Search Results (19,939)

The article presents the synthesis and characterization of double halide perovskites (DHPs) with the nominal composition Cs₂Ag_0.2Na_0.4In_0.6M_0.4Cl₆ (M = Si, Ti, Zr), including photoluminescence (PL), photoluminescence excitation (PLE) spectra measured over a range of temperatures and kinetics of luminescence. The materials were synthesized via a hydrothermal method. The phase purity and elemental composition of the synthesized perovskites were confirmed by X-ray diffraction (XRD), Rietveld refinement, scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS) and elemental analysis, which demonstrated that the samples showed a close match to the target stoichiometry. The PL spectra exhibit a systematic shift toward the lower-energy region with substitution from Si to Zr, correlating with the progressive increase in the ionic radii of the substituting cations. All samples display broad, asymmetric emission bands, characteristic of self-trapped excitonic (STE) states. Temperature-dependent PL measurements reveal a gradual decrease in emission intensity with increasing temperature for all samples. The maximum emission intensity is observed in the range of ~160–200 K, corresponding to optimal conditions for radiative recombination, whereas the lowest intensity is recorded at ~80–100 K, where thermal activation of radiative centers is minimal. An increase in temperature is accompanied by a red shift in the PL bands across all compositions. In the Ti-doped DHP, a pronounced blue shift at low temperatures is observed, which can be attributed to the involvement of Ti³⁺-related electronic states. An analysis of the activation energy of thermal luminescence quenching and the results of time-resolved spectroscopy revealed the activation of thermal processes in the titanium-containing sample and their rapid decay, whereas replacing titanium with silicon leads to more stable luminescence in the crystal under study. Thus, the enhanced luminescence characteristics of double halide perovskites doped with Ti, Si, and Zr highlight their potential for advanced photonic and optoelectronic applications. Full article

Background: Smart-city road and intersection management increasingly aims to smooth bus operations and reduce stop-and-go driving, but cities often lack auditable indicators linking routine fleet data with comparable energy and environmental KPIs. Methods: This study develops a Monitoring–Reporting–Verification (MRV) workflow for daily bus records from a 2024 Polish metropolitan fleet (diesel, compressed natural gas (CNG), hybrid, and battery-electric buses). Records were quality checked, harmonized to MJ/km, aggregated to bus-month observations, and analyzed using a linear mixed-effects model with propulsion technology, season, and activity level as fixed effects and vehicle-level random intercepts. Environmental impacts were then calculated under well-to-wheel (WTW) boundaries using Environmental Footprint 3.1 (EF 3.1) impact categories, Poland’s 2024 electricity mix, and illustrative electricity-mix scenarios through 2050. Results: Relative to diesel, BEV and HEV were associated with lower adjusted energy intensity (ratios 0.272 and 0.681, respectively), whereas the CNG–diesel contrast was directionally higher but statistically inconclusive under the available CNG sample. BEV energy intensity more than doubled in winter in descriptive terms, and vehicle-specific heterogeneity remained high (ICC ≈ 0.61). The BEV climate profile improved under electricity decarbonization, while some EF categories showed mix-dependent trade-offs. The 3–10% traffic-management variants are interpreted as screening assumptions rather than measured ITS effects. Conclusions: Routine bus records can support auditable MRV and preliminary screening of fleet and corridor interventions, but causal traffic-management evaluation requires route-level trajectory, congestion, and before–after data. Full article

The emergence of citizen energy communities under the European Clean Energy Package is creating new opportunities for neighboring households to collectively reduce electricity costs through local energy sharing. This paper presents a distributed multi-agent energy management system for a two-household residential energy community in which each household is equipped with photovoltaic generation and a battery energy storage system operating under realistic hourly-varying electricity prices. Each household is managed by an independent Deep Q-Learning agent that learns a cost-optimal charging and discharging policy using only local observations. In parallel, a coordination agent, implemented on the SPADE platform with XMPP-based messaging, oversees real-time peer-to-peer energy transfers between households, enabling energy exchange whenever one household has surplus generation and another faces a deficit. The two households are deliberately configured with complementary profiles: one has higher PV generation capacity while the other has higher energy consumption. This setup creates natural opportunities for local energy sharing between them. Performance is assessed through a three-level evaluation framework: (i) individual household economics (cost reduction, battery management, grid exchanges), (ii) coordination efficiency (transfer frequency, direction, and volume), and (iii) aggregate community performance, which isolates the added value of peer-to-peer sharing beyond what each household achieves through individual BESS optimization. Numerical experiments using GEFCom2014 solar generation data, synthetic residential load profiles calibrated following documented consumption patterns, and day-ahead price signals representative of the Spanish electricity market demonstrate that both Deep Q-Learning agents independently learn effective charge/discharge strategies aligned with price signals and PV availability. They also show that the coordination layer further reduces community grid dependence by routing surplus energy locally rather than exchanging it with the main grid at less favorable rates. The results confirm that a well-engineered integration of decentralized reinforcement learning with a lightweight coordination protocol can deliver measurable economic benefits in realistic residential energy communities without requiring centralized training, shared data, or complex multi-agent reinforcement learning architectures. Full article

