Search Results (980)

Today, several conventional wastes (fly ash, ground granulated blast furnace slags, etc.) are used as valid precursors for geopolymer synthesis. However, there are several new wastes that can be studied to replace geopolymer precursors. This study investigates the behavior of four industrial wastes—suction dust (SW1), red mud (SW2), electro-filter dust (SW3), and extraction sludge (SW4)—as 20 wt.% substitutes for metakaolin in geopolymer synthesis. The objective is to assess how their incorporation before alkali activation affects the structural, thermal, mechanical, chemical, and antimicrobial properties of the resulting geopolymers, namely GPSW1–4. FT-IR analysis confirmed successful geopolymerization in all samples (the main Si-O-T band underwent redshift, confirming Al incorporation in geopolymer structures after alkaline activation), and stability tests revealed that none of the GPSW1–4 samples disintegrated under thermal or water stress. However, GPSW3 showed an increase in efflorescence phenomena after these tests. Moreover, compressive strength was reduced across all waste-containing geopolymers (from 22.0 MPa for GP to 12.6 MPa for GPSW4 and values lower than 8.1 MPa for GPSW1–3), while leaching tests showed that GPSW1 and GPSW4 released antimony (127.5 and 0.128 ppm, respectively) above the legal limits for landfill disposal (0.07 ppm). Thermal analysis indicated that waste composition influenced dehydration and decomposition behavior. The antimicrobial activity of waste-based geopolymers was observed against E. coli, while E. faecalis showed stronger resistance. Overall, considering leaching properties, SW2 and SW3 were properly entrapped in the GP structure, but showed lower mechanical properties. However, their antimicrobial activity could be useful for surface coating applications. Regarding GPSW1 and GPSW4, the former needs some treatment before incorporation, since Sb is not stable, while the latter, showing a good compressive strength, higher thermal stability, and leaching Sb value not far from the legal limit, could be used for the inner reinforcement of building materials. Full article

The design of the buckling configuration for a rolling soft robot has a significant effect on its rolling performance, but a thorough analysis remains lacking for many soft robot buckling configurations because of the difficulty of analyzing the buckling problem. This work comprehensively analyzes the static buckling morphology of two nested elastic rings under gravity based on a theoretical model using the minimum potential energy principle. Two nested rings present a tank-track-like buckling morphology under gravity, which depends on the length ratio, the bending stiffness ratio, and the gravity ratio of the inner ring to the outer ring. Increases in these three ratios lead to a lower tank-track-like buckling structure with an increased ground contact length and a reduced gravity moment on the slope. The tank-track-like buckling structures predicted using the theory agree well with Finite Element Method (FEM) simulations and experimental results. This work provides design guidance on achieving the maximum slope stability and the required robot configuration by tuning the geometrical and material parameters of rolling soft robots. Full article

Heated tobacco products (HTPs) frequently induce user discomfort due to high mainstream smoke temperatures. To address this challenge and improve the inhalation experience, this experiment designed and prepared a cage-shaped braided tube as the cooling section of the filter for HTPs. The thermal, cooling, suction resistance, and smoke composition properties of the filter were tested and analyzed. Thermal analysis (DSC/TG) revealed a 116.53 J/g increase in endothermic enthalpy for PEG-impregnated samples, accompanied by maintained thermal stability (decomposition temperature ≈ approximately 350 °C). The 0.8 wt% Carbon Nanotube (CNT) composite achieved exceptional thermal conductivity (0.597 W/m·K), representing a 521% improvement over untreated controls. The braided tube optimal performance (3 mm inner diameter, 30% PEG/0.8% CNT) reduced the highest smoke temperature to 47.8 °C while maintaining acceptable suction resistance (68.5 Pa, 56.4% reduction vs. commercial IQOS filters). GC-MS analysis confirmed negligible alterations in smoke composition (p > 0.05). This innovation offers an effective thermal management solution that does not compromise sensory experiences. Full article

