Search Results (7,405)

This paper presents a compact multi-beam dual-circularly polarized phased array receiving system operating in the 10.7–12.7 GHz frequency band is designed and implemented, which can generate eight reconfigurable receiving beams with independently configurable polarization modes and scanning directions for each beam. To improve the aperture utilization efficiency of the array and reduce the array size, the proposed phased array architecture adopts a “full-aperture multiplexing” beamforming method, where all beams share the same array aperture. For cost-effective phased array architecture with two-dimensional scalability, the array is divided into several identical receiving subarrays, with the control and power supply modules arranged beneath the array aperture. In addition, a heterogeneous integration scheme is introduced to realize high-density integration of various receiving functional chips, which reduces the overall array footprint by approximately 30% while maintaining the basic performance of the system gain-to-noise-temperature ratio (G/T). Meanwhile, different dielectric substrates are adopted to implement multi-level combining networks, optimizing the trade-off between overall efficiency and cost. To verify the feasibility of the proposed architecture, a prototype with a 16 × 16 array configuration is developed and tested. The measured results show that the array gain reduction is no more than 4 dB at a maximum scanning angle of 60°, and the G/T value of all beams in the boresight direction is not less than 0.9 dB/K at 11.7 GHz. The experimental results validate the effectiveness of the proposed multi-beam dual-circularly polarized phased array architecture in terms of engineering implementation and system performance. Full article

Hydrogels are endowed with exceptional hydrophilicity and biocompatibility by their network structure, while also exhibiting soft physical properties similar to living tissues, which renders them ideal biomaterials. Responsive hydrogels—particularly those constructed from multicomponent systems including proteins, polysaccharides, peptides, and polyphenols—have emerged as a frontier research focus owing to their tunable responsiveness and controllable functional properties. In this review, hydrogel response mechanisms were categorized according to pH, ionic strength, temperature, light, enzymes, and multi-stimuli interactions. Key preparation strategies, encompassing chemical, physical, and enzymatic crosslinking, were systematically introduced. The preparation of hydrogels from various food-grade matrices, such as polysaccharide-based, protein-based, peptide-based, and polyphenol-based systems, was also summarized, with emphasis placed on how their tailored structures govern functional performance. Furthermore, innovative applications of responsive hydrogels were highlighted, including targeted delivery of nutrients and bioactive substances (e.g., probiotics, anthocyanins, vitamins) in functional foods, smart packaging and sensing for real-time freshness monitoring of meat and fruits, food quality detection through colorimetric and photothermal sensors, and 4D food printing for personalized nutrition and dysphagia-friendly foods. Full article

Engineering carbon nanostructures directly on carbon fiber fabrics offers an effective route to constructing hierarchical multifunctional coating systems. In this study, methane-based chemical vapor deposition (CVD) was employed to investigate nanocarbon coating formation on woven carbon fabrics supported by electrodeposited Ni catalysts. Catalyst morphology was systematically engineered through surface pretreatment, electric-field configuration, and pulse electrodeposition. At 700 °C, methane activation was insufficient to sustain continuous nanocarbon growth, indicating a temperature-dependent activation threshold. Raising the growth temperature to 900 °C enabled sustained methane decomposition and produced dense nanocarbon coatings; hydrogen assistance suppressed amorphous deposition and promoted more ordered nanofilament features. Pulse electrodeposition refined Ni catalyst dispersion and nucleation density, improving coating uniformity compared with direct-current deposition. Structural ordering was further supported by Raman spectroscopy (D and G bands with an average ID/IG of 0.678 ± 0.068 for methane-grown samples versus 0.798 ± 0.011 for electrodeposition-only controls) and by HRTEM revealing multi-layer graphitic walls (~0.34 nm interlayer spacing). Together, the results support a methane-derived dissolution–diffusion–precipitation growth pathway governed by catalyst morphology, temperature, and gas composition. This controllable, textile-compatible catalyst engineering approach provides a scalable route to hierarchical graphitic coatings for carbon-fabric-based composites, electromagnetic interference shielding, and thermal management applications. Full article

