Search Results (248)

Despite the rapid proliferation of unmanned aerial vehicles (UAVs) across industrial, agricultural, and scientific domains, their deployment remains constrained by limited endurance, aerodynamic inefficiency, and acoustic emissions, all mediated by a shared onboard energy budget. Existing biomimetic UAV reviews have generally treated aerodynamics, structures, sensing, control, and energy systems as parallel topics rather than as interacting components of a unified aerial architecture. Drawing primarily on literature published between 2015 and June 2026 and identified through searches of Web of Science, Scopus, and Google Scholar, this review addresses this gap by examining bio-inspired technologies across six principal domains: aeroacoustic and passive flow control, aerodynamic efficiency, multifunctional structural composites, neuromorphic sensing and control, ionic energy storage, and energy harvesting. Its principal contribution is a cross-domain synergy analysis identifying five performance couplings and one structural enabling architecture through which these domains interact physically and functionally. Representative examples include serration-based propeller geometries that can simultaneously reduce noise and power demand; morphing wing surfaces that serve as both aerodynamic structures and triboelectric harvesting substrates; and neuromorphic spiking neural networks that have been reported, in specific event-vision inference benchmarks, to reduce inference energy by three to four orders of magnitude relative to embedded graphics processing unit (GPU)-based implementations. Mechanical harvesting outputs nonetheless remain orders of magnitude below propulsion requirements and are thus positioned as supplementary. Four systemic barriers (unquantified mass–energy balance, undocumented durability, aeroelastic co-design gaps, and heterogeneous metrics) are evaluated, and the resulting synthesis indicates that advancing bio-inspired UAVs requires a transition from structural imitation to functional, system-level biomimetics. Full article

Surface solar radiation (SSR) is a fundamental component of the Earth’s energy budget, driving climate dynamics, ecosystem stability, and solar energy potential. By integrating high-quality in situ observations from 87 ground stations with multi-source satellite products (CERES) and reanalysis data, this study systematically quantifies the spatiotemporal evolution and driving mechanisms of SSR across China from 1994 to 2022. Nationally, SSR exhibits a significant brightening trend of 72 MJ m⁻² per decade, despite pronounced regional and seasonal divergence. Annual SSR increases significantly in North, Central, Southwest, and South China—with North China experiencing the fastest growth (160 MJ m⁻² per decade). Strikingly, the Tibetan Plateau exhibits a persistent and significant “dimming” trend (−86 MJ m⁻² per decade). Furthermore, spatial analysis reveals that summer SSR trends show a unique meridional “+ − +” dipole structure that closely resembles the dominant mode of summer precipitation over eastern China. Quantitative attribution analysis indicates that declining aerosol optical depth (AOD) is the primary driver of brightening across most of China, whereas the dimming on the Tibetan Plateau is specifically triggered by increased atmospheric water vapor, cloud cover, and precipitation. These findings underscore that in sensitive high-altitude regions, regional climate dynamics and hydrological feedback can override the radiative effects of anthropogenic aerosol reductions, highlighting the necessity for localized solar resource assessments. Full article

Undular bores are classical shallow-water phenomena in which a sharp transition between two flow states is replaced, in a dispersive theory, by an oscillatory wave train. In non-dispersive shallow-water theory, the bore is associated with an apparent loss of mechanical energy. In dispersive models, this energy can be interpreted as being redistributed into the oscillatory tail. The aim of this short article is to formulate a possible extension of this interpretation when surface tension is included. The capillary contribution modifies the long-wave dispersion coefficient through a Bond-number-dependent term and adds an additional surface energy to the total energy functional. We derive the basic capillary-gravity KdV scaling, identify the modified energy density, and discuss how surface tension may affect the amplitude, wavelength, and energy flux of the trailing oscillations. The proposed direction is relevant for small-scale laboratory bores, tidal-bore fronts, and shallow tidal currents in which a rapid transition generates short dispersive oscillations. Special attention is paid to the critical value $Bo=1/3$, where the classical KdV dispersion vanishes, and a fifth-order correction is required. Full article