To ensure the mechanical performance of gas turbine hollow blades under high-temperature conditions, the application of aluminide high-temperature protective coatings on the inner gas flow channel surfaces of hollow blades via chemical vapor deposition (CVD) has become a critical measure for enhancing blade safety. This study employs computational fluid dynamics (CFD) to investigate the flow field within CVD reactors and the influences of deposition processes on the chemical reaction rates at sample surfaces, thereby guiding the optimization of CVD reactor design and deposition parameters. Three distinct CVD reactor configurations are examined to analyze the flow characteristics of precursor gases and the internal flow field distributions. The results demonstrate that Model A, featuring a bottom-positioned outlet and an extended inlet, exhibits a larger stable deposition zone with more uniform flow velocities near the sample surface, thereby indicating the formation of higher-quality aluminide coatings. Based on Model A, CFD simulations are conducted to evaluate the effects of process parameters, including inflow velocity, pressure, and temperature, on aluminide coating deposition. The results show that the surface chemical reaction rate increases with inflow velocity (0.0065–6.5 m/s), but the relative change rate (ratio of reaction rate to flow rate) shows a declining trend. Temperature variations (653–1453 K) induce a trapezoidal-shaped trend in deposition rates: an initial increase (653–1053 K), followed by stabilization (1053–1303 K), and a subsequent decline (>1303 K). The underlying mechanisms for this trend are discussed. Pressure variations (0.5–2 atm) reveal that both excessively low and high pressures reduce surface reaction rates, with optimal performance observed near 1 atm. This study provides a methodology and insights for optimizing CVD reactor designs and process parameters to enhance aluminide coating quality on turbine blades. Full article

Clustering algorithms based on non-negative matrix factorization (NMF) have garnered significant attention in data mining due to their strong interpretability and computational simplicity. However, traditional NMF often struggles to effectively capture and preserve topological structure information between data during low-dimensional representation. Therefore, this paper proposes an autoencoder-like sparse non-negative matrix factorization with structure relationship preservation (ASNMF-SRP). Firstly, drawing on the principle of autoencoders, a “decoder-encoder” co-optimization matrix factorization framework is constructed to enhance the factorization stability and representation capability of the coefficient matrix. Then, a preference-adjusted random walk strategy is introduced to capture higher-order neighborhood relationships between samples, encoding multi-order topological structure information of the data through an optimal graph regularization term. Simultaneously, to mitigate the impact of noise and outliers, the $l_{2,1}$-norm is used to constrain the feature correlation between low-dimensional representations and the original data, preserving feature relationships between data, and a sparse constraint is imposed on the coefficient matrix via the inner product. Finally, clustering experiments conducted on 8 public datasets demonstrate that ASNMF-SRP consistently exhibits favorable clustering performance. Full article

This paper addresses stability issues in modern power grids arising from extensive integration of power electronic converters, which introduce complex multi-time-scale interactions. A symbolic simplification method is proposed to accurately model grid-connected converter dynamics, significantly reducing computational complexity through transfer function approximations and yielding efficient reduced-order models. An impedance-based approach utilizing impedance ratio (IR) is developed for stability assessment under active-reactive (PQ) and active power-AC voltage (PV) control strategies. The impacts of Phase-Locked Loop (PLL) and proportional-integral (PI) controllers on system stability are analysed, with a particular focus on quantifying remote converter interactions and delineating stability boundaries across varying network strengths and configurations. Furthermore, time-scale separation effectively simplifies Multi-Voltage Source Converter (MVSC) systems by minimizing inner-loop dynamics. Validation is conducted through frequency response evaluations, IR characterizations, and eigenvalue analyses, demonstrating enhanced accuracy, particularly with the application of lead–lag compensators within the critical 50–250 Hz frequency band. Time-domain simulations further illustrate the adaptability of the proposed models and reduction methodology, providing an effective and computationally efficient tool for stability assessment in converter-dominated power networks. Full article

I show here that if we construct D-branes not in the form of infinite superpositions of string modes, in order to satisfy the technical condition of coherence by means of eigenstates of annihilation operators, but instead insist on an approximate but much more physical and practical definition based on phase coherence, we obtain finite (and hence realistic) superpositions of string modes that would form realistic D-branes that would encode (at least as a semiclassical approximation) various quantum properties. Re-deriving the AdS/CFT duality by starting in the pre-Maldacena limit from such realistic D-branes would lead to quantum properties on the AdS side of the duality. Causal structures can be modified in various many-particle systems, including strings, D-branes, photons, or spins; however, there is a distinction between the emergence of an effective causal structure in the inner degrees of freedom of a material, in the form of a correlation-generated effective metric, for example, in a spin liquid system, and the emergence of a causal structure in an open propagating system by using classical light. I will show how an Uhlmann gauge construction would add stability to a modified causal structure that would retain the shape of a closed causal loop. Various other ideas related to the quantum origin of the string length are also discussed and an analogy of the emergence of string length from quantum correlations with the emergence of wavelength of an electromagnetic wave from coherence conditions of photon modes is presented. Full article

