Search Results (441)

Titanosilicates are Lewis acid catalysts widely applied in liquid-phase olefin epoxidation; however, in the presence of water, their performance is often limited by structural instability, active-site deactivation, and competing side reactions. This review critically examines hydrophobization strategies—based on controlled reduction in silanol groups or incorporation of organic functionalities—and discusses the experimental approaches used to evaluate surface hydrophobicity, including water adsorption measurements, infrared spectroscopy of silanols, contact angle analysis, and complementary spectroscopic methods. Although direct quantitative comparison among studies is hindered by differences in reaction systems and the lack of standardized catalytic metrics, consistent trends emerge. Lower silanol densities are generally associated with improved preservation of isolated tetrahedral Ti (IV) sites, higher H₂O₂ utilization efficiency, and reduced secondary epoxide ring-opening, leading to enhanced activity and selectivity under comparable conditions. These improvements are attributed to decreased local water activity, suppression of non-productive oxidant decomposition, and stabilization of Ti-peroxo intermediates responsible for direct epoxidation. Incorporation of organic groups produces a similar beneficial effect when introduced in moderate amounts, increasing surface hydrophobicity without significantly perturbing Ti coordination. However, beyond an optimal loading, catalytic performance declines due to pore blockage, diffusion limitations, and partial masking of active sites, revealing a threshold behavior. Fluoride also plays a dual role: when used during synthesis, it influences the insertion and distribution of framework Ti, whereas as a post-treatment, it primarily regulates silanol density and surface polarity while preserving active sites. Finally, hydrophobicity cannot be considered independently, as its impact depends on the solvent, oxidant, olefin nature, and active-site location, which collectively govern activity, selectivity, and catalyst stability. Full article

The adjustable speed hydro-generating unit has a complex three-phase alternating current excitation structure. The existing rotor winding short circuit (RWSC) fault diagnosis methods are generally difficult to use to locate the fault location and identify the severity of the fault. Therefore, an offline diagnosis method for the internal RWSC of an adjustable speed hydro-generating unit is proposed in this paper. Firstly, after the unit is shut down, the low-voltage pulse signal is repeatedly injected into the rotor winding by the pulse generator. By comparing and analyzing the voltage response characteristics under different types of short circuit faults, an identification method of rotor winding short circuit fault type and fault phase based on detecting the reverse polarity sub-spike is proposed. Furthermore, the short circuit fault point can be accurately located by combining ensemble empirical mode decomposition (EEMD) with the Teager energy operator (TEO). Finally, the fault factor is constructed based on the area between the characteristic waveform and the zero line, and the quantitative evaluation of the severity of the short circuit fault is realized based on this. The effectiveness of the proposed fault diagnosis and location method is verified by the simulation results. Full article

Spring phytoplankton bloom mechanisms in the Bohai Sea show clear spatial differences, but the physical–biological coupling in the ice-covered Liaodong Bay (LDB) remains poorly understood. Utilizing satellite observations and high-resolution reanalysis data from 2009 to 2023, this study explores the drivers of spring blooms through generalized additive models (GAMs) and the Equation of State of Seawater (EOS). The results reveal pronounced regional heterogeneity. In the southern Bohai Sea, bloom dynamics are co-regulated by a complex combination of nutrient availability and localized physical mixing. In contrast, blooms in LDB are predominantly driven by the shoaling of the mixed layer depth (MLD), a physical state intrinsically linked to winter sea-ice melt. Linear decomposition of water density via EOS quantitatively demonstrates that spring stratification in LDB is salinity-dominated (contributing ~60.7%), rather than thermally driven. The rapid influx of low-salinity meltwater forms a strong halocline that suppresses vertical mixing and physically compresses the MLD into the euphotic zone. Consistent with Sverdrup’s Critical Depth Theory, this inferred physical pathway effectively alleviates light limitation and acts as the primary trigger for the early bloom peak timing. This complete melting–freshening–stratification–light coupling chain provides a novel physical perspective on how mid-latitude marginal sea ecosystems respond to climate change, distinct from canonical polar light-limitation models. Full article

