Search Results (237)

ZnNb₂O₆-based microwave dielectric ceramics have attracted considerable attention due to their high quality factor (Q × f) and low sintering temperature, but their application was limited by poor temperature stability with a large negative temperature coefficient of resonant frequency (τ_f). Herein, novel (1 − x)ZnNb₂O_6−xCa_0.5Sr_0.5TiO₃ (x = 0.05–0.125) composite ceramics were designed and fabricated. The used ZnNb₂O₆ and Ca_0.5Sr_0.5TiO₃ were synthesized through solid-phase reaction by using stoichiometric metal oxides or carbonates as the raw materials at 650 and 1100 °C, respectively. The composite ceramics were prepared by solid-state sintering, and the sintering parameters were optimized at 1175 °C for 4 h by visual high-temperature deformation analysis. A focus was paid on the temperature stability and compositional effects of Ca_0.5Sr_0.5TiO₃ of the obtained composited ceramics. As the Ca_0.5Sr_0.5TiO₃ content increases, the dielectric constant (ε_r) and Q × f gradually decrease, while τ_f shifts toward positive values. At x = 0.075, the composite ceramics sintered at 1175 °C for 4 h exhibit near-zero τ_f (−8.99 ppm/°C), coupled with ε_r = 23.23 and Q × f = 21,686 GHz. This study provides theoretical guide and material support for designing and fabricating various high-performance thermally stable microwave dielectric ceramics for 5G communication devices and future communication technologies. Full article

Molten salt, as a phase change heat storage material, can be used to mitigate the volatility of clean energy. Increasing the specific heat of molten salts can help to increase heat storage density and reduce costs. In this study, nanoparticles with different potentials were prepared and doped into Solar Salt (NaNO₃-KNO₃). The modification results of the nanoparticles were evaluated by transmission electron microscopy, energy dispersive X-ray spectroscopy and infrared spectroscopy, and the modification process was analyzed by density functional theory. The specific heat, thermal diffusion coefficient, melting point, latent heat of the composites and their variation mechanism were analyzed using synchronized thermal analyzer, laser flash analyzer and scanning electron microscope. It was found that acidification was able to modify the SiO₂ nanoparticles and that the higher the acidity, the more the negative charge of the nanoparticles was neutralised. A 25.8% decrease in zeta potential to −23.17 mV was observed for the nano-SiO₂ after treatment with HCl at pH 1, compared to the non-acidified sample. The microelectric field generated by the charged nanoparticles affects the thermophysical properties such as the specific heat of the molten salt-nanoparticle composites, with one of the samples having the largest specific heat (1.79 J/(g·K)) and thermal diffusion coefficient (0.94 mm²/s), which were increased by 13.3% and 14.6%, respectively, compared to the Solar Salt. This study attributes the alterations in thermophysical properties to the variation in ion separation distance induced by the charge on nanoparticles. Full article

Scientific planning and optimal development of multi-type power sources are critical prerequisites for supporting the robust evolution of emerging power systems. However, existing techno-economic evaluation methods often face challenges such as higher-order uncertainty and weight conflicts, making it difficult to provide reliable support for comparing and selecting power source schemes. To address this, this paper proposes an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on Fermatean Fuzzy Sets (FFS) for techno-economic evaluation of multi-type power sources. First, building on the traditional TOPSIS framework, we introduce Fermatean Fuzzy Sets to construct a FF Hybrid Weighted Distance (FFHWD) measure. This measure simultaneously captures the subjective importance of evaluation indicators and decision-makers’ risk preferences. Second, we design a subjective-objective coupled weighting strategy integrating Fuzzy Analytic Hierarchy Process (FAHP) and Entropy Weight Method (EWM) to achieve dynamic weight balancing, effectively mitigating biases caused by single weighting approaches. Finally, the FFHWD is integrated into the improved TOPSIS framework by defining FF positive and negative ideal solutions. The comprehensive closeness coefficients of each power source scheme are calculated to enable robust ranking and optimal selection of multi-type power source alternatives. Empirical analysis of five representative power generation technologies—thermal power, hydropower, wind power, photovoltaics (PV), and energy storage—demonstrates the following comprehensive techno-economic ranking: hydropower > photovoltaics > thermal power > wind power > energy storage. Hydropower achieves the highest closeness coefficient (−0.4198), whereas energy storage yields the lowest value (−2.8704), effectively illustrating their respective advantages and limitations within the evaluation framework. This research provides scientific decision-making support and methodological references for optimizing multi-type power source configurations and planning new power systems. Full article