Soil carbon constitutes the largest terrestrial carbon reservoir, with inorganic forms (SIC) contributing an estimated 20–40% of the global total. Despite its relevance to arid-region carbon cycling and stabilization, SIC remains less studied than soil organic carbon (SOC). This study quantified surface SIC content (0–20 cm) and its environmental drivers across the Weibei Loess region using 3261 soil samples collected between 2008 and 2010. A combination of Random Forest (RF) modeling and optimal parameter geodetector (OPGD) analysis was employed to assess spatial heterogeneity and identify key environmental controls. SIC content ranged from 0.10 to 3.56 g kg⁻¹ (mean = 1.23 ± 0.41 g kg⁻¹), generally lower than reported values in the Tibetan Plateau and Inner Mongolia. Higher concentrations were observed in central areas, with lower values toward the periphery. While mean annual temperature (MAT) and precipitation (MAP) remained key climatic correlates, shortwave radiation (srad) emerged as the strongest control on SIC across the region, exhibiting a significant positive association with its accumulation. Notably, its interaction with wind speed (vs) further amplified this effect, highlighting the synergistic role of radiation and near-surface turbulence in regulating inorganic carbon retention in surface soils. Collectively, these variables explained ~56% of SIC spatial variation. Favorable conditions for SIC accumulation were identified within specific environmental thresholds: srad (171–172 W/m²), MAP (546–587 mm), MAT (10.2–11.5 °C), and vs (1.90–1.96 m/s). These findings offer a quantitative basis for understanding SIC patterns in loess-derived soils and support the development of region-specific strategies for carbon regulation under changing climatic conditions. Full article

To address compacted soils with high power consumption and waterlogging risks in rice–rapeseed rotation areas of the Yangtze River, this study designed a ditching machine combining a stepped cutter head and trapezoidal cleaning blade, where the mechanical synergy between components minimizes energy loss during soil-cutting and -throwing processes. We mathematically modeled soil cutting–throwing dynamics and blade traction forces, integrating soil rheological properties to refine parameter interactions. Discrete Element Method (DEM) simulations and single-factor experiments analyzed impacts of the inner/outer blade widths, blade group distance, and blade opening on power consumption. Results indicated that increasing the inner/outer blade widths (200–300 mm) by expanding the direct cutting area significantly reduced the cutter torque by 32% and traction resistance by 48.6% from reduced soil-blockage drag; larger blade group distance (0–300 mm) initially decreased but later increased power consumption due to soil backflow interference, with peak efficiency at 200 mm spacing; the optimal blade opening (586 mm) minimized the soil accumulation-induced power loss, validated by DEM trajectory analysis showing continuous soil flow. Box–Behnken experiments and genetic algorithm optimization determined the optimal parameters: inner blade width: 200 mm; outer blade width: 300 mm; blade group distance: 200 mm; and blade opening: 586 mm, yielding a simulated power consumption of 27.07 kW. Field tests under typical 18.7% soil moisture conditions confirmed a <10% error between simulated and actual power consumption (28.73 kW), with a 17.3 ± 0.5% reduction versus controls. Stability coefficients for the ditch depth, top/bottom widths exceeded 90%, and the backfill rate was 4.5 ± 0.3%, ensuring effective drainage for rapeseed cultivation. This provides practical theoretical and technical support for efficient ditching equipment in rice–rapeseed rotations, enabling resource-saving design for clay loam soils. Full article

In the casting and rolling production process, surface longitudinal cracks are a typical casting defect. Tracing the causes of longitudinal cracks online and controlling the key parameters leading to their formation in a timely manner can enhance the stability of casting and rolling production. To this end, the influencing factors of longitudinal cracks were analyzed, a data integration storage platform was constructed, and a tracing model was established using empirical rule analysis, statistical analysis, and intelligent analysis methods. During the initial production phase of a casting machine, longitudinal cracks occurred frequently. The tracing results using the LightGBM-SHAP method showed that the relative influence of the narrow left wide inner heat flow ratio of the mold was significant, followed by the heat flow difference on the wide symmetrical face of the mold and the superheat of the molten steel, with weights of 0.135, 0.066, and 0.048, respectively. Based on the tracing results, we implemented online emergency measures. By controlling the cooling intensity of the mold, we effectively reduced the recurrence rate of longitudinal cracks. Root cause analysis revealed that the total hardness of the mold-cooling water exceeded the standard, reaching 24 mg/L, which caused scaling on the mold copper plates and uneven cooling, leading to the frequent occurrence of longitudinal cracks. After strictly controlling the water quality, the issue of longitudinal cracks was brought under control. The online application of the tracing method for the causes of longitudinal cracks has effectively improved efficiency in resolving longitudinal crack problems. Full article

