groups. For Group G1 there were three specimens tested for concentric axial loading and for Group G2 three specimens were analyzed for eccentric axial loading. One control wall in each group was reinforced with conventional steel bars and the rest were reinforced with GFRP bars in vertical and horizontal directions. The experimental program studied first-cracking and ultimate loads, cracking behavior, stress–strain response, ductility ratios, energy absorption capacity, and lateral displacements. The results indicated that replacement of steel reinforcement with GFRP bars decreased ultimate axial capacity; however, GFRP-reinforced walls maintained stable post-cracking behavior and satisfactory ductility performance. When subjected to concentrically loaded specimens, the ultimate load capacity of GFRP-reinforced walls decreased by approximately 10.8–13.3% compared with the steel-reinforced control specimen, while the ductility ratio increased by about 4.4–4.8% points. Under eccentric loading, the ultimate capacity reduction ranged from 6.5% to 14.1% relative to the steel control wall. The energy absorption capacity, assessed from the load–displacement response, was lower for GFRP-reinforced walls compared to steel-reinforced specimens; however, a stable post-cracking response was maintained under both concentric and eccentric loading. In ABAQUS, nonlinear finite element models were generated through the Concrete Damaged Plasticity (CDP) model to emulate the structural response of the tested walls, to be complementary to the experimental study. The numerical results agreed well with the experimental results regarding ultimate capacity, load–deformation behavior, stiffness degradation, and crack distribution. The deviation between experimental and numerical ultimate loads ranged from approximately 0.25% to 11.9%, confirming the reliability and acceptable predictive accuracy of the adopted numerical modeling approach. Therefore, in general, in RC wall systems it is concluded that GFRP bars present a potential viable corrosion-resistant alternative to traditional steel reinforcement. The combined experimental and numerical results yield useful information about the axial behavior of GFRP-reinforced concrete walls under concentric and eccentric loading, that can be useful for making a better design decision in future for durable and sustainable structural wall applications.

Anticipating decoherence in quantum systems

Near-constant thermoelectric power factor of GaN two-dimensional hole gas in cryogenic environments

This work investigates the thermoelectric properties of a gallium nitride (GaN)-based two-dimensional hole gas (2DHG) using a double heterojunction, which can be utilized in complementary GaN thermoelectric (TE) platforms for power generation in extreme environments. A 5×1012 cm−2 hole density, a Hall mobility of up to 20 cm2 V−1 s−1, and a Seebeck coefficient of 0.4mVK−1 have been measured, resulting in a power factor of 0.5–1.0mWm−1 K−2 over a 300–77 K temperature range. These results demonstrate the stability and usability of the thermoelectric properties of GaN using hole conduction at sub-100 K temperatures, therefore providing clear evidence that GaN-based 2DHGs can function as a stable cryogenic TE platform, opening new opportunities for complementary device architectures (leveraging both 2DHGs for p-type and two-dimensional electron gases for n-type) optimized for extreme environment electronics commonly encountered in deep-space missions, where other materials become unreliable.

The potential role of transcranial direct current stimulation in experimental ischemic stroke in adult male albino rats

Abstract Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulatory technique with potential therapeutic applications in stroke, but the mechanisms underlying its neuroprotective effects in acute ischemia remain unclear. To evaluate the effects of cathodal versus anodal tDCS on neurobehavioral outcomes, histopathological changes, and inflammatory and glial responses in a rat model of focal cerebral ischemia. Adult male albino rats were randomized into normal non-ischemic, untreated stroke, sham, anodal, and cathodal tDCS groups. Neurological status and sensorimotor function were assessed 24 h after ischemia. Infarct volume (TTC), neuronal integrity (H&E and Nissl), and expressions of TNF-α, c-Fos, CD206, and GFAP were analyzed to characterize neuroinflammation, neuronal activity, and glial responses. Cathodal tDCS improved neurological scores and preserved sensorimotor function compared with anodal, sham, and untreated groups, the latter of which frequently exhibited acute coma. Histopathology in the cathodal group showed reduced necrosis, diminished inflammatory infiltration. In contrast, anodal stimulation produced only partial improvement, remaining significantly less effective than cathodal stimulation. Molecular profiling revealed that cathodal tDCS decreased TNF-α, enhanced astrocytic activation (GFAP) and neuronal activation (c-Fos), and promoted a trend toward M2 microglial polarization (CD206), whereas anodal tDCS exerted weaker effects. Cathodal tDCS conferred superior early neuroprotection and functional recovery after experimental ischemic stroke compared with anodal, sham, and untreated groups, likely through stronger modulation of inflammatory and glial pathways. While anodal stimulation showed limited benefit, cathodal stimulation demonstrated greater translational potential as an acute-phase intervention for ischemic stroke.