Group III-nitride semiconductors (GaN, AlN, InN) serve as foundational materials for modern optoelectronics, high-frequency microelectronics, and next-generation energy harvesting devices. However, traditional high-temperature epitaxy (>700 °C) introduces severe thermal stress, high dislocation densities, and fundamental incompatibility with flexible substrates or CMOS back-end-of-line (BEOL) processes. Plasma-enhanced atomic layer deposition (PEALD) provides a disruptive, ultra-low thermal budget (<300 °C) pathway for atomic-scale precision growth and conformal coating. This review systematically summarizes recent frontiers in PEALD-synthesized Group III-nitrides and 2D/3D polar heterostructures. First, we dissect the microscopic nucleation kinetics, surface bond reconstruction, and impurity suppression mechanisms across diverse substrates, including Si, sapphire, quartz, metals, and flexible polymers. Next, we highlight 2D template-assisted van der Waals epitaxy on graphene and MoS2, and elucidate polarization-driven dipole interactions and band alignment engineering at 2D/3D polar interfaces (e.g., α-In₂Se₃, Janus MoSSe). Furthermore, we comprehensively discuss innovative applications in advanced photovoltaics (as electron transport and passivation layers in perovskite and quantum dot-sensitized solar cells), silicon-based microcavity lasers, high-electron-mobility transistors (HEMTs), and flexible multimodal sensors. Finally, key technological challenges—including the low-thermal-budget paradox, wafer-scale uniformity, and deposition throughput—are addressed alongside future perspectives in area-selective ALD and neuromorphic computing, presenting a cohesive blueprint from underlying physics to macroscopic system integration. Full article

Marine heatwaves (MHWs) are persistent extreme warm events in the ocean that pose substantial threats to marine ecosystems, fisheries, aquaculture, and offshore energy infrastructure. In 2024, the Yellow Sea experienced the most intense MHW on record in terms of cumulative intensity, with sea surface temperature (SST) anomalies exceeding 5 °C and an exceptional duration of 118 days. Using the ERA5 atmospheric reanalysis and GLORYS12V1 ocean reanalysis, this study systematically investigates the characteristics, driving mechanisms, and extremity of this event. Mixed-layer heat budget analysis indicates that enhanced shortwave radiation was the primary contributor to the warming, which is closely linked to the westward-extending and northward-shifting subtropical high. During MHW decay, sea surface cooling is dominated by enhanced latent heat flux, closely linked to typhoon and cold air activities. Further analysis links the positive SST anomalies to the North Atlantic and the Barents Sea warming, which triggered a Eurasian teleconnection wave train. These results highlight the importance of cross-basin climate connectivity in driving regional maritime temperature extremes. Full article

Pumped-storage hydropower (PSH) can modify reservoir evaporation in arid regions by altering water-level dynamics, surface-area exposure, and thermal exchange between reservoirs. This study quantifies operation-induced evaporation changes at the Fukang PSH station in Xinjiang, China, using a one-dimensional lumped hydrodynamic–thermal model driven by hourly station observations and ERA5 reanalysis for 2024. A four-scenario factorial design separates thermal, surface-area, and interaction effects within a unified water energy framework. Under station forcing, fully coupled operation reduces annual system-scale evaporation from 135.36 × 10⁴ m³ to 115.45 × 10⁴ m³, corresponding to a net reduction of 19.91 × 10⁴ m³ (14.7%). Energy-budget analysis identifies advective heat transport as the main pathway linking dispatch, reservoir thermal evolution, and evaporation response, with annual cumulative values of +205 TJ in the upper reservoir and −333 TJ in the lower reservoir. Dispatch-regime experiments further show that stronger exchange-flow operation does not necessarily increase evaporation reduction: the low, baseline, and enhanced schedules produce system-scale net changes of 37.70 × 10⁴ m³, 19.91 × 10⁴ m³, and −3.41 × 10⁴ m³, respectively. These results indicate that evaporation effects in arid-region PSH systems depend on the timing of surface-area exposure relative to local evaporative demand, rather than on exchange-flow magnitude or operating duration alone. Full article