Aerobic composting shows state-dependent dynamics in key parameters such as temperature, moisture content, oxygen concentration, and pH, and these variables are strongly coupled over time. This coupling makes accurate state identification and process regulation challenging when relying on single-parameter thresholds or experience-based control. To enable robust recognition of composting states throughout the process, we propose an IRRTO-optimized CNN–LSTM–attention model (IRRTO–CNN–LSTM–attention). The model uses a convolutional neural network (CNN) to extract discriminative multivariate features, a long short-term memory (LSTM) network to model temporal dependencies, and an attention module to adaptively emphasize informative features. To address the hyperparameter selection challenge, the Rapidly-exploring Random Tree Optimizer (RRTO) was introduced and further enhanced via four strategies (fluctuating attenuation adaptive regulation, dual-mode guided update, dynamic dimension adaptive perturbation, and dual-mechanism adaptive perturbation regulation), forming the improved IRRTO. The proposed approach was validated using sensor data from windrow composting of pig manure and corn straw. The IRRTO–CNN–LSTM–attention model achieved an overall accuracy of 98.31% in classifying the four states (mesophilic/heating, thermophilic, cooling, and abnormal) on the independent test set, which was 3.39 percentage points higher than the RRTO-based model. These results suggest that the proposed method can accurately identify composting states and support early warning and state-specific regulation in practical aerobic composting systems. Full article

The adoption of electric vehicles (EVs) is a promising strategy for reducing emissions and promoting sustainable mobility. The increasing adoption of EVs has created a demand for efficient and sustainable charging infrastructure. The integration of rooftop solar-powered EV charging stations into distribution networks is a promising solution for reducing carbon emissions and improving grid efficiency. This integration also introduces challenges, such as power quality issues, grid instability, and the impact of environmental factors on solar generation. This study proposes a novel system that integrates a smart control algorithm for a central battery management system (CBMS) with advanced bidirectional DC-DC converters for optimised power distribution. Unlike existing systems that focus on individual components, this study combines real-time environmental monitoring with adaptive power management algorithms to handle variations in generation owing to solar irradiance, temperature, and shading, and ensure maximum power harvesting. This study also presents the role of the DC-to-DC converter integrated with a smart charging control and CBMS in smart grid-enabled EV charging station. The proposed system was validated using MATLAB 2025b Simulink simulations. This study demonstrates an improvement in overall grid stability and highlights the potential of DC-DC converter technologies for smart grid applications and decarbonisation efforts. Full article

Linear alkylbenzene (LAB) is the main raw material used to make biodegradable detergents, and its production process is based on aromatic alkylation. HY zeolites that have undergone controlled dealumination and desilication have led industrial standards amongst solid acid catalysts because of their controllable acidity and hierarchical pore structure. Coke formation in such systems can assume a dual role, which is dependent on its condition. Though the over-deposition is known to cause deactivation by blocking the micropores, Bronsted acid-site masking, and diffusion collapse, the low-level deposition could also be done to increase the monoalkylate selectivity by the pore mouth catalysis, steric modulation, and selective suppression of secondary alkylation pathways. The critical review is done on the structural-kinetic interaction that determines the coke evolution in HY-based catalysts. In order to moderate the acid-site density and enhance hydrothermal stability, dealumination (Si/Al optimization of about 2.5 to 30–100) occurs, but to reduce deep-pore coke formation, desilication (interconnected mesopores) is created. The bimodal porosity and regulated acidity are found to be synergistic, as hierarchical HY zeolites produced through successive cycles of steam and alkaline treatments not only show LAB selectivity in excess of 90% but also exhibit much longer catalyst lifetimes. Quantitative research on the beneficial coke regime revealed that it was composed of about 36 wt% hydrogen-rich species, which were localized at the pore mouths, hence enhancing monoalkylation selectivity by 15–40%. Beyond a critical transition window (e.g., 8–12 wt.%), coke formation to condensed polyaromatic and graphitic products leads to fast deactivated coke formation, which is due to percolation limits and transport-controlled kinetics. More advanced techniques of characterization of the coke, e.g., temperature-programmed oxidation (TPO), ²⁷Al MAAS NMR, and UV-Raman spectroscopy, indicate how the coke is changed to highly structured graphitic deposits of high oxidation activation energy. Activity recovery of 85–98% is obtained in regeneration processes, including controlled oxidative calcination, microwave-based and plasma-based processes, and thermal management protocols, and it would be determined by the chemistry of the coke, its spatial distribution, and the regeneration protocols. This paper has developed a mechanistic coke control system by cross-tuning the acidity and development of an effective pore network, which led to a sustainable aromatic alkylation reaction with minimal activity loss, high selectivity, and long life. Full article

