Search Results (669)

The incorporation of phase change material (PCM) can enhance wall thermal performance and indoor thermal comfort, but practical applications still face challenges related to high costs and potential leakage issues. In this study, a novel dual-biomass-based shape-stabilized PCM (Bio-SSPCM) was proposed, wherein waste cooking fat and waste reed straw were, respectively, incorporated as the PCM substance and supporting material. The waste fat (lard) consisted of both saturated and unsaturated fatty acid glycerides, exhibiting a melting point about 21.2–41.1 °C and a melting enthalpy value of 40 J/g. Reed straw was carbonized to form a sustainable porous biochar supporting matrix, which was used for the vacuum adsorption of waste fat. The results demonstrate that the as-prepared dual-Bio-SSPCM exhibited excellent thermal performance, characterized by a latent heat capacity of 25.4 J/g. With the addition of 4 wt% of expanded graphite (EG), the thermal conductivity of the composite PCM reached 1.132 W/(m·K), which was 5.4 times higher than that of the primary lard. The thermal properties of the Bio-SSPCM were characterized using an analog T-history method. The results demonstrated that the dual-Bio-SSPCM exhibited exceptional and rapid heat storage and exothermic capabilities. The dual-Bio-SSPCM, prepared from waste cooking fat and reed straw, can be considered as environmentally friendly construction material for energy storage in line with the principles of the circular economy. Full article

Climate change has accelerated the retreat of Andean glaciers, with significant recent losses in the tropical Andes. This study evaluates the extinction of the Carihuairazo volcano glacier (Ecuador), quantifying its area from 1312.5 m² in September 2023 to 101.2 m² in January 2024, its thickness (from 2.5 m to 0.71 m), and its volume (from 2638.85 m³ to 457.18 m³), before its complete deglaciation in February 2024; this rapid melting and its small size classify it as a glacierette. Multivariate analyses (PCA and biclustering) were performed to correlate climatic variables (temperature, solar radiation, precipitation, relative humidity, vapor pressure, and wind) with glacier surface and thickness. The PCA explained 70.26% of the total variance, with Axis 1 (28.01%) associated with extreme thermal conditions (temperatures up to 8.18 °C and radiation up to 16.14 kJ m⁻² day⁻¹), which probably drove its disappearance. Likewise, Axis 2 (21.56%) was related to favorable hydric conditions (precipitation between 39 and 94 mm) during the initial phase of glacier monitoring. Biclustering identified three groups of variables: Group 1 (temperature, solar radiation, and vapor pressure) contributed most to deglaciation; Group 2 (precipitation, humidity) apparently benefited initial stability; and Group 3 (wind) played a secondary role. These results, validated through in situ measurements, provide scientific evidence of the disappearance of the Carihuairazo volcano glacier by February 2024. They also corroborate earlier projections that anticipated its extinction by the middle of this decade. The early disappearance of this glacier highlights the vulnerability of small tropical Andean glaciers and underscores the urgent need for water security strategies focused on management, adaptation, and resilience. Full article

Hepatitis E virus (HEV) is a leading cause of acute viral hepatitis and is primarily transmitted via contaminated water and food. Groundwater may also serve as a potential vector for HEV transmission. This study aimed to optimize real-time polymerase chain reaction (rtPCR) for the detection of HEV, employing both TaqMan probe- and SYBR Green-based methods. A total of 12 primer sets for the TaqMan probe-based method and 41 primer sets for the SYBR Green-based method were evaluated in order to identify the optimal combinations. Primer sets #4 (TaqMan probe-based) and #21 (SYBR Green-based) demonstrated the highest sensitivity and specificity, successfully detecting HEV in artificially spiked samples at 1 fg/μL. The TaqMan probe-based method facilitated rapid detection with minimized non-specific amplification, whereas the SYBR Green-based method allowed for broader primer exploration by leveraging melting curve analysis. Despite the absence of HEV detection in 123 groundwater samples, this study underscores the value of real-time PCR for environmental monitoring and paves the way for enhanced diagnostic tools for public health applications. Full article