Magnetic-field-assisted electrocatalysis offers a powerful route to enhance the oxygen evolution reaction (OER) by coupling spin-dependent effects with magnetohydrodynamic phenomena. Here, we present a unified study of cobalt ferrite (CoFe₂O₄)-based nanofilms, elucidating the combined roles of rare-earth doping, nanoparticle size, film morphology, and electrode substrate magnetism on OER performance under external magnetic fields. The effect of UV-light irradiation is also investigated. CoFe₂O₄ and yttrium-doped CoFe₂O₄ nanoparticles were synthesized via thermal decomposition and self-combustion routes, yielding single-domain particles with distinct structural and magnetic properties, and assembled into homogeneous nanofilms using the Langmuir–Blodgett technique. Electrocatalytic measurements in alkaline media reveal that intrinsic OER activity is primarily governed by film compactness and charge-transfer efficiency, while the magnitude of magnetic-field-induced enhancement depends on the magnetic response of both the nanofilms and the supporting electrode. Ferromagnetic substrates promote enhanced catalytic activity under magnetic fields, whereas diamagnetic substrates can exhibit suppressed performance. Across all systems, the strongest enhancement is observed when the magnetic field is applied parallel to the electrode surface, reflecting the combined effects of spin polarization and Lorentz-force-driven mass transport. UV-light irradiation is also evaluated as an external stimulus to promote the reaction. Our findings establish a comprehensive framework for designing magnetically assisted OER electrocatalysts and demonstrate that magnetic-field effects can rival or complement rare-earth doping or UV-light irradiation, offering a sustainable pathway toward high-efficiency water oxidation. Full article

Achieving green development demands simultaneously balancing between economic growth and pollutant emission reduction, which can have complex impacts on regional disparities. This study measures the green development efficiency (GDE) for 266 Chinese cities during the 11th–13th National Five-Year Plan periods (2006–2020) by a global non-oriented endogenous directional distance function (endogenous DDF) that endogenizes direction vectors using the maximum improvement potential. Regional disparities are then quantified and decomposed by the Dagum Gini coefficient decomposition (intra-group, net inter-group, and hypervariable density) across seven regions. To make the policy implications operational, we further derive the separable economic efficiency loss and environmental efficiency loss components from the endogenous DDF and identify cities’ optimal preference options (γ); scenario experiments (5–30% improvement) are used to validate whether differentiated improvement directions can simultaneously raise GDE and narrow disparities. The main findings are as follows: (1) From the 11th Five to the 13th Five, cities’ GDE evolved from a median-centered distribution to a bimodal distribution, accompanied by spatial polarization and widening regional disparities. (2) By the 13th Five period, regional disparities had deepened, mainly driven by inter-group differences, notably hypervariable density. The original regional development patterns were disrupted, leading to increased overlap across cities. (3) Most cities have shifted from a “green-oriented” to an “economic-oriented” development preference since the 13th Five period. North China, South China, and East China favor pollution reduction, while others prioritize economic growth. (4) Preference options for cities with varying resource endowments should adapt over time. Under various hypothetical scenarios, cities adopting differentiated optimal options can enhance their GDE while simultaneously narrowing regional disparities. Reducing arbitrariness in balancing emission reduction and economic growth can promote regionally coordinated and environmentally sustainable development. Full article

China’s rapid urbanization has driven a pronounced east–west sustainability schism, where affluent coastal corridors face cumulative pollution pressures, while interior regions grapple with ecological fragility and comparatively weaker governance capacity. To diagnose this divergence, we establish the Environmental Stressor Regulatory Capacity (ESRC) framework, integrating indicators across industrial emissions, resource intensity, economic innovation, and institutional resilience. Leveraging Chinese spatiotemporal data from 283 prefecture-level cities from 2003 to 2021, our multi-method analysis reveals three core findings: Dagum Gini decomposition indicates intensifying interregional inequality. Kernel density estimation identifies four distinct transition archetypes: eastern high-base consolidation, central relay diffusion, western polarization–correction, and northeastern asymmetric revitalization. Crucially, random forest regression highlights the high predictive salience of Regulatory Capacity for ESRC variation. These findings are consistent with institutional asymmetry as the key explanatory factor for why some Western regions remain locked in spatial traps. These results may inform targeted ecological compensation for critical zones to support SDG advancement with regional equity. Full article