Climate, which has important effects on pedogenesis, affects soils and its structure and mass transport through temperature and precipitation. Soil salinity or alkalinity, which is caused by the effects of climate, parent material, topography, and anthropogenic factors, is one of the important problems of arid and semi-arid regions and has negative effects on soil quality, requiring specific attention due to limited research. In this study, thermal properties were calculated using various classical and improved models in winter, spring, summer, and fall for alkaline and non-alkaline soil. For this purpose, temperature sensors were placed at depths of 0, 0.05, 0.10, 0.15, 0.20, and 0.40 m in non-alkaline and alkaline lands, and temperature data were collected from the sensors for 365 days. This study showed that (i) the thermal properties of both soils vary depending on the seasons of the year, and (ii) the thermal properties (thermal conductivity, thermal conductivity coefficient, thermal conductivity, attenuation depth, thermal conductivity coefficient, speed and length of the heat wave) were lower in the alkaline soil. These results could be used for consideration of climate change mitigation in similar semi-arid zones. Full article

Earth–Air Heat Exchangers (EAHEs) exploit stable subsurface temperatures to pre-condition supply air. To address limitations of conventional systems in hot–arid climates, this study investigates the performance of a hybrid EAHE prototype combining a serpentine subsurface pipe with a buried water tank. Installed in a residential building in Lichana, Biskra (Algeria), the system was designed to enhance land compactness, thermal stability, and soil–water heat harvesting. Experimental monitoring was conducted across 13 intervals strategically spanning seasonal transitions and extremes and was complemented by calibrated numerical simulations. From over 30,000 data points, outlet trajectories, thermal efficiency, Coefficient of Performance (COP), and energy savings were assessed against a straight-pipe baseline. Results showed that the hybrid EAHE delivered smoother outlet profiles under moderate gradients while the baseline achieved larger instantaneous ΔT. Thermal efficiencies exceeded 90% during high-gradient episodes and averaged above 70% annually. COP values scaled with the inlet–soil gradient, ranging from 1.5 to 4.0. Cumulative recovered energy reached 80.6 kWh (3.92 kWh/day), while the heat pump electricity referred to a temperature-dependent ASHP totaled 34.59 kWh (1.40 kWh/day). Accounting for the EAHE fan yields a net saving of 25.46 kWh across the campaign, only one interval (5) was net-negative, underscoring the value of bypass/fan shut-off under weak gradients. Overall, the hybrid EAHE emerges as a footprint-efficient option for arid housing, provided operation is dynamically controlled. Future work will focus on controlling logic and soil–moisture interactions to maximize net performance. Full article

Mechanical draft cooling towers are among the most critical water-consuming equipment in industries such as thermal power and petrochemicals. Strengthening their water usage performance is therefore crucial for alleviating China’s water resource pressure. To this end, this study employs the makeup water rate indicator to analyze the core factors influencing water-use efficiency in mechanical draft cooling towers, utilizing Spearman’s rank correlation coefficient analysis and partial least squares regression (PLSR) methods. The results reveal that ambient temperature and inlet pressure exhibit significant negative correlations with the makeup water rate, while blowdown pressure and concentration multiple show significant positive correlations. Gray correlation analysis indicates that blowdown pressure (correlation degree: 0.923) and concentration multiple (correlation degree: 0.897) are the key driving factors. The PLSR-based prediction model for the makeup water rate demonstrates a strong goodness of fit, with explanatory power exceeding 80%. This research provides a modeling foundation for optimizing the operational control of mechanical draft cooling towers, thereby promoting sustainable management of industrial water use. Full article