To capture the complex metallic spatter and melt pool behavior during the rapid interaction between the laser and metal material, high-speed cameras are applied to record the laser powder bed fusion process and generate a large volume of image data. In this study, four deep learning algorithms are applied: YOLOv5, Fast R-CNN, RetinaNet, and EfficientDet. They are trained by the recorded videos to learn and extract information on spatter and melt pool behavior during the laser powder bed fusion process. The well-trained models achieved high accuracy and low loss, demonstrating strong capability in accurately detecting and tracking spatter and melt pool dynamics. A stability index is proposed and calculated based on the melt pool length change rate. Greater index value reflects a more stable melt pool. We found that more spatters were detected for the unstable melt pool, while fewer spatters were found for the stable melt pool. The spatter’s size can affect its initial ejection speed, and large spatters are ejected slowly while small spatters are ejected rapidly. In addition, more than 58% of detected spatters have their initial ejection angle in the range of 60–120$°$. These findings provide a better understanding of spatter and melt pool dynamics and behavior, uncover the influence of melt pool stability on spatter formation, and demonstrate the correlation between the spatter size and its initial ejection speed. This work will contribute to the extraction of important information from high-speed recorded videos for additive manufacturing to reduce waste, lower cost, enhance part quality, and increase process reliability. Full article

Aiming at the problems of complex process flow, high energy consumption, and difficult emulsification in the preparation of traditional SBS-modified emulsified asphalt, a preparation method of fast-melting SBS (referred to as SBS-T) modified emulsified asphalt based on the integration of modification and emulsification is proposed. Based on surface free energy theory, the contact angles between three rapid-melting SBS-modified emulsified asphalts with different dosages and three probe liquids (deionized water, glycerol, and formamide) were measured using the sessile drop method. The adhesion performance of the asphalt–aggregate system was studied by means of micromechanical methods. The evaluation indicators such as the cohesion work of the emulsified asphalt, the adhesion work of asphalt–aggregate, the spalling work, and the energy ratio were analyzed. The results show that the SBS-T modifier can significantly improve the thermodynamic properties of emulsified asphalt. With increasing modifier content, the SBS-T-modified emulsified asphalt demonstrated enhanced cohesive work, improved asphalt–aggregate adhesive work, and increased energy ratio, while showing reduced stripping work. At equivalent dosage levels, the SBS-T-modified emulsified asphalt demonstrates a slight improvement in adhesion performance to aggregates compared to conventional SBS-modified emulsified asphalt. The SBS-T emulsified modified asphalt provides an effective technical solution for the preventive maintenance of asphalt pavements. Full article

With the rapid development of wireless communication, Wireless Local Area Networks (WLANs) are widely deployed in high-density environments. Ensuring fast handovers and optimal AP selection during device roaming is critical for maintaining network throughput and user experience. However, frequent mobility, high access density, and dynamic channel fluctuations complicate throughput prediction. To address this, we propose a method combining the Snow-Melting Optimizer (SMO) with decision tree regression models to optimize feature selection and model transmission opportunities (TXOP) and AP throughput. Experimental results show that the Extreme Gradient Boosting (XGBoost) model performs best, achieving high prediction accuracy for TXOP (MSE = 1.3746, R² = 0.9842) and AP throughput (MAE = 2.5071, R² = 0.9896). This approach effectively captures the nonlinear relationships between throughput and network factors in dense WLAN scenarios, demonstrating its potential for real-world applications. Full article

