Search Results (8,999)

The comprehension of the complex dynamics of degassing is critical for volcano monitoring and assessing volcanic hazards. In this study, we apply visibility graph analysis (VGA) to a decadal, high-resolution time series of daily soil CO${}_2$ flux recorded by a standardized monitoring network at Mt. Etna volcano (Italy). By mapping these time series into complex networks, we demonstrate that the connectivity degree distributions follow a power law described by the exponent $\gamma$, which reveals a self-similar behavior of gas emissions. We introduce the $\gamma$-deviation, namely the variation of the scaling exponent from its long-term site-specific baseline, as a novel proxy for degassing efficiency. The long-term baseline is interpreted as a site-specific measure of flux efficiency, while its variations are attributed to other factors, such as fluctuations in the sources or changes in the efficiency of fluids transport pathways. Our results identify a transition from a period of discordance across the monitoring sites (pre-2016) to a phase of network-wide concordance (after 2016). The striking correlation between topological $\gamma$-deviations and the established normalized network signal (${\Phi }_{norm}$) validates the methodology, suggesting that VGA is able to capture the same underlying magmatic drivers. This study establishes VGA as a robust and reliable tool for medium- and long-term monitoring, potentially capable of identifying the occurrence of large-scale magmatic processes and refining the characterization of fluid transport dynamics in active volcanic systems. Full article

Despite a growing interest in biochar for olive orchard fertility management, little is known about its effects on nitrogen (N) dynamics and greenhouse gas (GHG) emissions in Mediterranean soils, particularly when comparing neutral (pH 6.7) and alkaline (pH 8.2) soils using farmer-accessible flame-curtain pyrolysis biochar. In this 60-day soil mesocosm study, we hypothesized that biochar amendments in fertilized soils would enhance soil N availability and potentially reduce N₂O emissions, with effects modulated by soil pH. Treatments included: control, urea fertilizer, and urea plus biochar (5% w/w). Urea fertilization significantly increased soil ammonium (NH₄⁺) and total oxidized nitrogen (NO₃⁻ + NO₂⁻) in both soils, and co-application of biochar further increased these pools, particularly in the neutral soil (NH₄⁺: + 91% and + 62% in neutral and alkaline soil, respectively). Biochar addition consistently reduced cumulative carbon dioxide (CO₂) emissions in both soils, supporting its role in stabilizing soil organic carbon. However, impacts on nitrous oxide (N₂O) emissions were soil-pH-dependent: biochar slightly reduced N₂O emissions in neutral soil, though nearly doubled N₂O emissions in alkaline soil, highlighting that biochar’s efficacy for GHG mitigation is context-specific. These findings underscore biochar’s potential to improve soil N availability and reduce carbon losses but reveal clear limitations for N₂O mitigation in alkaline soils, necessitating site-specific application strategies that explicitly consider soil pH when targeting climate benefits in Mediterranean olive production. Full article

Heterogeneous multi-core systems (HMCSs) typically face a dilemma: heuristics (e.g., Linux CFS) are fast but blind to global constraints, while meta-heuristics (e.g., GAs) are globally optimal but too slow for real-time OS interaction. To bridge this gap without relying on “black-box” neural networks, we introduce the Tissue P System-Inspired Task Allocator (TPSTA). By mapping HMCS and parallel task scheduling to Tissue P System models and vectorized linear algebra problems, TPSTA achieves a computational complexity of $\mathrm{O}\left(\mathrm{M}/\mathrm{W}\right)$, effectively compressing the decision space. Our rigorous evaluation across four dimensions reveals a system strictly bound by physical constraints rather than algorithmic heuristics. (1) Under sufficient resource provisioning (four chips), TPSTA achieves a 0.00% Deadline Miss Ratio (DMR). Crucially, stress tests on constrained hardware (two chips) show graceful degradation to a 12.88% DMR, matching the optimal theoretical bound of EDF, whereas standard heuristics collapse to failure rates > 68%. On a massive 4096-core cluster, TPSTA outperforms the Linux GTS scalar baseline by 14.4×, maintaining low latency where traditional algorithms fail (>8 s). (3) Adaptability: The system demonstrates adaptive routing in handling hardware heterogeneity; without explicit rule-coding, it autonomously prioritizes data locality during NUMA transfers and migrates compute-bound tasks during thermal throttling events. (4) Physical Limits: Finally, our roofline analysis confirms that while the algorithmic speedup is theoretically linear, practical performance saturates at ~375× due to the Memory Wall, validating the isomorphism between synaptic bandwidth and hardware memory channels. Full article