Electron emission from hydrogen atoms induced by antiproton impact at intermediate energies is investigated using the one-centre Basis Generator Method within a semi-classical impact-parameter framework. The formulation employs a single-centre expansion of the time-dependent Schrödinger equation with a pseudostate basis consisting of hydrogenic orbitals acted upon by powers of a Yukawa-regularized potential, providing a compact and effective representation of the electronic continuum. Ionization probabilities are obtained by projecting the time-evolved wavefunction onto Coulomb continuum states, from which energy-differential cross sections (EDCS) are extracted. Exponential piecewise functions are constructed to interpolate between the pseudostate eigenenergies, yielding smooth EDCS profiles for each partial wave. The total EDCS, reconstructed by summing over all partial-wave contributions, exhibits good agreement with results from other pseudostate-based approaches. Full article

This paper presents a comprehensive investigation of the effects of atmospheric plasma treatment (APT) on the surface morphology, microhardness, chemical composition, and tribological performance of alloy steel used in railway applications. A novel mathematical model is proposed to describe the dependence of the maximum surface asperity height on the APT parameters and material properties. Experimental validation was performed using a series of alloy steel specimens treated under controlled APT conditions. The surfaces were characterized by roughness measurements, microhardness testing, scanning electron microscopy, and energy-dispersive spectroscopy. Tribological properties were evaluated under dry sliding conditions using ball-on-disk tests with steel counterbodies (grades 1.3529 and 1.3505). Tribological testing showed that APT leads to a 6–7% reduction in the steady-state friction coefficient, eliminates the long running-in stage, and improves stability by lowering the coefficient of variation by up to 43%. Overall, this study demonstrates that APT provides a dual benefit: improving tribological performance through surface smoothing and stabilization of the friction regime, and preserving the mechanical and chemical integrity of the material. Full article

The rapid expansion of artificial intelligence and cloud computing is straining terrestrial data center infrastructure, motivating exploration of space-based data centers (SBDCs) as a scalable and energy-efficient alternative. While orbital platforms offer unique advantages, including continuous solar energy, radiative cooling, and global coverage, their practical deployment is constrained by unresolved reliability challenges across the mission lifecycle. This study presents a lifecycle-oriented reliability and risk assessment for SBDCs spanning launch, orbital operation, maintenance, and end-of-life phases, using a structured systems-level analysis of failure modes and operational dependencies. This paper focuses on compute-centric SBDC architectures, treating storage solely as a supporting resource. We identify and classify space-environment-specific risks, including launch-induced mechanical stress, radiation-driven degradation, thermal extremes, and single points of failure in power and communication subsystems. By integrating engineering constraints with economic considerations, we develop a unified risk-chain framework that shows how reliability limitations propagate from component design to system cost and operational viability. The analysis reveals a critical trade-off: achieving terrestrial-grade reliability in orbit requires substantial redundancy and radiation hardening, increasing mass and cost and reducing economic feasibility, whereas lower-reliability designs introduce operational and financial risks that challenge sustainability. These findings establish reliability as the central determinant of SBDC viability, providing an applied foundation for fault-tolerant, modular, and lifecycle-aware design strategies essential for transitioning orbital cloud infrastructure from concept to scalable reality. Full article