Lightweight, efficient, and reversible hydrogen storage materials are critical for the advancement of hydrogen-based energy technologies. In this work, we present a comprehensive density functional theory (DFT) investigation of hydrogen storage in pristine and metal-decorated C₈ carbon quantum dots (CQDs), representing ultrasmall, highly curved nanomaterials at the molecular–nanoscale interface. Lithium, magnesium, and titanium were investigated as representative decorating metals to tailor hydrogen adsorption strength and reversibility. The pristine C₈ quantum dot is structurally stable but exhibits negligible hydrogen affinity (−0.062 eV per H₂), rendering it unsuitable for practical storage applications. In contrast, metal decoration significantly enhances hydrogen adsorption while preserving molecular H₂ physisorption, yielding optimal single-molecule adsorption energies of −0.172, −0.304, and −0.451 eV for Li-, Mg-, and Ti-CQDs, respectively. Sequential adsorption analysis indicates exceptionally high hydrogen uptakes of up to 18 H₂ molecules for Li-CQD and 20 H₂ molecules for both Mg- and Ti-CQDs, corresponding to very high theoretical gravimetric capacities. Energy decomposition and interaction region analyses demonstrate that hydrogen uptake proceeds via a cooperative physisorption mechanism driven by dispersion, electrostatic, and polarization interactions, strongly enhanced by quantum confinement and extreme curvature effects inherent to the CQD. Grand canonical thermodynamic modeling confirms fully reversible hydrogen storage under practical temperature and pressure conditions. Among the systems studied, Mg-CQD exhibits the most favorable balance between adsorption strength and desorption accessibility, delivering a remarkable reversible gravimetric hydrogen storage capacity of 21.7 wt%, significantly surpassing most metal-decorated graphene-, fullerene-, and carbon nanotube-based materials reported to date. These results establish metal-decorated C₈ quantum dots as a new class of high-performance nanomaterials for reversible hydrogen storage and demonstrate the potential of ultrasmall carbon quantum dots to overcome the long-standing trade-off between hydrogen uptake and reversibility in nanostructured storage media. Full article

Monitoring small water body coverage spatiotemporal evolution in karst areas of complex hydrogeology is pivotal for water resource management and disaster assessment. With recent infrastructure expansion, intensive tunnel excavation has occurred in Chongqing’s Geleshan, a typical karst region with fragile aquifers. It has disrupted hydrogeological systems, triggering ground subsidence, groundwater leakage, and subsequent reservoir desiccation, as well as threatening regional water security and ecology. Thus, monitoring reservoir coverage evolution is critical to clarify dynamics and driving mechanisms. Synthetic Aperture Radar (SAR) is ideal for water body mapping, enabling data acquisition independent of illumination and weather. However, traditional SAR-based water extraction methods are hampered by low-scatter noise and poor adaptability to hydrological fluctuations. To address this, a two-stage dual-polarization SAR clustering algorithm (TSDPS-Clus) was developed using 452 time-series Sentinel-1 images (7 February 2017–24 August 2025). Specifically, the Kolmogorov–Smirnov test via pixel-wise time-series statistics screened core water areas, built candidate regions, and mitigated noise. Subsequently, dual-polarization and positional features were fused via singular value decomposition (SVD) to generate a high-discrimination low-dimensional feature set, followed by the Iterative Self-Organizing Data Analysis Techniques Algorithm (ISODATA) clustering for high-precision extraction. Results demonstrate that the algorithm suits reservoir storage-desiccation dynamics; dual-polarization complementarity boosts accuracy and clarifies six reservoirs’ spatiotemporal evolution. Notably, post-2023, tunnel excavation-induced land subsidence increased drying frequency and duration, with a 24-month maximum cumulative desiccation period. Full article

The escalation of thermal runaway in lithium-ion batteries presents severe safety hazards that necessitate advanced monitoring protocols to ensure early warning of potential failures. Carbon dioxide (CO₂) is released during preliminary decomposition well before catastrophic failure occurs, thereby providing a strategic advantage for early-stage warning. Consequently, identifying materials with high-selective CO₂ recognition is an essential prerequisite for developing reliable sensing platforms. This study integrates Grand Canonical Monte Carlo simulations with Random Forest (RF) models to systematically screen 1470 MOFs from the CoRE-MOF 2019 database. The screening process evaluates selective CO₂ recognition under multicomponent competitive adsorption conditions involving CO₂, C₂H₄, and O₂. The performance evaluation is based on working capacity, selectivity, and the trade-off between working capacity and selectivity (TSN). The RF model achieves high predictive accuracy, with tested R² exceeding 0.92 on the test samples. Shapley Additive Explanations (SHAP) interpretability analysis identifies Q⁰_st(CO₂), Q⁰_st(C₂H₄), WEPA, K_H(C₂H₄), and ETR as key performance drivers. The results indicate that CO₂ selectivity is constrained by the binding strength of competing C₂H₄. Optimal materials tend to have hard Lewis acid centers and polar inorganic clusters to minimize non-specific π-interactions with interfering species. Top-performing MOFs require balanced structural features, concentrating in moderate surface areas (965–1975 m²/g), narrow pore windows (PLD ≈ 4–7 Å, LCD ≈ 5.5–9.6 Å), high void fractions above 0.6, and low densities below 1.3 g/cm³. AJOTEY emerges as the optimal candidate with a TSN of 6.43 mol/kg, combining substantial working capacity (4.57 mol/kg) with strong selectivity (25.52). These results will accelerate the discovery of sensing materials and provide a practical pathway for MOF-based CO₂ sensor development to enhance lithium-ion battery safety. Full article