Efficient ortho–para hydrogen conversion is essential to suppress spontaneous heat release and boil-off losses during cryogenic liquid hydrogen storage and pre-liquefaction processes. In this study, a novel catalyst-filled wavy plate-fin heat exchanger (CFHE) is proposed to simultaneously enhance heat transfer and ortho–para hydrogen conversion under cryogenic conditions. Compared with conventional straight-fin configurations, the wavy-fin structure introduces controlled flow perturbations and increased specific surface area, thereby intensifying transport processes. Three-dimensional computational fluid dynamics (CFD) simulations, using the SST k–ω turbulence model, coupled with an ortho–para hydrogen conversion kinetic model were performed to quantitatively investigate the effects of key geometric parameters and catalyst loading on hydrogen conversion, heat transfer, and pressure drop within a Reynolds number range of 941–1577 and a temperature range of 35–20 K. Within the same CFHE configuration, the para-hydrogen fraction remains nearly unchanged without catalyst but increases significantly with catalyst loading. However, the catalyst reduces the global average Colburn j-factor by about 25%. Despite higher friction losses, the outlet–inlet temperature difference decreases to about 0.866 times that of the non-catalyst case, indicating improved temperature uniformity. A comprehensive performance index e, integrating heat transfer enhancement, flow resistance, and conversion efficiency, was introduced and optimized using a genetic algorithm. The optimized CFHE achieves an outlet para-hydrogen fraction exceeding 95% of the thermodynamic equilibrium value while maintaining hydrogen entirely in the gaseous phase to avoid catalyst deactivation. Overall, the catalyst-packed wavy channel configuration demonstrates superior conversion efficiency, enhanced thermal uniformity, and improved overall performance compared with straight-fin structures, providing quantitative design guidance for high-performance heat exchangers in cryogenic hydrogen liquefaction systems. Full article

This study presents a structured multi-sensor predictive maintenance framework for CO₂ laser cutting machines based on real-time data acquisition and supervised machine learning. The proposed architecture integrates heterogeneous sensor signals—including vibration, temperature, humidity, and acoustic measurements—through synchronized feature-level fusion to characterize machine operational states. A statistically grounded thresholding strategy, validated using two years of operational observations and controlled experimental perturbations, is employed to distinguish normal and abnormal behavior. Sensor data are processed using a Decision Tree classifier implemented in Python with Scikit-learn, enabling short-horizon probabilistic fault prediction during operational cycles. The system is deployed in a real industrial environment and validated using cross-validation and structured dataset partitioning to assess generalization performance. Results demonstrate reliable fault discrimination capability under controlled operational conditions, highlighting the effectiveness of feature-level sensor integration for early anomaly detection. The modular hardware–software architecture supports adaptability to other CNC platforms with appropriate recalibration and retraining. The proposed framework provides a low-cost, interpretable, and computationally efficient solution for real-time industrial predictive maintenance applications. Full article

Thermoelectric generators (TEGs) enable compact waste-heat energy harvesting but require high-gain DC–DC conversion due to their low-output voltage for DC microgrid interfacing. This work proposes a novel TEG-supplied two-stage architecture consisting of a perturb-and-observe (P&O)-based MPPT boost converter followed by a modified Z-source converter regulated through an advanced model predictive control (MPC) framework. The modified Z-source topology enables high-voltage gain without extreme duty ratios and mitigates switching losses by eliminating diode reverse-recovery effects via synchronous operation. To enhance dynamic performance, the advanced MPC strategy incorporating an adaptive ripple-based weighting mechanism is applied to the modified Z-source converter and benchmarked against MPC and sliding mode control (SMC). Simulation results under multiple disturbance scenarios, including hot-side and cold-side temperature variations, multi-condition disturbances, coupling-factor variation, and measurement noise, demonstrate that the proposed system maintains stable 400 V regulation at a 100 W output level. In contrast, MPC exhibits switching frequency deviations that increase switching losses during transient operation, while SMC suffers from significant voltage deviations under source variations. The proposed strategy maintains tight voltage regulation with nearly fixed-frequency operation around 50 kHz, providing a new perspective for TEG researchers while supporting sustainable waste-heat energy utilization. Full article