This paper presents the results of a comprehensive study of the structure, phase composition, thermal corrosion, and tribological properties of multilayer gradient coatings based on YSZ/NiCrAlY obtained using detonation spraying. X-ray phase analysis showed that the coatings consist entirely of metastable tetragonal zirconium dioxide (t’-ZrO₂) phase stabilized by high temperature and rapid cooling during spraying. SEM analysis confirmed the multilayer gradient phase distribution and high density of the structure. Wear resistance, optical profilometry, wear quantification, and coefficient of friction measurements were used to evaluate the operational stability. The results confirm that the structural parameters of the coating, such as porosity and phase gradient, play a key role in improving its resistance to thermal corrosion and CMAS melt, which makes such coatings promising for use in high-temperature applications. It is shown that a dense and thick coating effectively prevents the penetration of aggressive media, providing a high barrier effect and minimal structural damage. Tribological tests in the temperature range from 21 °C to 650 °C revealed that the best characteristics are observed at 550 °C: minimum coefficient of friction (0.63) and high stability in the stage of stable wear. At room temperature and at 650 °C, there is an increase in wear due to the absence or destabilization of the protective layer. Full article

Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination of the stability of samples. An analysis of PXRD characteristic peaks and DSC melting data suggested that instability likely stems from the presence of the amorphous phase. To validate this hypothesis, blended samples containing controlled ratios of amorphous phase and crystalline Form I were prepared. Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. Experimental results confirmed that all three models achieved classification accuracy values exceeding 70% in the stability prediction of the two groups of samples, which included “stable” and “unstable” samples, substantiating the hypothesis. Among them, the modeling method based on NIRS data was not only non-destructive and rapid but also demonstrates a superior discrimination accuracy value reaching 100% (n = 11), showing potential for promotion and application in industrial sample detection. The quantitative correlation between amorphous content and stability was successfully established in this study, offering a novel method for a quality stability assessment of atorvastatin calcium drug substances. Full article

Process control and quality assurance of wire + arc additive manufacturing (WAAM) and automated welding rely heavily on in-process monitoring videos to quantify variables such as melt pool geometry, location and size of droplet transfer, arc characteristics, etc. To enable feedback control based upon this information, an automatic and robust segmentation method for monitoring of videos and images is required. However, video segmentation in WAAM and welding is challenging due to constantly fluctuating arc brightness, which varies with deposition and welding configurations. Additionally, conventional computer vision algorithms based on greyscale value and gradient lack flexibility and robustness in this scenario. Deep learning offers a promising approach to WAAM video segmentation; however, the prohibitive time and cost associated with creating a well-labelled, suitably sized dataset have hindered its widespread adoption. The emergence of large computer vision models, however, has provided new solutions. In this study a semi-automatic annotation tool for WAAM videos was developed based upon the computer vision foundation model SAM and the video object tracking model XMem. The tool can enable annotation of the video frames hundreds of times faster than traditional manual annotation methods, thus making it possible to achieve rapid quantitative analysis of WAAM and welding videos with minimal user intervention. To demonstrate the effectiveness of the tool, three cases are demonstrated: online wire position closed-loop control, droplet transfer behaviour analysis, and assembling a dataset for dedicated deep learning segmentation models. This work provides a broader perspective on how to exploit large models in WAAM and weld deposits. Full article