Hydrogen plasma heating, a unique method for heating and reducing iron ore, is distinguished by its high heat, rapid reduction, and high efficiency, making it a promising technique in the metallurgy field. In this study, a non-transferred arc plasma heating system was used with Ar-H₂ as the working gas and acidic pellets as the raw material. The microstructures and elemental distributions of the slag and iron phases during the reduction process were examined using electron microscopy and energy-dispersive X-ray. The variation patterns of Fe-containing phases in the reduction products were found using X-ray diffraction and full-spectrum fitting refinement. The conversion rate of the oxidized pellets and the deoxidation conversion rate per area were estimated for various gas flow rates and reduction times. A reaction kinetics model was also used to study the reaction controlling step. The results showed that during the reduction process, with an H₂ flow rate of 4.5 L min⁻¹ and a 40 min reduction, the conversion(α) reached 99.89% and the purity of the reduced metallic iron reached 99.9%, achieving the industrial-grade 3N standard. Si and Al in the melt bath generated fayalite (Fe₂SiO₄) and hercynite (FeAl₂O₄) with Fe_xO. The deoxidation conversion rate per unit area was 1.11 g (cm² min)⁻¹. A three-dimensional diffusion-controlled model was used to describe the reduction process, and the mechanism function was 2/3(1 + α)^3/2[(1 + α)^1/3]⁻¹. The values of the reduction reaction rate constant (K) were 12.6 × 10⁻² s⁻¹ and 12.8 × 10⁻² s⁻¹ when the flow rates of H₂ gas were 3 and 4.5 L min⁻¹, respectively. The apparent activation energy was 21.9 kJ mol⁻¹. The empirical equation for the specific reduction rate was calculated as ln r = −2637.5/T − 0.407. Full article

High-temperature particulate matter (PM) filtration remains a fundamental challenge, because most fiber filters not only face the challenge of high temperatures but also suffer from an inherent trade-off between capture efficiency, pressure drop, and service life. This paper reports a hierarchical layered zirconia (ZrO₂) ceramic fiber aerogel featuring a continuous multiscale gradient. The aerogel was prepared by gradient air-blown spinning, and the resulting structure has directional order, with the fiber diameter gradually decreasing from upstream to downstream, thus forming a pore size gradient and achieving hierarchical particle interception across multiple scales. This rational design simultaneously suppresses surface clogging and reduces flow resistance, resolving the longstanding trade-off between efficiency and permeability. Consequently, this aerogel achieves an ultra-high filtration efficiency of 99.96%, a low pressure drop of 156 Pa, and a high dust-holding capacity of 101 g m⁻². The material also exhibits outstanding mechanical toughness (80% compressive strain elasticity and 25.75% tensile fracture strain) and thermal stability up to 1000 °C. Moreover, it maintains over 99.95% filtration efficiency at high temperatures and can be fully regenerated through 800 °C heat treatment. This work establishes a structure-based design paradigm for high-temperature filtration media and provides a scalable pathway for next-generation industrial flue gas purification. Full article

Accurate endpoint control in basic oxygen furnace (BOF) steelmaking is essential for reducing production costs and improving steel quality. To overcome the limited mechanism support and poor transparency of purely data-driven models, this study proposes a physics-aware and interpretable framework for cumulative decarburization prediction based on real industrial data. Historical multi-heat data from the same converter were integrated, and an averaged full-spectrum cross-correlation method was used to estimate and correct the transport delay of off-gas signals, thereby constructing a heat-wise large-sample dataset. Key elemental features with clear physical significance were then extracted from high-dimensional flame spectra by incorporating their underlying radiation mechanisms. On this basis, a Stacking-based ensemble model was developed for cumulative decarburization prediction, and SHAP was introduced to interpret the model decision logic. Results show that the proposed framework outperforms conventional single models and purely data-driven dimensionality reduction methods. SHAP analysis further indicates that model decisions are mainly dominated by four core elemental spectral features, namely Fe, C, O, and Mn. Overall, the proposed method combines predictive performance, physical constraints, and interpretability, and provides a new solution for auxiliary soft sensing and decision support in BOF endpoint control. Full article