To address the strong nonstationarity and complex multi-source interference in vibration signals of bogie axle-box bearings, a fault diagnosis method combining Improved Empirical Wavelet Transform (IEWT) and a Convolutional Neural Network (CNN)–Transformer model is proposed. First, the vibration signals are decomposed using the IEWT method, where dynamic frequency-band division adaptively determines the decomposition bands. This yields multiple intrinsic mode functions, and key modes containing fault features are selected based on information entropy. Next, the selected key modes are fused and transformed into polar coordinate projection maps, further enhancing the distinctiveness of fault data features. Finally, CNN is employed to extract local features from the vibration signals, while the Transformer captures long-range dependencies through the self-attention mechanism, significantly improving feature modeling for complex signals. To validate the fault diagnosis performance of the IEWT and CNN–Transformer model, vibration signals from bogie axle-box bearings in urban railways are analyzed. Analysis of the experimental data suggests that the adaptive decomposition of bearing signals using IEWT effectively overcomes the fixed band boundary limitations of traditional EWT, enhancing the precision of signal feature extraction. The integration of polar coordinate projection maps more accurately illustrates frequency variations and amplitude differences in the signals, fully capturing their nonstationary characteristics. Among the five fault categories of bogie axle-box bearings, the proposed method achieves an accuracy of 99.46%, a recall rate of 99.52%, and an F1-score of 0.995, significantly outperforming five classic comparison methods. This demonstrates that the combined strengths of CNN and Transformer yield higher classification accuracy and better robustness in handling complex fault patterns, effectively solving the fault diagnosis challenges for bogie axle-box bearings. Full article

We develop a fully gauge-invariant analysis of gravitational-wave polarizations in metric $f\left(R\right)$ gravity with a particular focus on the modified Starobinsky model $f\left(R\right)=R+\alpha R^2-2\mathsf{\Lambda }$, whose constant-curvature solution $R_d=4\mathsf{\Lambda }$ provides a natural de Sitter background for both early- and late-time cosmology. Linearizing the field equations around this background, we derive the Klein–Gordon equation for the curvature perturbation $\delta R$ and show that the scalar propagating mode acquires a mass $m_{\psi }^2=1/\left(6\alpha \right)$, highlighting how the same scalar degree of freedom governs inflationary dynamics at high curvature and the propagation of gravitational waves in the current accelerating Universe. Using the scalar–vector–tensor decomposition and a decomposition of the perturbed Ricci tensor, we obtain a set of fully gauge-invariant propagation equations that isolate the contributions of the scalar, vector, and tensor modes in the presence of matter. We find that the tensor sector retains the two transverse–traceless polarizations of General Relativity, while the scalar sector contains an additional massive scalar propagating degree of freedom, which manifests through breathing and longitudinal tidal responses depending on the wave regime and detector frame. Through the geodesic deviation equation—computed both in a local Minkowski patch and in fully covariant de Sitter form—we independently recover the same polarization content and identify its tidal signatures. The resulting framework connects the extra scalar polarization to cosmological observables: the massive scalar propagating mode sets the range of the fifth force, influences the time evolution of gravitational potentials, and affects the propagation and dispersion of gravitational waves on cosmological scales. This provides a unified, gauge-invariant link between gravitational-wave phenomenology and the cosmological implications of metric $f\left(R\right)$ gravity. Full article

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) δD, CO₂, and CH₄ records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve understanding of the intensity, amplitude, and asymmetry features of 73 marine isotope stages/substages (MISs) and seven glacial terminations. The Antarctic stack record can be described by a variance-weighted superposition of ten thermal waves of different origins (mid-term oscillation, orbitals, and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, amplitude, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low-intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low-interference regions, where dominant destructive patterns minimize the thermal envelope. The positive skewness of the EPICA stack resulted from constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect has led to the saw-tooth shape of glacial cycles, which was strongly induced by interference. Full article