The Tibetan Plateau (TP) plays a crucial role in the global climate system, yet long-term trends in its top-of-atmosphere (TOA) radiation budget remain poorly understood. Using 40-year (1981–2020) CLARA-A3 satellite data and reanalysis datasets, we quantify the spatiotemporal variations of TOA reflected shortwave radiation (RSF) and outgoing longwave radiation (OLR), and decompose the RSF into atmospheric and surface contributions. Additionally, we attribute observed trends to key drivers via multiple linear regression. The TP shows a significant decrease in RSF (−11.06 W/m²) and a significant increase in OLR (+4.88 W/m²). Spatially, OLR increases are widespread and statistically significant over the central and western plateau, while RSF trends are heterogeneous and mostly non-significant except for localized negative trends. The atmospheric contribution to RSF declines markedly (−0.329 W/(m²·year)), whereas the surface contribution increases (+0.061 W/(m²·year)). Attribution analysis identifies cloud fraction change (CFC) as the dominant drivers: it explains most of the RSF decline and the OLR increase. Cloud optical thickness and vertical structure play only minor roles. Our findings demonstrate that decreasing cloud cover is reshaping the TP’s TOA energy budget, providing essential geo-information for the spatial evaluation of climate models and the refinement of satellite-derived radiation products. Full article

Programmable electromagnetic environments, including reconfigurable intelligent surface (RIS)-assisted systems, are often described in terms of physical or controllable degrees of freedom. Such counts, however, do not determine which channel or operator directions can actually be distinguished by a finite measurement architecture. This paper develops an operator-space formulation of observable degrees of freedom for programmable propagation systems. We distinguish three nested layers: the physical operator space generated by the family of physically admissible propagation operators, the effective operator space selected by architectural constraints, and the observable subspace induced by a finite probing architecture. Once the effective space is fixed, observability is characterized by the spectrum of the associated measurement Gram operator. To remove arbitrary amplitude scaling, we introduce a common probe-energy normalization and define the resolution-dependent observable dimension $N_{\mathrm{obs}}\left(\eta \right)$ from the normalized Gram spectrum. The same spectrum also yields an observability condition number, which quantifies the stability of the visible subspace. We then extend the construction to symmetry-resolved operator spaces, showing how invariant probing can create sectorial blind subspaces and how controlled symmetry breaking produces second-order restricted visibility inside the original blind subspace. The mathematical ingredients are standard finite-dimensional tools from operator theory, frame theory, representation theory, and matrix concentration; the contribution is their integration into a measurement-oriented degrees-of-freedom framework for programmable electromagnetic environments. Numerical experiments with normalized probing families, sectorial decompositions, controlled symmetry breaking, and a canonical narrowband RIS-inspired model illustrate that architectures with the same effective dimension and probing budget can exhibit substantially different observable dimensions and conditioning. The results support the view that practical electromagnetic design should optimize not only the number of accessible modes or control states, but also the Gram geometry through which those directions are measured. Full article

Accurate estimation of daily net radiation (R_{n_daily}) at high spatial resolution (1 km) over the Tibetan Plateau (TP) is crucial for understanding land surface energy budgets and climate dynamics. This study proposes a densely connected multilayer perceptron (DenseMLP)-based transfer learning framework, with a two-stage strategy (coarse pre-training on GLASS R_{n_daily}, followed by fine-tuning on limited TP ground observations) using MODIS land surface parameters and auxiliary data to generate 1 km R_{n_daily}. When evaluated on the training set, the proposed model achieves an overall R² of 0.87, MAE of 16.06 W m⁻², RMSE of 21.94 W m⁻², and a near-zero bias of 0.07 W m⁻². On an independent test set, the model maintains robust performance with R² = 0.83, MAE = 17.43 W m⁻², RMSE = 22.55 W m⁻², and bias = −1.12 W m⁻². The method exhibits consistently low bias across individual sites (mostly within ±3.7 W m⁻²) and accurately captures seasonal variability. When applied to the entire TP for 2018, the 1 km R_{n_daily} product reveals clear aspect-related terrain effects and a distinct annual cycle. This framework effectively mitigates site-dependent errors, providing a useful reference for long-term R_n product development over the TP. Full article