In this study, a three-dimensional simulation of a walking-beam reheating furnace was developed to improve the steel slab reheating process and reduce surface oxidation kinetics using computational fluid dynamics (CFD). Combustion, heat transfer, fluid dynamics, and chemical reaction models were integrated into the numerical framework of this study. In addition, dynamic mesh remeshing was coupled through user-defined functions (UDFs), enabling the simultaneous simulation of slab movement and evolution of the involved transport phenomena. Turbulence was modeled with the realizable k-ε formulation, combustion with the Eddy Dissipation model, and radiation with the P-1 model coupled with WSGGM to include CO₂ and H₂O gas radiation. Scale formation was modeled using customized functions based on Arrhenius-type kinetics and Wagner’s oxidation model, evaluating its growth as a function of time, temperature, and furnace atmosphere. The predicted thermal evolution inside the furnace was validated using industrial data, yielding an average deviation of 5%. Furthermore, the proposed operating conditions led to an average slab temperature of 1289.77 °C at the exit of the homogenization zone, which was 16 °C higher than that under the current operation but still within the target range (1250 ± 50 °C). The reduction in combustion air decreased energy losses and improved product quality, lowering the molar oxygen content in the furnace atmosphere from 4.9 × 10² mol to 6.7 × 10¹ mol. Additionally, annual savings of 4,793,472 kg of natural gas and 13,884 tons of steel were estimated owing to reduced oxidation losses. The proposed air–fuel adjustment led to estimated annual energy savings (equivalent to 4,793,472 kg of natural gas) and a reduction in material loss due to oxidation from 4.5% to 3.75% (an absolute reduction of 0.75 percentage points; relative reduction ≈ 16.7%), which has a significant industrial impact on metal conservation and descaling cost reduction. Although there are CFD studies on plate overheating and scale growth separately, this work presents three main contributions: (1) the integration, within a single numerical framework, of combustion, radiation, species transport, oxidation kinetics, and actual plate movement using a dynamic mesh; (2) validation against continuous industrial records (16 thermocouples) and quantification of operational benefits such as fuel savings and reduced material loss; and (3) a comparative analysis between actual and optimized conditions, which standardize the air–methane ratio. Full article

Kyoho grape, a leading table grape variety in China, is prone to rapid postharvest deterioration due to its soft texture and high respiration rate. Despite the use of low-temperature storage and modified atmosphere packaging (MAP), systematic studies defining the optimal combination of subzero temperature and gas composition for Kyoho grapes remain lacking. This study aimed to fill this gap by evaluating the synergistic effects of subzero temperature and MAP on quality preservation. Results demonstrated that storage at −1 °C most effectively maintained fruit firmness, stem freshness, and key biochemical components. Based on this temperature, a gas composition of 3% O₂, 15% CO₂, and 82% N₂ was identified as the most effective, extending postharvest shelf life to 54 days. Additionally, a kinetic shelf-life prediction model based on firmness changes was developed with relative errors below 10%, demonstrating high accuracy. This study establishes an integrated preservation strategy combining subzero temperature (−1 °C) and optimized MAP (3% O₂, 15% CO₂, 82% N₂) that significantly extends the shelf life of Kyoho grapes, providing a practical solution for enhancing postharvest quality. Full article

This study employs a Computational Fluid Dynamics (CFD) approach based on the Two-Fluid Model (TFM) to investigate the CO₂ capture characteristics in a bubbling fluidized bed reactor using potassium carbonate (K₂CO₃) as the sorbent. The simulations are conducted at five superficial gas velocities ranging from 1.5 to 3.5 times the minimum bubbling velocity (u_mb = 0.26 m/s), with a particle diameter of 0.4 mm, particle density of 2300 kg/m³, and an initial solid volume fraction of 0.55. The gas mixture consists of CO₂, H₂O, and N₂ at a molar ratio of 0.1:0.1:0.8 and a temperature of 343 K. First, the numerical simulation was validated against experimental data reported in the literature, confirming its accuracy in quantitatively describing the adsorption process. Subsequently, the distributions of CO₂ concentration and adsorption reaction rate in both the bubble phase and the emulsion phase were analyzed under different superficial gas velocities. The simulation results indicate that CO₂ concentration and adsorption reaction rate in both phases decrease along the bed height. Compared to the emulsion phase, the bubble phase exhibits higher CO₂ concentration and gas temperature but a lower adsorption reaction rate. As the gas velocity increases, CO₂ concentration rises in both the bubble and emulsion phases, accompanied by an increase in the proportion of the bubble phase, and a higher CO₂ concentration at the reactor outlet. Further comparison of CO₂ concentrations in the bubble and emulsion phases at the upper part of the bed with the outlet concentration reveals that the outlet CO₂ primarily originates from the unadsorbed portion within the bubble phase, while the contribution from unadsorbed CO₂ in the emulsion phase is almost negligible. Full article