The significant negative thermal expansion (NTE) that occurs in La(Fe,Si)₁₃-based alloys during magnetic transition make them promising to combine with positive thermal expansion (PTE) materials to obtain near-zero thermal expansion (NZTE) materials. However, La(Fe,Si)₁₃-based alloys with NTE generally show intrinsic poor mechanical properties. Here, thermal expansion properties are optimized by adding Ag in La_0.6Ce_0.4(Fe_0.91Co_0.09)_11.9Si_1.1 to form a multi-phase structure exhibiting enhanced compressive strength. Through spark plasma sintering (SPS) and annealing, the samples consisted of α-Fe(Co,Si), NaZn₁₃-type, and LaAg₂ phases. When the annealing temperature reaches 1323 K, LaAg₂ disappears and is replaced by La₂O₃. The LaAg₂ phase and α-Fe(Co,Si) phase contribute as PTE materials to compensate for the NTE of the NaZn₁₃-type phase. Near-zero thermal expansion was achieved in the temperature range of 240–294 K, with a coefficient of thermal expansion (CTE) of 3.5 ppm/K at a 9.581 at.% Ag content. Benefiting from the uniform phase distribution and coordinated deformation, the samples obtained high mechanical strengths, with fracture stresses of 1481.1 MPa for the 15 wt.% Ag sample. This work provides a promising route for high-strength and near-zero thermal expansion Ag/La(Fe,Si)₁₃ composites. Full article

Reactive co-sputtering was applied to deposit TaN-(Ag,Cu) nanocomposite films on Si and tool steels. Prior to post-deposition annealing, the films were deposited with TaN cap (diffusion barrier) layers in various thicknesses in order to slow down the nucleation and growth of emerging Ag and Cu particles. The thickness of the cap layers was set at 5, 10, 20, or 50 nm. The films were then annealed using Rapid Thermal Annealing (RTA) at 400 °C to induce the nucleation and growth of Ag and Cu nanoparticles. These films’ surface morphologies and structures were examined. The samples were tested for their anti-wear and antibacterial behaviors against Gram-positive S. aureus and Gram-negative E. coli, with a variation in cap layer thickness. It is found that, through the application of TaN cap layers, the out-diffusion of Ag and Cu atoms may be slowed down. The surface concentrations of Ag and Cu might decrease from 35 at.% and 17 at.% to 18 at.% and 6 at.%, respectively, when the cap layer thickness increases to 50 nm (after being annealed for 12 min). The diffusion mechanism is proposed to explain the formation of nanoparticles on the surface through boundary diffusion. Antibacterial behaviors against both bacteria, as well as tribological properties, could still be effective but become less significant with an increase in the cap layer thickness. The antibacterial efficiency after 3 h testing decreased from 99% to 5% and 8% against E. coli and S. aureus, respectively. At 12 h, all the samples reached >99% antibacterial efficiency, despite the variation in cap thickness. For sliding wear, the wear rate was doubled when the cap thickness increased to 50 nm (when the normal load was 1 N). On the other hand, the difference was minor when the normal load was changed to 5 N. The sliding lifetime of the samples was studied using a tribometer. The total lifetime may increase with an increase in the cap thickness. The wear is found to be due to the oxidation of Ag and Cu nanoparticles, which results in the loss of low coefficient behaviors. Full article

Anxiety disorders represent a significant global health challenge, yet a substantial treatment gap persists, motivating the development of scalable digital health solutions. This study investigates the potential of integrating passive physiological data from consumer wearable devices with subjective self-reported surveys to predict state–trait anxiety. Leveraging the multi-modal, longitudinal LifeSnaps dataset, which captured “in the wild” data from 71 participants over four months, this research develops and evaluates a machine learning framework for this purpose. The methodology meticulously details a reproducible data curation pipeline, including participant-specific time zone harmonization, validated survey scoring, and comprehensive feature engineering from Fitbit Sense physiological data. A suite of machine learning models was trained to classify the presence of anxiety, defined by the State–Trait Anxiety Inventory (S-STAI). The CatBoost ensemble model achieved an accuracy of 77.6%, with high sensitivity (92.9%) but more modest specificity (48.9%). The positive predictive value (77.3%) and negative predictive value (78.6%) indicate balanced predictive utility across classes. The model obtained an F1-score of 84.3%, a Matthews correlation coefficient of 0.483, and an AUC of 0.709, suggesting good detection of anxious cases but more limited ability to correctly identify non-anxious cases. Post hoc explainability approaches (local and global) reveal that key predictors of state anxiety include measures of cardio-respiratory fitness (VO₂Max), calorie expenditure, duration of light activity, resting heart rate, thermal regulation and age. While additional sensitivity analysis and conformal prediction methods reveal that the size of the datasets contributes to overfitting, the features and the proposed approach is generally conducive for reasonable anxiety prediction. These findings underscore the use of machine learning and ubiquitous sensing modalities for a more holistic and accurate digital phenotyping of state anxiety. Full article