Graphite nozzles remain the dominant choice for small hybrid and solid rocket motors operating on laboratory and university budgets, owing to their low cost, ease of machining, and rapid turnaround during iterative design campaigns. These same programs, however, must contend with the fact that graphite erodes through coupled thermochemical and mechanical mechanisms when exposed to the oxidizing species generated by high-energy propellant combustion, and the resulting throat-area growth fundamentally alters the time histories of chamber pressure, thrust, and delivered specific impulse. This paper presents a nozzle-erosion reconstruction model that extracts the time-resolved throat area from coupled thrust and chamber-pressure measurements using the thrust coefficient relationship, scales the reconstructed area history against pre- and post-test throat measurements, identifies the onset and rate of erosion, and accounts for variable sensor lag between the thrust-stand and pressure-transducer signal chains. The model is exercised on two complementary sets of laboratory-scale GOX/ABS hybrid hot-fire data that together span roughly two orders of magnitude in total throat-area change and peak chamber pressures from 0.5 to 3.4 MPa: a controlled three-operating-point campaign conducted in support of the NASA Plume-Surface Interaction (PSI) program, and a set of higher-pressure firings from the laboratory development series in which the technique was matured. Reconstructed erosion-onset times, erosion rates, and total throat-diameter change are reported for each firing, the reconstruction accuracy is characterized as a function of erosion magnitude. A correlation of graphite erosion with chamber pressure is examined across the combined envelope. The results demonstrate the robustness of the reconstruction technique and provide a reusable framework for post-test reconstruction of transient nozzle geometry in rocket-engine ground testing. Full article

We investigatewhether a finite local information capacity of spacetime can account for the gravitational phenomena commonly attributed to cold dark matter. Starting from a covariant effective-field-theory description, we modelcoarse-grained entropy deposition as a dynamical scalar field $S\left(x\right)$ whose stress–energy tensor contributes to structure formation. The macroscopic action contains a single dimensionless coupling λ multiplying the canonical kinetic term, ensuring ghost-free dynamics and conservation of the associated stress–energy tensor. In a slow-roll regime, defined by a covariant source term $\Gamma \equiv \ddot{S}+3H\dot{S}=0$, where H is the Hubble parameter and overdot denotes derivative with respect to cosmic time, and $|\ddot{S}|\ll H|\dot{S}|$, the entropy sector behaves as pressureless dust at background and in linear order. Implemented in a modified Cosmic Linear Anisotropy Solving System (CLASS) Boltzmann solver, the entropy component fits Planck satellite 2018 cosmic microwave background (CMB) data, baryon acoustic oscillation (BAO) measurements, and the Pantheon + Type Ia supernova sample for $0.5\lesssim \lambda \lesssim 2$, while preserving the linear growth factor to within 0.2% over Euclid space telescope scales. To regulate ultraviolet contributions, we introduce a holographically motivated prescription in which gravitationally active entropy deposition is confined to causal two-surfaces, yielding a $\rho \propto r^{-2}$ halo envelope with a finite-density core determined by local entropy saturation. Fixing the flux scale $\mathcal{A}$ from astrophysical entropy budgets reproduces Milky-Way-mass halos without introducing fine-tuned length scales. Pilot N-body simulations that evolve the entropy field on a staggered grid reproduce the halo mass function down to ${10}^{10.5}{M}_{\odot }$, mitigate the cusp–core and missing-satellite tensions, and remain consistent with cluster lensing constraints. On linear scales, the model predicts percent-level, scale-dependent deviations in the lensing convergence and matter power spectra, testable by Euclid space telescope, the Roman Space Telescope High Latitude Survey, and the CMB-S4 experiment. Full article

Net surface shortwave radiation (NSSR) is a key parameter in the Earth’s energy cycle, greatly affecting global water and heat balance. Currently, a comprehensive comparative analysis regarding the accuracy of different models remains severely lacking, and there is also a notable deficiency in the systematic exploration of seasonal radiative drivers. Therefore, we developed a machine learning-based seasonal NSSR estimation model. By integrating in-situ observational data with multi-source remote sensing datasets, we achieved precise quantification of radiative fluxes. This proposed model framework employed three cutting-edge algorithms, namely Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), to capture the non-linear interactions among radiative drivers across the four seasons. Through mechanistic sensitivity analysis, we quantified the impacts of key variables on NSSR prediction. The results unequivocally demonstrated that the RF algorithm demonstrated the best performance. Its seasonal R² were 0.95 (spring), 0.89 (summer), 0.95 (autumn), and 0.96 (winter). The Solar Zenith Angle (SZA) dominated in spring and winter; its absence reduced R² by 0.23 and raised RMSE by 20.66–26.42 W/m². Meteorological factors mattered most in summer; excluding them cut R² by 0.17 and hiked RMSE by 23.82 W/m². This study provides actionable insights for terrestrial radiation budget research. Full article