To address global carbon reduction demands, oxy-fuel combustion in circulating fluidized beds (oxy-CFB) has emerged as a highly promising carbon capture technology, offering extensive fuel flexibility and facilitating bioenergy with carbon capture and storage (BECCS). However, its commercialization is hindered by significant energy penalties and complex scale-up challenges. This review comprehensively analyzes the fundamental multiphase mechanisms, heat transfer behaviors, and multi-pollutant emission characteristics of oxy-CFB systems, drawing upon multiscale modeling advancements and operational data from pilot to 30 MW_th industrial demonstrations. Replacing air with an O₂/CO₂/H₂O mixture fundamentally alters gas–solid hydrodynamics and char conversion pathways, necessitating active fluidization state re-specification. Despite shifting optimal desulfurization temperatures and introducing recarbonation risks, the technology demonstrates inherent advantages in synergistic pollutant control, including the complete elimination of thermal NO_x. While atmospheric oxy-CFB is technically viable, transitioning to pressurized operation is critical to minimizing system efficiency penalties. Furthermore, integrating oxygen carrier-aided combustion (OCAC) and developing advanced predictive control strategies are essential to managing multi-module thermal inertia and enabling rapid dynamic responsiveness for modern power grids. Full article

Nitrous oxide (N₂O) is recognized as a potent greenhouse gas, and 60% of atmospheric N₂O emissions come from cropland soils. Potassium (K) is an important fertilizer for rice paddy fields. K fertilizer decreased the abundance of functional genes mediating nitrification and denitrification processes, thereby mitigating N₂O emissions. However, few studies have explored the effect of K fertilization rates on N₂O emissions and grain yields, as well as the associated soil properties and aboveground N accumulation in paddy fields under different irrigation regimes. This study aimed to propose an optimum combination of K fertilization rate and irrigation regime to increase grain yield while reducing N₂O emissions. Here, a 2-year field experiment using a split-plot design with three replicates was conducted to assess the effect of three K fertilization rates (K₀: 0 kg ha⁻¹, K₇₅: 75 kg ha⁻¹, K₁₅₀: 150 kg ha⁻¹) on N₂O emissions, grain yield, aboveground N accumulation, and soil properties, including soil redox potential (Eh), NH₄⁺, NO₃⁻, soil gene abundance of AOA, AOB, nirK, nirS, nirK/nirS, and nosZ, under continuous flooding irrigation (I_CF) and alternate wetting and drying irrigation (I_AWD). The soil physicochemical properties, the gene abundance and the aboveground N accumulation were evaluated and used to explain how irrigation and K fertilization affect grain yield and N₂O emissions. We found that I_AWD significantly increased N₂O emissions by 38% compared to I_CF, and K fertilizer significantly reduced N₂O emissions by 15% relative to K₀. The effects of I_AWD and K fertilizer on N₂O emissions can be attributed to the combined impact of soil physicochemical properties and the abundance of functional genes governing N₂O emissions. Both irrigation regimes produced equivalent grain yield and aboveground N accumulation. Shifting from I_CF to I_AWD, the increase in N₂O emissions can be mitigated by K fertilization. Moreover, K₇₅ and K₁₅₀ had similar effects in reducing N₂O emissions and yield-scaled N₂O emissions, while K₇₅ had a lower K fertilizer cost and higher K partial factor productivity. Therefore, applying K fertilizer at 75 kg ha⁻¹ under I_AWD is identified as a potentially suitable rate to secure grain yield while effectively mitigating N₂O emissions. Full article

Motivated by altitude-induced fluctuations in oxygen partial pressure (pO₂) and their impacts on PCS off-line arc motion and erosion response, this study proposes a comparative experimental approach featuring single-variable control under constant total pressure and coordinated multi-source electrical-signal observation. A reciprocating current-carrying arc-generation rig was established, in which pO₂ was equivalently regulated via a constant-pressure gas substitution and mixing approach. High-speed imaging–based quantitative vision analysis was integrated with synchronized voltage–current measurements to evaluate the net effects of five O₂ volumetric fraction levels (6, 11, 14, 17, and 21 vol%) under a DC supply of 120 V/25 A on arc dynamics, electrochemical processes, and contact pair erosion. Based on repeated-test results, the 14 vol% case exhibited the poorest stability (maximum fluctuation coefficient 20.306%), whereas the 17 vol% case showed the lowest current-carrying efficiency (minimum 56.070%) together with the most severe erosion damage. Moreover, with increasing pO₂, the erosion morphology evolved in a staged manner, transitioning from localized central ablation accompanied by melt-related traces to adhesive wear-induced delamination, and ultimately to electrochemical oxidative wear. Overall, pO₂ imposes a pronounced non-monotonic “window effect” on arc stability and erosion, providing key evidence for PCS structural optimization and risk assessment in open operating environments. Full article