The limited high-temperature resistance of Ordinary Portland Cement (OPC) remains a critical challenge for fire-exposed and industrial concrete structures. Its performance deterioration above 500 °C is associated with dehydration and recrystallization of hydration products, leading to structural degradation of the cement matrix. To address this limitation, partial clinker replacement with fly ash combined with sodium water glass activation was proposed to enhance thermal stability. Physico-chemical analysis revealed the absence of portlandite and the formation of C-A-S-H and zeolite-like N–C–A–S–H phases in the fly ash-containing alkali-activated Portland cement. Upon heating, C-A-S-H phases sintered into stable high-temperature calcium aluminosilicate phases and zeolite-like phases underwent topotactic recrystallization into feldspathoid-type structures, preserving matrix integrity at high temperatures. The optimized composition region of cement system (fly ash—12.0–16.5 wt. %, density of water glass—1220–1240 kg/m³) was characterized by residual strength ≥ 50%, while compressive strength at 28 days was ≥80 MPa, exceeding the residual performance typically reported for conventional OPC systems under similar conditions (5–35%). The study was devoted to revealing the potential of low-emission Portland cements in high-temperature-resistant concretes through the utilization of fly ash. The mechanism that controls the compressive strength and temperature resistance of such cements has been demonstrated. Full article

School classrooms represent complex, interconnected systems where indoor environmental quality critically influences student health, cognitive performance, and educational equity. Yet traditional approaches operate in disciplinary silos, creating systemic failures in design, operation, and maintenance. This narrative review adopts a systems engineering framework to demonstrate how integrated interventions—spanning policy, design, technology, and operations—create resilient, sustainable, and healthy classroom climates. Amid escalating climate change impacts (rising temperatures, heatwaves, wildfires) and emerging threats (airborne pathogens, urban pollution), reactive measures like school closures prove pedagogically counterproductive. This review synthesizes evidence on natural, mechanical, and mixed-mode ventilation systems optimized through advanced control strategies, smart technologies, and health-centred policies. Key findings reveal that synergistic integration of Policy, Management, Construction, Operation, and Smart Technologies, in a systems engineering framework, outperforms singular strategies. Critical interventions include hybrid ventilation coupled with layered defences (HEPA filtration, UVGI), AI-driven adaptive controls using IoT sensors and Model Predictive Control to optimize energy while managing pollutant concentrations, and mandatory IAQ standards rooted in stakeholder education. By framing classrooms as interconnected engineering systems, this work provides actionable insights for architects, engineers, policymakers, and administrators, positioning future school design toward resilience, sustainability, and human-centred health outcomes. Full article

Arctic regions are experiencing accelerated environmental change, yet integrated assessments of terrain-scale responses remain limited. This study quantifies the spatial-temporal variability of glaciers, shorelines, and outwash plains in Kaffiøyra, Svalbard, Norway, over four decades (1985–2023) using cross-evaluated Landsat and Sentinel imagery. Our results reveal systematic retreat across all eight glaciers (R² = 0.83–0.96), with tidewater glaciers experiencing substantially greater terminus area loss (62.8% and 72.1%) compared to land-terminating glaciers (34.5–69.0%). Coastal changes were highly variable: erosion (up to −3.2 m/yr) was most pronounced on shores exposed to southwesterly summer waves, while significant accretion (+13.0 m/yr) occurred near the tidewater glacier terminus. The insignificant outwash changes (−6.4% to +2.7%) despite substantial land-terminating glacier retreat indicate these systems respond to different controls. A moderate negative correlation between glacier terminus area and summer temperatures (r = −0.55 to −0.69) enabled a simple projection model. Diagnostic projections to 2020–2039 showed that both downscaled climate models and extrapolated local data overestimated retreat. However, extrapolated local data proved more accurate, with its projection gap averaging 11% for land-terminating and 46% for tidewater glaciers. The study provides crucial insights into Arctic terrain behaviors, highlighting complex and divergent responses. These findings emphasize the need for enhanced localized monitoring systems through ongoing high-resolution image surveys and planned modeling to understand accelerating polar environmental changes. Full article