Polypropylene (PP), with its good physical, thermal, and mechanical properties and excellent processing capabilities, has become one of the most used synthetic polymers. It is known that the overall properties of semicrystalline polymers, including PP, are governed by morphology, which is influenced by the crystallization behavior of the polymer under specific conditions. The most important industrial PP remains the isotactic one, and it has been studied extensively for its polymorphic characteristics and crystallization behavior for over half a century. Due to its regular chain structure, isotactic polypropylene (iPP) belongs to the group of polymers with a high tendency for crystallization. The rapid quenching of molten iPP fails to produce a completely amorphous polymer but leads to an intermediate crystalline order. On the other hand, slow cooling yields a material with high crystalline content. The processing conditions that occur in practice and industry are between these two extremes and, in some cases, are even very close. Therefore, the study of limits in processability and the impact of extreme preparation conditions on morphology, structure, thermal, and mechanical properties fills a gap in the current understanding of how the processing conditions of iPP can be used to design the desired properties for specific applications and is in the focus of this research. The first set of samples (Q samples) was obtained by rapid quenching, while the second was prepared by very slow cooling from the melt to room temperature (SC samples). Testing of samples was performed by optical microscopy (OM), scanning electron microscopy (SEM), wide-angle X-ray diffraction (WAXD), Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), dynamic dielectric spectroscopy (DDS), and mechanical measurements. Characterization revealed that slowly cooled samples exhibited a significantly higher degree of crystallinity and larger crystallites (χ ≥ 55% and L₍₁₁₀₎ ≈ 20 nm), compared to quenched samples (χ < 30%, L₍₁₁₀₎ ≤ 3 nm). Mechanical testing showed a drastic contrast: quenched samples exhibited elongation at break > 500%, while slowly cooled samples broke below 15%, reflecting their brittle behavior. For the first time, DDS is applied to investigate molecular mobility differences between processing-dependent structural forms, specifically the mesomorphic (smectic) and α-monoclinic forms. In slowly cooled samples, α relaxation exhibited both enhanced intensity and an upward temperature shift, indicating stronger structural constraints due to a much higher crystalline phase content and significantly larger crystallite size, respectively. These findings provide novel insights into the structure–property–processing relationship, which is crucial for industrial applications. Full article

316L stainless steel (316L SS) exhibits excellent corrosion resistance, mechanical properties, and biocompatibility, but the rapid melting and solidification of the laser powder bed fusion (PBF-LB/M) process reduce the properties of the newly formed parts. This study aims to enhance the mechanical properties of PBF-LB/M PBF-LB/M-formed 316L SS parts by investigating the effects of various heat treatment temperatures. The results show that an appropriate heat treatment temperature can improve the microstructure and mechanical properties of the formed parts. Lower temperatures have minimal effects on performance; however, at 1100 °C, recrystallization occurs, resulting in more uniform grain structures, improved densification, and substantial stress relief. The residual stress is reduced by 85.59% compared to the untreated PBF-LB/M samples, while the ferrite content is significantly decreased, making the phase structure more homogeneous. Although both yield strength and tensile strength decrease, plasticity improves by 21.11%. Full article

Background/Objectives: An accurate quantification of the effective antigens from different serotypes is essential for the quality control of multivalent vaccines, but it remains challenging. Herein, we developed a simple and high-throughput method using differential scanning fluorimetry (DSF) for quantifying foot-and-mouth disease virus (FMDV) antigens in monovalent and bivalent vaccines. Methods: Purified serotypes A and O FMDV were used to establish and validate the method. The DSF parameters, including the dye concentration, thermal scanning velocity, and PCR tube material, were optimized at different FMDV concentrations. The established DSF method was validated for the quantification of monovalent and A/O bivalent FMDV, and was compared with the ultracentrifugation of 86 samples from different processing stages and serotypes. Results: The DSF showed that the melting temperature (T_m) of type A (56.2 °C) was significantly higher than that of type O FMDV (50.5 °C), indicating that their T_m can be distinguished in bivalent antigens. After optimizing the DSF parameters, a strong correlation (R² > 0.998) was observed between the 146S concentration and the maximum of the first derivative of the DSF fluorescence (d(RFU)/dT) for both serotypes A and O FMDV. The method demonstrated good reproducibility (RSD < 10%) and high sensitivity (limit of detection: 0.7 μg/mL). Using a multiple linear regression analysis, the simultaneous quantification of A and O FMDV in the bivalent mixtures achieved recovery rates of 82.4–105.5%, with an RSD < 10% for most of the samples. Additionally, the DSF results correlated well with the ultracentrifugation data (Pearson ρ = 0.9789), validating its accuracy and broad applicability. Conclusions: In summary, DSF represents a simple, rapid, and high-throughput tool for the quality control of monovalent and bivalent FMDV vaccines. Full article