Gauge-field-induced duality group in metamaterials

Optimized spectral purity of unfiltered photons via pump and nonlinearity shaping

Photonic quantum technologies rely on the efficient generation and interference of indistinguishable photons. Exceptional achievements in this respect have been obtained by domain engineering of quasi-phase-matched parametric downconversion sources, demonstrating high two-photon interference visibility using only moderate bandpass spectral filtering. Here, we optimized the spectral purity and indistinguishability of photons from telecom-wavelength sources by combining Gaussian quasi-phase matching with Gaussian pump spectral shaping. Without spectral filtering, we used time-of-flight spectrometry to estimate an upper bound spectral purity of 99.9272(6)%, and achieved visibilities of up to 98.5(8)% in two-photon interference experiments with independent sources.

Effect of rumen-protected L-tryptophan on productivity and metabolic responses in dry Holstein cows under heat stress conditions

Author Correction: Viral entry shapes HCMV latency establishment

Gate leakage suppression in p-GaN/AlGaN p-channel transistors via transferred BN gate dielectric for high-temperature operation

In this Letter, we report gate leakage suppression in p-GaN/AlGaN p-channel transistors enabled by a transferred boron nitride (BN) gate dielectric for high-temperature operation. To elucidate the impact of BN integration, we systematically compare transfer characteristics, transconductance, and related metrics as functions of temperature (25–300 °C) for BN and conventional Schottky gate devices. Notably, current density in the BN device remains stable above ∼3 mA/mm at 300 °C, with an on/off ratio >103 and ID, max × LDS reaching ∼47 μA. At the same time, both the threshold voltage shift and the subthreshold slope show minimal variation, highlighting the excellent stability of this device. These results can provide insight into design strategies for high-temperature p-GaN p-channel transistors.

A human-centric fuzzy decision support system for medical diagnosis using fuzzy cognitive maps

Abstract Medical decision support requires models that remain interpretable under uncertainty while still adapting to evolving data and expert knowledge. Fuzzy cognitive maps (FCMs) are attractive in this setting because they encode concept-level relations in a transparent graphical form. However, static expert-defined FCMs are often too rigid, whereas purely data-driven updates may weaken semantic consistency and drift away from clinically meaningful relations. This paper proposes a human-centric adaptive framework for fuzzy cognitive map-based medical decision support. The proposed Human-Centric Fuzzy Decision Support System (HCFDSS) combines data-driven weight adjustment with an explicit expert-correction operator, allowing the causal structure of the map to be refined without discarding domain knowledge. The method is formulated through a two-stage procedure: an inner reasoning loop updates concept activations for fixed weights, while an outer learning loop updates the weight matrix using a regularized objective together with bounded expert intervention. Under standard smoothness and boundedness assumptions, we establish sufficient conditions for stability of the inner reasoning dynamics and convergence of the outer weight-update operator. A numerical illustration shows how expert feedback can revise clinically important edges and alter the final diagnostic activation in an interpretable way. In addition, the paper reports a reproducible empirical evaluation involving synthetic medical scenarios and three public medical benchmark datasets from the UCI Machine Learning Repository, together with sensitivity analysis for expert intervention, preprocessing validation, robustness checks under missingness and imbalance, and expanded comparisons with mainstream machine-learning baselines. The proposed HCFDSS is positioned not as a replacement for high-capacity black-box predictors, but as a transparent and editable decision-support framework in which clinicians can inspect, question, and refine the learned relations. The main contribution of the present work is therefore methodological and theoretical, while the empirical evaluation clarifies the predictive–interpretability trade-off of the proposed framework under reproducible benchmark settings.

Electrolyte additive screening for co-regulation of solvation and solid electrolyte interphase in aqueous zinc batteries

Biochar-driven multi-stage pyrolysis-roasting-relithiation strategy enables energy-saving and green regeneration of spent LiCoO2 batteries

The rapid expansion of the lithium-ion battery (LIB) industry has resulted in the exponential growth of spent LIBs, underscoring the urgent requirement for the efficient recycling and utilization of spent LIBs. Traditional recycling methods of spent LIBs suffer from high energy and chemical reagent consumption, high pollutant emission, and limited economic viability. Herein, this work proposes a novel biochar-driven multi-stage pyrolysis–roasting–relithiation strategy to achieve energy-saving and green regeneration of spent LiCoO2 (LCO) cathodes. The results show that the introduction of pine sawdust char (PSC) into spent LCO greatly promotes the complete decomposition and reduction of spent LiCoO2 under relatively mild conditions. The subsequent roasting process is able to easily remove the impurities (such as residual PSC) in the pyrolysis products, achieving rather satisfactory recovery rates of Li (95.8%) and Co (99.5%) at optimal conditions during the whole multi-stage process. The sufficient removal of the impurities is beneficial for the final relithiation process, obtaining high-quality regenerated LCO with a well-ordered layered structure, uniform morphology, and freedom from agglomeration, which contributes to its electrochemical performance (170.79 mA h g−1 at 0.1 C) comparable to commercial LCO. Moreover, life cycle and techno-economic assessments indicate that the proposed strategy is an energy-efficient (10.75 MJ kg−1 regenerated LCO) and economical (9.78 $kg−1 regenerated LCO) regeneration route with minimal impact on the environment. This work paves the way for the economical and sustainable recovery technologies of spent LIBs.