Metal additive manufacturing (AM) facilitates the production of geometrically complex components, yet its broader industrial use remains limited by the risk of defect formation and uncertainties in their detection, originating from the highly dynamic and high-temperature process environment. To make additive manufacturing more reliable and establish high-quality parts, it is important to understand how these defects form and how their characteristics appear during the process. This review explains the main causes of common defects, such as cracking, porosity, lack of fusion, and inclusions in metal AM processes, including Powder Bed Fusion and Directed Energy Deposition. It also connects main defect formation mechanisms to the optical, thermal, acoustic, and spectroscopic signals that can be measured during the process. Moreover, it is described how commonly used in situ monitoring systems work and how their signals correspond to melt pool dynamics, vapor plume, particle movement, and the solidification process for each kind of defect. An overview is provided of how data from these systems are analyzed, including the extraction of features from images, the evaluation of temperature fields, and the use of time and frequency domain techniques for various signals. By linking the physics of defect formation to measurable process signals, the interpretation of sensor data is enabled, and potential strategies for monitoring specific problems are outlined. Finally, recent developments are examined, including the integration of multiple sensors, advanced feature-representation approaches, and real-time data interpretation coupled with adaptive control. Together, these directions represent promising advances towards more intelligent and reliable monitoring systems for the future of metal AM. Full article

In the current work, a novel heat pump drying system with precise control of temperature and humidity of drying medium was developed and the impacts of drying temperature and humidity on the drying characteristics of apple slices and energy consumption of drying system were investigated. Experimental results indicated that the temperature and relative humidity (RH) of drying medium have a significant impact on drying efficiency and operating performance. During the first hour of the drying process, the heat pump drying of apple slices exhibited the highest drying rate throughout the entire process at a temperature of 40~50 °C and a relative humidity of 30~60%. And then the apple slices drying was in a falling-rate drying stage. When the relative humidity of the drying medium exceeded 50%, the final moisture content of the material increased significantly and exceeded 20% (dry basis, d.b.). Increased air medium temperature and humidity enhance the dehumidification rate of the evaporator. When the drying temperature was maintained at 40–60 °C, the condensation rate at 60% RH was 3.5–10 times that at 30% RH. The increased dehumidification rate significantly promoted the energy efficiency. The specific moisture extraction rate (SMER) was 2.53 kg/(kW·h) at 60 °C and 60% RH, which is 3.4 times that at 30% RH. It was appropriate to adopt high-temperature and high-humidity conditions in the early drying stage to improve drying energy efficiency. Meanwhile, the relative humidity should be reduced to promote moisture removal from the material in the late drying stage. The obtained results provided theoretical methods for the energy-saving control of heat pump drying for fruits. Full article

This study presents an Internet of Things (IoT)-assisted semi-open hydroponic system for cultivating Andrographis paniculata under tropical conditions, aiming to enhance biomass productivity, andrographolide (AG) yield, and production efficiency. IoT-assisted hydroponics, non-IoT hydroponics, and soil-based cultivation were compared in 10 m² greenhouses. The IoT system enabled real-time monitoring and adaptive regulation of temperature, relative humidity, light intensity, nutrient solution pH, and electrical conductivity (EC). IoT-assisted hydroponics achieved earlier harvest (≈90 days) and the highest fresh biomass yield (0.409 ± 0.014 kg m⁻²) while maintaining per-plant productivity (15.74 ± 0.54 g plant⁻¹) comparable to soil-based cultivation. Andrographolide concentration reached 25.58 ± 3.36 mg g⁻¹ DW (2.56% w/w), meeting pharmacopeial requirements. Owing to stable environmental regulation and tolerance to high planting density, the IoT system produced the highest areal AG productivity (209.5 mg m⁻²), representing a four- to tenfold increase over the other systems. Despite higher operational costs, IoT-assisted hydroponics achieved the lowest AG unit cost (≈6.77 USD g⁻¹). While most previous studies emphasize tissue-level AG concentration, system-level productivity and cost efficiency under realistic cultivation conditions remain insufficiently explored. Overall, IoT-enabled semi-open hydroponics provides a scalable and economically viable approach for medicinal plant production, bridging the gap between open-field cultivation and fully controlled plant factory systems. Full article