Amid the ongoing acceleration of climate change over recent decades, extreme precipitation events have become more frequent and intense on a global scale, triggering severe natural hazards and considerable socioeconomic damage. Nevertheless, how extreme precipitation has evolved at the national level over long time spans, and what role atmosphere–ocean teleconnections play in driving regional differences, remains insufficiently explored. This study addresses that knowledge gap by conducting a comprehensive assessment of eight ETCCDI-based extreme precipitation indices (PRCPTOT, CWD, R20, R95p, R99p, RX1day, RX5day, and SDII) across six climatic sub-regions of China (Northeast, North, East, Central South, Northwest, and Southwest) over 1960–2020, drawing on daily records from 695 quality-controlled meteorological stations. Key atmospheric and oceanic circulation drivers were further diagnosed and their joint influence was quantified via multiple wavelet coherence (MWC). The analysis shows that five of the eight indices (CWD, R95p, R99p, RX1day, and RX5day) underwent statistically significant fluctuating changes (p < 0.05) throughout the 61-year record. Seven indices, all except CWD, demonstrated upward tendencies, with mutation points clustering after 2010, most notably between 2011 and 2016. Wavelet power spectra indicates elevated energy concentrations at multiple time scales, although only CWD exhibited a statistically significant periodicity of approximately 8–10 a (p < 0.05 against red noise). In terms of spatial patterns, index magnitudes generally increased along a northwest-to-southeast gradient. Stations registering significant upward shifts were concentrated in East and Central South China, whereas significant downward shifts appeared mainly in North China and the northern portion of East China. An altitude-dependent pattern was also detected: CWD rose with elevation, while the remaining indices declined sharply below 1288 m, fluctuated in the 1288–2090 m band, and dropped again above 2090 m. Wavelet coherence analysis uncovered significant resonance between extreme precipitation and four circulation indices—SCSMMI, WPSHI, PNA, and NAO. MWC further identified three driver combinations—ENSO-PNA, SCSMMI-WPSHI, and ENSO-NAO-EASMI—as the most influential, acting both individually and synergistically. These results furnish an empirical basis for forecasting, preventing, and managing precipitation-related disasters across China under future climate scenarios. Full article

Reducing carbon emissions while improving air quality is a central challenge for rapidly urbanizing regions. Focusing on 31 prefecture-level cities in the Middle Reaches of the Yangtze River Urban Agglomeration, this study examines carbon–pollution synergy (CPS), spatial dynamics, and the driving factors of CO₂ and representative air pollutants from 2013 to 2023. Spatial autocorrelation analysis, a revised four-factor Logarithmic Mean Divisia Index (LMDI) decomposition, and a factor-based CPS assessment were used to identify spatial clustering, compare driver heterogeneity, and evaluate coordination between CO₂ and primary pollutants. To improve methodological consistency, the LMDI decomposition and CPS assessment focus on the primary pollutants SO₂, CO, and NO₂, whereas PM_2.5 and O₃ are retained in the spatial analysis and discussion because they are strongly affected by secondary formation, atmospheric transport, and meteorological conditions. The results show that CO₂ and the selected pollutants exhibit significant but pollutant-specific spatial clustering. High CO₂ values remain concentrated in the core cities of Wuhan, Changsha, and Nanchang, PM_2.5 shows a persistent north–south gradient, and SO₂ hotspots shift from traditional industrial cores toward peripheral areas receiving industrial relocation. The revised LMDI results show that economic development is the most stable positive driver of CO₂ and the primary pollutants, whereas the energy-consumption factor generally suppresses emissions. The recalculated population-scale factor fluctuates around 1, indicating a comparatively limited and stage-dependent contribution once the other factors are controlled for. CPS analysis further indicates that coordinated reduction is most robust under the energy-consumption factor and, for conventional combustion-related pollutants, also under the energy-structure factor. Overall, the region has a clear basis for CPS governance, but effective implementation requires pollutant-specific and region-specific control strategies rather than a uniform co-mitigation pathway. Full article

Hydrogen is widely considered a promising clean energy carrier because of its high energy density and environmental benignity, yet the development of safe and reversible hydrogen storage materials remains a major challenge. Two-dimensional materials are particularly attractive for this purpose owing to their large specific surface area, fully exposed active sites, and highly tunable electronic structures. Here, using crystal structure prediction combined with first-principles calculations, we predict a stable metallic Li₃B₂N₂ monolayer as a potential hydrogen storage material. This monolayer can adsorb up to six H₂ molecules per unit cell with an average adsorption energy of ∼0.23 eV/H₂, yielding a high hydrogen storage capacity of ∼7.8 wt.%. Further analysis reveals that hydrogen adsorption is governed by the synergistic effects of electrostatic polarization and orbital hybridization. Moreover, calculations on the temperature- and pressure-dependent hydrogen storage behavior show that all hydrogen-adsorbed structures remain stable at room temperature under a pressure of 3.7 MPa. The van’t Hoff analysis indicates that the maximum desorption temperature at atmospheric pressure is 316 K, suggesting favorable reversibility under near-ambient conditions. These results establish Li₃B₂N₂ as a promising intrinsic two-dimensional material for high-density and reversible hydrogen storage. Full article