Degradable fluorescent sensors present a promising portable approach for heavy metal ion detection, aiming to prevent secondary environmental pollution. Additionally, the excessive intake of ferric ions (Fe³⁺), an essential trace element for human health, poses critical health risks that urgently require effective monitoring. In this study, we developed a thermally degradable fluorescent hydrogel sensor (Eu-CDs@DPPG) based on europium-doped carbon dots (Eu-CDs). The Eu-CDs, synthesized via a hydrothermal method, exhibited selective fluorescence quenching by Fe³⁺ through the inner filter effect (IFE). Embedding Eu-CDs into the hydrogel significantly enhanced their stability and dispersibility in aqueous environments, effectively resolving issues related to aggregation and matrix interference in traditional sensing methods. The developed sensor demonstrated a broad linear detection range (0–2.5 µM), an extremely low detection limit (1.25 nM), and rapid response (<40 s). Furthermore, a smartphone-assisted LAB color analysis allowed portable, visual quantification of Fe³⁺ with a practical LOD of 6.588 nM. Importantly, the hydrogel was thermally degradable at 80 °C, thus minimizing environmental impact. The sensor’s practical applicability was validated by accurately detecting Fe³⁺ in spinach and human urine samples, achieving recoveries of 98.7–108.0% with low relative standard deviations. This work provides an efficient, portable, and sustainable sensing platform that overcomes the limitations inherent in conventional analytical methods. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

For the high-voltage AC port of power electronic transformer (HVAC-PET) with three-phase independent DC buses on the low-voltage side, a decoupling control strategy, concerning the influence of grid voltage imbalance, three-phase active-load imbalance, and high-order harmonic distortion, is proposed in this paper to simultaneously realize the functions of active power control, reactive power compensation, and active power filtering. In the outer power control loop, according to the distribution rule of decoupled average active power components in three phases, stability control for the sum of cluster average active power flows is realized by injecting positive-sequence active current, so as to control the average cluster voltage (i.e., the average of all the DC-link capacitor voltages), and by injecting negative-sequence current, the cluster average active power flows can be controlled individually to balance the three cluster voltages (i.e., the average of the DC-link capacitor voltages in each cluster). The negative-sequence reactive power component is considered to realize the reactive power compensation. In the inner current control loop, the fundamental and high-order harmonic components are uniformly controlled in the positive-sequence dq frame using the PI + VPIs (vector proportional integral) controller, and the harmonic filtering function is realized while the fundamental positive-sequence current is adjusted. Experiments performed on the 380 V/50 kVA laboratory HVAC-PET verify the effectiveness of the proposed control strategy. Full article

The unique characteristics of desert vegetation, such as different leaf morphology, discrete canopy structures, sparse and uneven distribution, etc., pose significant challenges for remote sensing-based estimation of fractional vegetation cover (FVC). The Unmanned Aerial Vehicle (UAV) system can accurately distinguish vegetation patches, extract weak vegetation signals, and navigate through complex terrain, making it suitable for applications in small-scale FVC extraction. In this study, we selected the floodplain fan with Caragana korshinskii Kom as the constructive species in Hatengtaohai National Nature Reserve, Bayannur, Inner Mongolia, China, as our study area. We investigated the remote sensing extraction method of desert sparse vegetation cover by placing samples across three gradients: the top, middle, and edge of the fan. We then acquired UAV multispectral images; evaluated the applicability of various vegetation indices (VIs) using methods such as supervised classification, linear regression models, and machine learning; and explored the feasibility and stability of multiple machine learning models in this region. Our results indicate the following: (1) We discovered that the multispectral vegetation index is superior to the visible vegetation index and more suitable for FVC extraction in vegetation-sparse desert regions. (2) By comparing five machine learning regression models, it was found that the XGBoost and KNN models exhibited relatively lower estimation performance in the study area. The spatial distribution of plots appeared to influence the stability of the SVM model when estimating fractional vegetation cover (FVC). In contrast, the RF and LASSO models demonstrated robust stability across both training and testing datasets. Notably, the RF model achieved the best inversion performance (R² = 0.876, RMSE = 0.020, MAE = 0.016), indicating that RF is one of the most suitable models for retrieving FVC in naturally sparse desert vegetation. This study provides a valuable contribution to the limited existing research on remote sensing-based estimation of FVC and characterization of spatial heterogeneity in small-scale desert sparse vegetation ecosystems dominated by a single species. Full article

Carbon dots (CDs) have attracted much attention as new types of luminescent carbon nanomaterials in recent years because of their tunable fluorescence, good biocompatibility, high stability, and low cost. In this review, the classification of CDs is overviewed based on their differences in structure. Subsequently, the latest research progress of CDs in fluorescence sensing is systematically summarized and various sensing principles are elucidated in detail, including fluorescence resonance energy transfer, aggregation-induced emission, aggregation-caused quenching, electron transfer, and the inner filter effect. Finally, the challenges and future direction of CD fluorescent probes are discussed in detail. The purpose of this review is to stimulate the design of advanced CD fluorescent probes and achieve the accurate and reliable measurement of analytes in complex samples. Full article