The Tungnárhraun basalts in southern Iceland record a transcrustal magma system formed during Holocene deglaciation. These large-volume (>1 km³) Early through Mid-Holocene lavas contain ubiquitous plagioclase feldspar macrocrysts that are too primitive to have grown from the host lavas. Thermobarometry based on plagioclase melt and clinopyroxene melt equilibrium reveals a transcrustal structure with at least three distinct storage regions. A lower-crustal mush zone at ~14–30 km is fed by primitive, low ⁸⁷Sr/⁸⁶Sr magmas with diverse Ti/K and Al/Ti signatures. Plagioclase feldspar growth is controlled by an experimentally determined pseudoazeotrope where crystals develop inversely correlated An and Mg contents. The rapid ascent of magmas to mid-crustal levels (~8–9 km) allows the feldspar system to revert to conventional thermodynamic phase constraints. Continued plagioclase growth releases heat, causing olivine and pyroxene to be resorbed and giving the magmas their characteristic high CaO/Al₂O₃ values (~0.8–1.0) and Sc contents (~52 ppm in matrix material). Mid-Holocene MgO-rich lavas with abundant plagioclase feldspar macrocrysts erupted directly from this depth, but both older and younger magmas ascended to a shallow-crustal storage chamber (~5 km) where they crystallized olivine, clinopyroxene, and plagioclase feldspar and evolved to lower MgO contents. The Sr isotope differences between the plagioclase macrocrysts and their carrier melts suggest that the fractionation involves the minor assimilation of country rock. This model does not require the physical disruption of an established and long-lived gabbroic cumulate mush. The transcrustal structures documented here existed in south Iceland at least throughout the Holocene and likely influenced much of Icelandic magmatism. Full article

With the rapid development of renewable energy, the co-combustion of Zhundong coal and biomass has attracted more and more attention. However, the high content of alkali metals in Zhundong coal and biomass leads to serious slagging and fouling in the co-combustion process. In this study, cotton straw was selected for co-combustion with Zhundong coal. The ash deposition model was established according to the melting ration calculated by Factsage, and the ash deposition characteristics during the co-combustion of Zhundong coal and cotton stalks in the actual boiler were explored by Fluent. The results showed that the K₂O content in ash increased from 0.31% to 9.31% with the increase in the blending ratio, while the contents of other components had no significant changes. In addition, with the increase in the blending ratio, the ash deposition rate increased from 0.00327 kg/(m²·s) to 0.00581 kg/(m²·s), an increase of 77.6%. The reduction in the tangential circle diameter obviously alleviated the ash deposition on the wall. When the tangential circle diameter was reduced to 400 mm, the ash deposition rate was 0.00207 kg/(m²·s), which was 37.6% lower than the original condition. Full article

This study presents a bioinspired phase-change transparent flexible heater (PTFH) for programmable droplet manipulation under ultralow voltage. By embedding a self-junctioned copper nanowire network into paraffin-infused, porous PVDF-HFP gel matrices, the PTFH achieves rapid, non-contact, and reversible control of microdroplet mobility. The PTFH can be bent or tailored into diverse shapes (e.g., V/X configurations), enabling multidirectional droplet transport. Under ultralow voltage actuation (<1 V), the surface of PTFH melts the phase-change lubricant within 2 s, switching surface wettability from high adhesion (Wenzel state) to low adhesion (SLIPS state). By combining Laplace pressure and temperature gradients (up to 22 °C/mm), drive droplets at ~2.0 mm/s over distances of ~13.9 mm. Programmable droplet coalescence, curved-surface transport, and a microreactor design for batch reactions were also demonstrated. The PTFH exhibits excellent transparency (89% when activated), mechanical flexibility, and cyclic stability, offering a versatile platform for microreactors, microengines, and smart windows. Full article