Impairment in blood supply to the brain deprives its cells of the much-needed nutrients and molecules such as oxygen and glucose necessary for its development, growth and survival. This will set up a host of pathological processes such as impaired homeostasis, energy failure, excitotoxicity, oxidative stress, impaired protein synthesis, inflammation, cytokine-mediated toxicity and impairment of blood–brain barrier. These pathological processes will result in the damage or death of the cells depending on the extent of the deprivation. Similarly, they will impair synthesis of acetylcholine (Ach) and norepinephrine (NE), which are important neurotransmitters in the cholinergic and adrenergic systems responsible for cellular communication and functions. Thus, interventions to help arrest and/or modulate the initial and subsequent pathological states and help recover the functions of the brain are needed. One of such interventions is vagus nerve stimulation, which helps activate the cholinergic and the adrenergic systems via projections of the afferent fibers of the vagus nerve to the nucleus of the solitary tract (NTS). Activation of the cholinergic and the adrenergic systems results in reduction in pro-inflammatory factors such as tumor necrosis α, increase in pro-angiogenic factors and increase in firing of adrenergic neurons in the central nervous system (CNS). Full article

Punching shear failure in reinforced concrete RC slabs is one of the most significant and detrimental failure modes due to its sudden nature and its dependence on a complex interaction between concrete strength, the reinforcement, and the loading conditions. In recent years, there has been increasing interest in utilizing sustainable cementitious materials and steel fibers as a way of enhancing structural performance and improving the durability of concrete. The study aims to assess the structural behavior of RC slabs utilizing a partial cement substitution with limestone powder (LP) and granulated blast-furnace slag (GBFS), with the addition of steel fibers. Twelve RC slabs were examined under uniform concentric loading to analyze cracking behavior, load–deflection relationship, stiffness variation, and ultimate punching shear strength. The results demonstrated that using limestone powder (LP) had a significant impact on the crack distribution pattern and resulted in a slight reduction in initial stiffness, with the load-bearing capacity decreasing to approximately 55.8% of the control mixture at high replacement ratios. Due to a slower hydraulic reaction than with other mixtures, increasing additional granulated blast-furnace slag resulted in a decrease in crack resistance and relative deformation. With a load-bearing capacity of approximately 92.9% of the control mixture, a tertiary mixture of limestone powder and granulated blast-furnace slag (GBFS) demonstrated a better balance in structural behavior, leading to improved crack control while maintaining a sufficient level of load-bearing capacity. The steel fibers also significantly contributed to enhanced post-cracking behavior by decreasing crack width and improving the stress redistribution mechanism within the RC slab. This led to increased punching shear resistance and enhanced energy absorption, with the ultimate load increased to 119 kN compared to the control mixture. Overall, the findings show that combining sustainable cementitious materials with steel fibers can effectively improve punching shear performance and enhance the efficiency and durability of reinforced concrete. Full article

Accurate estimation of the state of health (SOH) and prediction of the remaining useful life (RUL) of lithium-ion batteries (LIBs) are critical for ensuring system reliability and safety across diverse energy storage applications. This paper proposes a hybrid deep learning framework that integrates an axial-embedding Transformer (AxEmbTrans) encoder and a bidirectional LSTM (BiLSTM) module for the joint estimation of SOH and RUL. The AxEmbTrans encoder employs axial attention with abstract embeddings to capture global dependencies among multidimensional health features at reduced computational complexity compared to standard self-attention, while the BiLSTM models local temporal dynamics and short-term degradation fluctuations across consecutive cycles, with its bidirectional structure enhancing robustness against transient noise. Informative health features are extracted from charge–discharge curves, grouped into temporal, energy, and thermal categories, and fused using local linear embedding (LLE) for nonlinear dimensionality reduction. An improved Newton–Raphson-based optimizer (INRBO) is introduced to automatically tune the framework’s key hyperparameters, including the hidden dimension, number of attention heads, number of BiLSTM units, and learning rate, incorporating directional similarity modulation and multi-elite guidance to overcome the convergence instability of the standard NRBO. Extensive experiments on NASA and Maryland datasets demonstrate that the proposed method consistently outperforms baselines in both SOH and RUL prediction, achieving higher accuracy, improved robustness, and better cross-condition generalization. Full article