In this study, Ti-Co-Ce getter films were deposited via magnetron sputtering to investigate their activation mechanism—the thermal removal of surface passivation layers to restore gas sorption capability. The morphology before and after film activation was characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The oxygen content on the film surface before and after activation was measured using an energy-dispersive X-ray spectrometer (EDS), and gas desorption during activation was monitored with a quadrupole mass spectrometer (QMS). The combined results confirmed the absence of O₂ desorption during activation, suggesting oxygen migration into the film bulk. Crucially, in situ X-ray photoelectron spectroscopy (XPS) combined with controlled Ar⁺ ion sputtering depth profiling (0–30 nm) was employed to directly probe the chemical-state evolution within the thin film before and after thermal activation at 400 °C, thereby providing direct evidence of the activation dynamics. The data reveal that within the 0–10 nm near-surface region, a strong oxygen chemical potential gradient drives rapid oxide reduction and inward migration of lattice oxygen. At depths of 20–30 nm, moderate reduction coupled with oxygen enrichment induces phase separation, while around 30 nm, a dynamic equilibrium between oxygen inflow and outflow is established. These findings provide a theoretical basis for optimizing activation processes and guiding the development of low-temperature getter materials. This work is particularly relevant for MEMS, vacuum electronics, and other applications with stringent thermal budgets, expanding the design possibilities for heat-sensitive device integration. Full article

This study examines the hydro-sedimentological–radioecological controls governing the distribution of natural (K-40, Ra-226, Th-232) and anthropogenic (Cs-137) radionuclides in surface sediments of the western Black Sea shelf. Activity concentrations were determined by high-resolution gamma spectrometry, and radiological indices—including radium equivalent activity (Ra_eq), external hazard index (H_ex), and annual effective dose (AED)—were calculated to evaluate environmental safety. All indices remained well below internationally accepted thresholds, confirming the absence of radiological hazard in both coastal and offshore settings. Strong correlations between Ra-226 and Th-232 indicate dominant lithogenic control of natural radionuclides, whereas Cs-137 exhibits geochemical decoupling consistent with its behavior. A significant relationship between the fine-grained sediment fraction (<63 µm) and Cs-137 activity highlights the grain size effect, with offshore depositional zones acting as sediment-focusing areas where Cs-137 and excess Pb-210 co-accumulate under low-energy hydrodynamic conditions. Despite localized offshore enrichment, dose contribution analysis shows that natural radionuclides dominate the absorbed-dose budget, while Cs-137 contributes only marginally. Spatial predictive modeling using Artificial Neural Networks, validated under a Spatial Leave-One-Group-Out framework, yielded moderate generalization capacity (R² = 0.61 for Ra-226; R² = 0.41 for Cs-137), reflecting smoother spatial gradients of lithogenic radionuclides than heterogeneous radiocesium deposition. Furthermore, Machine Learning algorithms provided significant analytical value: a Random Forest (RF) model successfully classified environments (nearshore/shelf/depositional basin) based on distinct radionuclide signatures. At the same time, an optimized Artificial Neural Network (ANN-GA) enabled the nonlinear reconstruction of radiometric–granulometric patterns to identify local anomalies. The results show that radionuclide distributions are primarily structured by sediment provenance, grain size sorting, and hydrodynamic energy gradients rather than ongoing anthropogenic inputs. Full article

Turbulent structure and diffusion over different underlying surfaces are fundamental to understanding mass and momentum exchange in the atmospheric boundary layer. This study investigated these processes over six distinct surfaces—flat plate, sand, grass, small gravel, large gravel, and vegetation—through wind tunnel experiments combined with high-frequency velocity measurements. Quadrant analysis, Reynolds stress decomposition, and turbulence kinetic energy budget analysis were employed to elucidate the mechanisms driving variations in diffusion coefficients. The results reveal two distinct turbulence generation regimes: over rigid surfaces (flat plate, sand, gravel), turbulence is primarily generated by roughness elements, whereas over canopy surfaces (grass, vegetation), canopy-induced shear and wake dynamics dominate. Consequently, the vertical profiles of turbulent diffusion coefficients K_x and K_z exhibit markedly different patterns across surface types. For rigid surfaces, diffusion coefficients peak near the surface and decay monotonically with height. For canopy surfaces, diffusion coefficients reach their maximum at the canopy top, reflecting the dual influence of canopy-induced shear and energy dissipation within the canopy. These findings provide a mechanistic understanding of surface-induced variability in turbulent diffusion processes and offer quantitative parameterizations that can improve pollutant dispersion modeling over complex terrain. Full article