Metasurface cut-off perfect absorbers (MCPAs) are of great significance in technology. Research on MCPAs is extensive, whereas that on metasurface dual-band cut-off absorbers (MDCPAs) remains relatively scarce. An MDCPA operating in the visible and near-infrared (NIR) bands is proposed. This absorber realizes dual-band cut-off perfect absorption by integrating a bottom silver (Ag) layer, a silicon nitride (Si₃N₄) layer, Ag cylinders embedded with alumina (Al₂O₃) cylinders, and Al₂O₃ fan-shaped pillars. Finite-difference time-domain (FDTD) simulation calculation indicates that the absorber achieves polarization-independent high absorption (average 0.956) in the 676 nm–872 nm band and low absorptions (averages: 0.075 and 0.019, respectively) in the 400–600 nm and 980–1400 nm bands. We also use electromagnetic multipole decomposition, which is combined with electromagnetic field diagrams, to explain the origin of the dual-band cut-off absorption. This work proposes an effective strategy for realizing a high-performance MDCPA in the visible and NIR bands. With high cut-off sharpness and absorption contrast, the proposed MDCPA exhibits significant application potential in advanced nanophotonic devices and systems. Full article

The electrical resistivity and acoustic properties of marine sediments are essential for understanding their physical and mechanical behavior. Over recent decades, significant advancements have been made in both in situ and laboratory measurement techniques, alongside theoretical models, to establish correlations between these geophysical parameters and sediment properties such as porosity, saturation, and consolidation degree. However, a comprehensive comparison of the advantages, limitations, and applicability of different measurement methods remains underexplored, particularly in complex scenarios such as gas hydrate-bearing sediments. This review provides an in-depth synthesis of recent developments in in situ and laboratory testing technologies for assessing the resistivity and acoustic characteristics of marine sediments. Special emphasis is placed on the latest advances in acoustic measurements during gas hydrate formation and decomposition. The review highlights key challenges, including (1) limited vertical resolution in in situ resistivity measurements due to probe geometry; (2) errors arising from electrode polarization and poor soil–electrode contact; and (3) discrepancies in theoretical models linking geophysical parameters to sediment properties. To address these challenges, future research directions are proposed, focusing on optimizing electrode array designs for high-resolution resistivity measurements and developing non-destructive acoustic techniques for deep-sea sediments. This work offers a critical reference for marine geophysics and offshore engineering researchers, aiding the selection and development of testing technologies for effective marine sediment characterization. Full article

Compared to traditional marine productivity, marine new-quality productivity (MNQP) is composed of advanced productive forces driven by the deepening application of new technologies, is characterized by the rapid emergence of new industries, new business models, and new modes of operation, and is marked by a substantial increase in total factor productivity in the marine economy. It has, therefore, become a new engine and pathway for China’s development into a maritime power. The main research approaches and conclusions of this paper are as follows: ① Using a combined order relation analysis method–Entropy Weight Method (G1-EWM) weighting method that integrates subjective and objective factors, we measured the development level of China’s MNQP from 2006 to 2021 across two dimensions: “factor structure” and “quality and efficiency”. The findings indicate that China’s MNQP is developing robustly and still holds considerable potential for improvement. ② Utilizing Gaussian Kernel Density Estimation and Spatial Markov Chain analysis to examine the dynamic evolution of China’s MNQP, the study identifies breaking the low-end lock-in of MNQP as crucial for accelerating balanced development. Spatial imbalances in China’s MNQP may exist both at the national level and within the three major marine economic zones. ③ To further examine potential spatial imbalances, Dagum Gini decomposition was employed to assess regional disparities in China’s MNQP. The DER polarization index and EGR polarization index were used to analyze spatial polarization levels, revealing an intensifying spatial imbalance in China’s MNQP. ④ Finally, geographic detectors were employed to identify the factors influencing spatial imbalances in China’s MNQP. Results indicate that these imbalances result from the combined effects of multiple factors, with marine economic development emerging as the core determinant exerting a dominant influence. The core conclusions of this study provide theoretical support and practical evidence for advancing the enhancement of China’s MNQP, thereby contributing to the realization of the goal of building a maritime power. Full article