Underwater micro-bubble detection entails multiple challenges, including diminutive target sizes, sparse pixel information, pronounced specular highlights and water scattering, indistinct bubble boundaries, and adhesion or overlap between instances. To address these issues, we propose HSMD-YOLO, an improved detector tailored for high-resolution micro-bubble detection and built upon YOLOv11. The model incorporates three novel components: the Scale Switch Block (SSB), a scale-transformation module that suppresses artifacts and background noise, thereby stabilizing edges in thin-walled bubble regions and enhancing sensitivity to geometric contours; the Global Local Refine Block (GLRB), which achieves efficient global relationship modeling with an asymptotic linear complexity ($O\left(N\right)$) in spatial dimensions while further refining local features, thereby strengthening boundary perception and improving bubble–background separability; and the Bidirectional Exponential Moving Attention Fusion (BEMAF), which accommodates the multi-scale nature of bubbles by employing a parallel multi-kernel architecture to extract spatial features across scales, coupled with a multi-stage EMA based attention mechanism to enhance detection robustness under weak boundaries and complex backgrounds. Experiments conducted on an Side-Illuminated Light Field Bubble Database (SILB-DB) and a public gas–liquid two-phase flow dataset (GTFD) demonstrate that HSMD-YOLO achieves mAP@50 scores of 0.911 and 0.854, respectively, surpassing mainstream detection methods. Ablation studies indicate that SSB, GLRB, and BEMAF contribute performance gains of 1.3%, 2.0%, and 0.4%, respectively, thereby corroborating the effectiveness of each module for micro-scale object detection. Full article

The conformational properties and intrinsic reactivity of unsaturated CH₂=C(R)XH systems (R = –H, –CH=CH₂, –C≡CH, –C≡N, –Cl, –phenyl, –cyclopentadienyl, –pyrrole; X = O, S, Se)—namely enols, enethiols, and eneselenols—have been investigated using G4 and CCSD(T) calculations. All compounds exhibit antiperiplanar (ap) and anticlinal (ac)-conformers that are nearly isoenergetic, as their relative stabilities are governed by subtle noncovalent interactions, which are analyzed in detail. Both conformers are therefore expected to coexist in the gas phase, and because the rotational barriers are very low, their interconversion is effectively barrierless under typical conditions. In contrast, the corresponding protonated species display significantly higher barriers, approximately three to five times larger. The keto–enol tautomerization involves activation barriers exceeding 180 kJ·mol⁻¹, confirming that, as in other keto–enol rearrangements, the process is not monomolecular. Protonation generally occurs at the methylene carbon, with the exceptions of the –C≡CH and –C≡N derivatives. Strong linear correlations are found among the proton affinities of the three families studied, which follow the trend: enols > enethiols > eneselenols. All systems behave as strong carbon bases; some are predicted to be 20–21 orders of magnitude more basic than ketene and 3–5 orders of magnitude more basic than vinylimine in terms of equilibrium constants. Deprotonation preferentially occurs at the X–H group in nearly all cases. The only exception is the cyclopentadienyl-substituted enol, for which deprotonation of the cyclopentadienyl moiety is favored due to enhanced aromatic stabilization of the resulting anion. Overall, acidity increases along the series O < S < Se. Full article

Photocatalytic CO₂ reduction to high-value-added C₂+ products is a practical route from an economic viewpoint for advancing the industrialization of CO₂ conversion. Despite significant progress in catalyst modification in recent years (such as defect engineering, heterostructure construction, and single-atom modification), the generation of C₂+ products still faces challenges due to the slow kinetics of multi-electron reactions and the high thermodynamic barrier for C-C coupling. Moreover, the severely imbalanced molar ratio of CO₂ to H₂O in the traditional liquid-phase reaction systems exacerbated the challenge to the unfavorable situation. This article summarizes various strategies to improve the yield of C₂+ products through the regulation of reaction environments, including: (1) increasing the partial pressure of CO₂ to enhance its solubility; (2) using alternative solvents like ionic liquids to reduce water content; (3) transitioning the reaction system from liquid phase to gas phase; (4) designing a three-phase (gas–liquid–solid) interface or floating photocatalysts to optimize reactant transfer and local concentration; (5) utilizing photothermal synergistic effects to enhance the reaction temperature and efficiency under concentrated light. It also discusses the role of different reactor designs in improving the reaction environment. Finally, it emphasizes that future research should pay more attention to the optimization of the reaction environment engineering in addition to catalyst design, providing new perspectives for achieving efficient and highly selective C₂+ products in CO₂ photoreduction. Full article