AC microgrids with high penetration of inverter-based distributed energy resources (IBDERs) introduce major protection challenges due to reduced fault current levels, bidirectional power flows, and control-dependent fault behavior. Under these conditions, short-circuit current calculation and relay protection coordination become tightly coupled, since inaccurate fault modeling directly degrades relay sensitivity and selectivity. This review presents a protection-oriented assessment of state-of-the-art short-circuit calculation and relay protection strategies for AC microgrids. The analysis shows that conventional IEC-based fault models and static overcurrent protection schemes are insufficient for inverter-dominated networks. Generalized Δ-circuit–based modeling framework is identified as the most suitable foundation for microgrid fault analysis, as they enable inverter-aware phasor-domain representation and support both grid-connected and islanded operation. In addition, adaptive relay coordination approaches that incorporate time-varying IBDER participation and fault ride-through behavior demonstrate improved coordination robustness compared to conventional fixed settings, although their practical deployment remains constrained by network topology and communication requirements. Simulation results obtained on a representative microgrid case study confirm that the combined application of protection-oriented short-circuit modeling and adaptive relay coordination significantly improves fault detection reliability and coordination performance. The findings highlight the necessity of jointly addressing fault modeling and protection design to ensure reliable operation of inverter-dominated AC microgrids. Full article

Background/Objectives: Healthy longevity depends on not only lifespan but also the maintenance of physiological, metabolic, physical, and cognitive functions throughout aging. Identifying early determinants of health is crucial for preventing age-related decline. This narrative review aims to synthesize current evidence on how diet and specific nutrients relate to these early risk factors and indicators of healthy longevity. Methods: A review was performed to identify the links between dietary factors, energy balance, and gut microbiota composition and normal body weight; blood cholesterol, pressure, and glucose; healthy sleep; an active lifestyle; and normal physical function and cognitive performance. Particular attention was given to Mediterranean and other plant-based dietary models as sources of key nutrients. Evidence from observational studies, randomized controlled trials, and meta-analyses was considered. Results: Across all markers, dietary quality and nutrient adequacy emerged as consistent determinants of health outcomes. Key nutrients were associated with favorable cardiometabolic, cognitive, and musculoskeletal functions, such as omega-3 fatty acids, fiber, vitamins D and B, minerals like magnesium and potassium, and polyphenols. Common nutrition gaps included insufficient intake of fiber, unsaturated fats, and micronutrients, which was often linked to a shift toward less plant-based diets. Gut microbiota diversity may mediate several of these associations, influencing metabolism, inflammation, sleep quality, and cognitive performance, although inter-individual variability and causal pathways remain incompletely understood. Conclusions: An integrated dietary approach emphasizing the consumption of whole and plant-rich foods, with moderate amounts of animal foods, supports multiple early markers, risk factors, and indicators of healthy longevity. The modulation of the gut microbiota through plant-based diets and fermented foods represents a promising strategy for maintaining health across aging trajectories. Full article

As primary sites for oxygen consumption and energy production via oxidative phosphorylation (OXPHOS), mitochondria play a central role in the regulation of bioenergetics and generation of key metabolic intermediates for myogenic cell growth. Common methods to study mitochondria and their metabolism typically rely on population-level analyses, which can mask potential differences in individual cells. In this study, we used various imaging approaches to investigate the interplay between intracellular oxygenation, mitochondrial metabolism and dynamics in a model of myogenic differentiation. Fluorescence imaging of intracellular oxygen revealed that myogenic differentiation is accompanied by progressive shifts in intracellular oxygenation that depend upon and reflect changes in mitochondrial metabolism (i.e., higher oxygen consumption and adenosine triphosphate (ATP) production). By measuring intracellular oxygenation, we showed that mitochondrial metabolism reduces oxygen availability in the cytosol and the nucleus. Real-time redox imaging at the single-cell level further highlighted substantial metabolic heterogeneity and a shift toward OXPHOS as differentiation progressed. Morphological analyses revealed that during myogenic differentiation, mitochondria increase in size while becoming less mobile and overlapping less with microtubules. Overall, this study illustrates the value of combining complementary imaging approaches to provide a comprehensive single-cell perspective on mitochondrial metabolism, remodeling and spatial organization during myogenesis. Full article