As avionics advance, heat dissipation becomes more challenging. Microencapsulated phase change material slurry (MPCMS), with its latent heat transfer properties, offers a potential solution. However, the low thermal conductivity of microencapsulated phase change material (MPCM) limits heat transfer rates, and most studies focus on improving conductivity, with little attention given to convective enhancement. This study prepared MPCMS with an MPCM mass fraction (W_m) of 10% and 20%, investigating melting heat transfer under mechanical stirring at 0–800 RPM and heat fluxes of 8.5–17.0 kW/m². Stirring significantly alters MPCMS heat transfer behavior. As rotational speed increases, both wall-to-slurry and internal temperature differences decrease. Stirring extends the time at which the heating wall temperature (T_w) stays below a threshold. For example, at W_m = 10% MPCM and 8.50 kW/m², increasing speed from 0 to 800 RPM raises the holding time below 70 °C by 169.6%. The effect of MPCM mass fraction on heat transfer under stirring is complex: at 0 RPM, 0% > 10% > 20%; at 400 RPM, 10% > 0% > 20%; and at 800 RPM, 10% > 20% > 0%. This is because as W_m increases, the latent heat and volume expansion coefficients of MPCMS rise, promoting heat transfer, while viscosity and thermal conductivity decrease, hindering it. At 0 RPM, the net effect is negative even at W_m = 10%. Stirring enhances internal convection and significantly improves heat transfer. At 400 RPM, heat transfer is positive at W_m = 10% but still negative at W_m = 20%. At 800 RPM, both W_m levels show positive effects, with slightly better performance at W_m = 10%. In addition, at the same heat flux, higher speeds maintain T_w below a threshold longer. Overall, stirring improves MPCMS cooling performance, offering an effective means of convective enhancement for avionics thermal management. Full article

A liquid-sealed single-mode–no-core–single-mode (SNS) structure fiber temperature sensor based on polyvinyl alcohol (PVA) partial replacement coating is proposed. Using a liquid-sealed glass capillary structure, the PVA solution is introduced into the SNS structure and avoids its influence by environmental humidity. Temperature can be obtained by measuring the shift of the multimode interference spectrum, which is affected by the thermal optical effect of the PVA solution. Through theoretical simulation of the sensor, the optimal NCF fiber length and coating stripped length are obtained by comprehensively considering the transmitted loss and output spectrum signal-to-noise ratio (SNR). The optimal PVA solution concentration is selected by measuring the thermo-optic coefficient (TOC) and refractive index (RI). Based on the theoretical optimization results, a PVA solution-coated SNS fiber optic temperature sensor is experimentally fabricated, and temperature-sensing characteristics are measured within −3.6 to 73.2 °C. The experimental results show that the sensor has a high sensitivity (nm/°C, maximum is 21.713 nm/°C) and has a resolution of 10⁻³ °C. ${\lambda }_{dip}$ has a stable negative linear relationship with temperature, and the correlation coefficient of the fitting curve exceeds 95%. The temperature cycling experiment and long-term stability test show that the temperature sensor has good repeatability and stability. The experimental results also show the nonlinear relationship between the temperature measurement range and sensitivity, clarify the important factors affecting the response performance of fiber temperature sensors, and provide important reference values for optical fiber temperature sensors. Full article