A blockchain-secured 6G smartgrid framework for resilient renewable energy integration and intelligent anomaly detection

Challenges and opportunities of the full phase-out of fossil fuels under the 1.5 °C goal

Abstract The COP28 decision called for transitioning away from fossil fuels, sparking a growing interest in their full phase-out. However, energy system transformation pathways towards a phase-out of fossil fuels, which may reduce the reliance on carbon dioxide removal to meet the 1.5 °C goal, remain unclear. Here, we employ two global energy system models to explore energy system transformations and the challenges and opportunities associated with attaining a full phase-out of fossil fuels. We found that phasing out fossil fuels by 2050 would require accelerating direct and indirect electrification, involving 1.6–1.8-fold increases in power generation compared to the conventional cost-effective 1.5 °C pathways. This transition from cost-effective to fossil fuel phase-out pathways would increase energy supply investments by up to 34% over this century and require accelerated deployment of solar and wind power, as well as electrolysers. Despite opportunities including lower reliance on carbon dioxide removal and increasing probability of returning to 1.5 °C after temperature overshoot, these additional requirements imply that international society must approach the transition towards zero-fossil energy systems with strong determination.

Lateral carrier crosstalk suppression in pure-boron ultraviolet detector arrays using a novel deep trench isolation process

Pure-boron (Pure-B) ultraviolet photodiodes form an ultra-shallow P+ junction at the silicon surface, enabling a nearly ideal entrance window with high quantum efficiency and low dark current for UV/EUV and electron detectors. However, in high-density arrays, lateral carrier transport within lightly doped epitaxial layers induces pronounced pixel-to-pixel crosstalk, which degrades spatial resolution. In this work, a novel deep trench isolation (DTI) scheme compatible with a dual-epitaxial Pure-B planar structure is proposed and experimentally demonstrated to suppress crosstalk in ultraviolet detector arrays. Technology computer aided design simulations reveal that DTI structures leave a residual lateral bypass path beneath the trench bottom, leading to a strong dependence of crosstalk on epitaxial thickness, whereas a 10-μm-deep DTI effectively eliminates this path and reduces simulated crosstalk to the lower level, largely independent of epitaxial thickness. Devices fabricated with the optimized DTI process exhibit low crosstalk of 0.27% under 0–2 V reverse bias, a detector signal of 0.24 A/W at 13.5 nm, dark current below 0.15 nA, and a rise time of approximately 60 ns. The proposed approach provides a scalable isolation strategy for high-pixel-count ultraviolet detector arrays with minimal electrical-performance degradation.

Robust feature selection for cancer microarray data using a hybrid mRMR and Binary Lion Optimization Algorithm

Disorder-mediated non-equilibrium photocurrent redistribution enables homeostatic synaptic conditioning in AgBiS2 heterostructure

Hofstadter butterfly and quantum transport benchmarks in PVA-exfoliated graphene heterostructures

Polymer exposure during van der Waals heterostructure fabrication is widely regarded as compromising the integrity of the electronic system required for hosting emergent quantum physics. This assumption has persisted largely because electronic benchmarking of heterostructures from polymer-exposed graphene has remained limited to only foundational transport metrics, such as mobility and charge inhomogeneity. Here, we challenge this assumption by establishing that graphene heterostructures produced by polyvinyl alcohol (PVA)-assisted exfoliation and encapsulated in hexagonal boron nitride using elevated-temperature lamination satisfy demanding quantum transport benchmarks. Beyond exhibiting ultra-high mobility and ballistic transport, these heterostructures yield quantum scattering times comparable to the best polymer-free devices. Most demanding of all, moiré superlattices from PVA-exposed graphene exhibit Hofstadter butterfly spectra, confirming spatially uniform interlayer coupling across the device area. These results establish that PVA exposure is compatible with low-disorder electronic systems, relaxing the trade-off between scalable fabrication and low-disorder quantum transport. This study motivates further development of polymer-assisted assembly with engineered residue-removal protocols.