In this study, we consider a fractional-order extension of the Jeffreys equation (also known as the dual-phase-lag equation) by introducing the Reimann–Liouville fractional integral, of order $0<\nu <1$, to the Jeffreys constitutive law, where for $\nu =1$ it corresponds to the conventional Jeffreys equation. The kinetical behaviors of the fractional equation such as non-negativity of the propagator, mean-squared displacement, and the temporal amplitude are investigated. The fractional Langevin equation, or the fractional damped oscillator, is a special case of the considered integrodifferential equation governing the temporal amplitude. When $\nu =0$ and $\nu =1$, the fractional differential equation governing the temporal amplitude has the mathematical structure of the classical linear damped oscillator with different coefficients. The existence of a real solution for the new temporal amplitude is proven by deriving this solution using the complex integration method. Two forms of conditional closed-form solutions for the temporal amplitude are derived in terms of the Mittag–Leffler function. It is found that the proposed generalized fractional damped oscillator equation results in underdamped oscillations in the case of $0<\nu <1$, under certain constraints derived from the non-fractional case. Although the nonfractional case has the form of classical linear damped oscillator, it is not necessary for its solution to have the three common types of oscillations (overdamped, underdamped, and critical damped), unless a certain condition is met on the coefficients. The obtained results could be helpful for analyzing thermal wave behavior in fractals, heterogeneous materials, or porous media since the fractional-order derivatives are related to the porosity of media. Full article

The effects of HfC content on the ablation resistance of W-HfC composites were systematically studied. The oxy-acetylene flame ablation test was conducted at 2800 °C. Post-ablation samples were characterized via XRD, section morphology, and EDS. W-10HfC showed the best ablation resistance, with a linear ablation rate of just 0.0175 mm/s. This enhanced performance is attributed to the formation of a dense HfW₂O₈ oxide layer with negative thermal expansion properties, reinforced by uniformly dispersed blocky HfO₂ particles. However, excessive HfC content induces a stratified oxide structure. The thermal expansion coefficient mismatch between HfW₂O₈ and HfO₂ causes microcrack formation, ultimately degrading ablation resistance. These findings establish critical guidelines for HfC content optimization in W-HfC composite design. Full article

This script discusses a qualitative analysis of the characteristics of coals burned in the combustion chambers of thermal power plants in Serbia. The study includes the following coal characteristics (mass fraction): moisture ($W\%$) ash ($A\%$), combustible materials ($V_g\%$) and lower heating power ($H_d(\mathrm{kJ}·{\mathrm{kg}}^{-1})$). Based on the collected data, statistical modeling was conducted, which included the calculation of the mean value ($\overline{X}$), standard deviation ($S$), and coefficient of variation ($C_v$) for each of the listed characteristics. The results indicate that all analyzed characteristics exhibit significant deviations from their mean values, as confirmed by the high values of the coefficient of variation (moisture 70.20%, ash 62.21%, combustible matter 43.33%, and lower heating value 44.10%). Large mass fraction deviations ($W$), ($A$), $(V_g)$ and $H_d$ around the mean value may negatively impact the operation of boiler plants and electrostatic precipitators of thermal power plants in Serbia, where the considered coals are burned. Large oscillations of ash (62.21%) around the mean value (17.00%) suggests that it is not feasible to implement dry flue-gas desulfurization (FGD) processes, due to the additional amount of ash. Distribution testing confirmed that all examined parameters can be reasonably approximated by a normal distribution. Subsequent statistical modeling using Student’s t-test at a 0.05 significance level demonstrated strong agreement between the coal characteristics from Serbia and corresponding parameters of coals from Bosnia and Herzegovina and Montenegro. The obtained results enable reliable quality comparison of coals, particularly lignites, across different basins. These findings establish a solid foundation for further energy and technological valorization of these fuel resources. Full article

It has always been a research topic for some meteorologists to design a new and reasonable calculation scheme of the intensity of the Tibetan Plateau (TP) summer monsoon (TPSM). Existing indices are defined based on dynamic factors. However, the intensity of the TPSM can also be influenced by thermal factors. We therefore propose defining a TPMI in terms of horizontal temperature advection within the main body of the TP. This provides a new index that directly quantifies the extent to which the thermal forcing in the TP region regulates the monsoon system. The new index emphasizes the importance of the atmospheric asymmetry structure in measuring TPSM strength, represents the variability of the TPSM circulation system, effectively reflects the meteorological elements, and accurately represents the climate variation. Tropospheric temperature (TT) and TPSM are linked by the new index. These significant centers of correlation are characterized by alternating positive and negative phases along the Eastern European Plain, across the Turan Plain, and into southwestern and northeastern China. The correlation coefficients are found to be significantly out of phase between high and low altitudes in the vertical direction. This research broadens our minds and helps us to develop a new approach to measuring TPSM strength. It can also predict extreme weather events in advance based on TPMI changes, providing a scientific basis for disaster warnings and the management of agriculture and water resources. Full article