Search Results (1,018)

Polymer composites reinforced with nanofillers, synthetic fibers, and inorganic fillers have progressed rapidly, yet recent advances remain fragmented across filler-specific studies and often lack unified mechanistic interpretation. This review addresses this gap by presenting an interphase-centric, mechanism-driven framework linking processing routes, dispersion and functionalization requirements, interphase formation, and the resulting structure–property relationships. Representative quantitative datasets and mechanistic schematics are integrated to rationalize nonlinear mechanical reinforcement, percolation-controlled electrical/thermal transport, and thermal stabilization and barrier effects across major filler families. The review highlights how reinforcement efficiency is governed primarily by interfacial adhesion, filler connectivity, and processing-induced microstructural evolution rather than filler loading alone. Key challenges limiting scalability are critically discussed, including dispersion reproducibility, viscosity and processability constraints, interphase durability, and recycling compatibility. Finally, mechanism-based design rules and future outlook directions are provided to guide the development of high-performance, multifunctional, and sustainability-oriented polymer composite systems. Full article

The structural origin of the germanate anomaly in glasses, which involves complex Ge–O coordination environments, is frequently studied using crystalline analogs. This study aims to provide reliable spectroscopic fingerprints by performing a detailed structural and thermal analysis of crystalline A₄Ge₉O₂₀ model systems with A = Li, Na, K. The compounds were synthesized via melt crystallization and characterized using powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), and Raman spectroscopy techniques. The results demonstrate clear cation-dependent crystallization pathways. The Li-containing system predominantly forms Li₂Ge₇O₁₅ in mixture with Li₄Ge₉O₂₀, indicating a preference for thermodynamically stable phases. The Na-system successfully yields the target Na₄Ge₉O₂₀ compound. In contrast, the K-system primarily produces the likely metastable K₂Ge₄O₉ phase with a significant amorphous fraction, highlighting the role of kinetic limitations. This comparative study demonstrates that the size of the alkali cation is a critical factor for controlling phase formation under identical stoichiometric and thermal conditions. Full article

The valorization of dredged sediments represents a major environmental and logistical challenge, particularly in the context of forthcoming regulations restricting their marine disposal. This study investigates the potential of untreated dredged sediments as sustainable raw materials for geopolymer binder development, with the dual objective of sustainable sediment management and reduction in cement-related environmental impact. Dredged sediments from the Grand Port Maritime de Bordeaux (GPMB) were activated with sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃), both alone and in combination, with supplementary aluminosilicate and calcium-rich co-products, to assess their reactivity and effect on binder performance. A multi-scale experimental approach combining mechanical testing, calorimetry, porosity analysis, Scanning Electron Microscopy and Energy-Dispersive Spectroscopy (SEM–EDS), X-ray diffraction (XRD), Thermogravimetric Analysis (TGA), and solid-state Nuclear Magnetic Resonance (NMR) was employed to challenge the commonly assumed inert behavior of sediments within geopolymer matrices, to elucidate gel formation mechanisms, and to optimize binder formulation. The results show that untreated sediments actively participate in alkali activation, reaching compressive strengths of up to 5.16 MPa at 90 days without thermal pre-treatment. Calcium-poor systems exhibited progressive long-term strength development associated with the formation of homogeneous aluminosilicate gels and refined microporosity, whereas calcium-rich systems showed higher early age strength but more limited long-term performance, linked to heterogeneous gel coexistence and increased total porosity. These findings provide direct evidence of the intrinsic reactivity of untreated dredged sediments and highlight the critical role of gel chemistry and calcium content in controlling long-term performance. The proposed approach offers a viable pathway for low-impact, on-site sediment valorization in civil engineering applications. Full article

This paper presents a thermal management solution for a Ka-band gyrotron traveling wave tube (gyro-TWT) with non-superconducting magnets. At present, the miniaturization and non-superconductivity of gyro-TWT have become a trend, but miniaturization leads to a significant increase in power density and a severe limitation in heat sink volume, which critically limits power capacity. To address this challenge, a joint microwave–thermal management evaluation model is used to investigate the heat transfer process and identify the crucial factors constraining the power capacity. A cylindrical heat sink with narrow rectangular grooves is introduced. Based on this, the cooling efficiency has been enhanced through structural optimization. The beam–wave interaction, electrothermal conversion, and heat conduction processes of the interaction circuit are analyzed. The compact heat sink achieves a 1.2-fold increase in coolant utilization and reduces the overall volume by 27.4%. Meanwhile, this heat sink improves the cooling performance and power capability of the gyro-TWT effectively. At 29 GHz, the gyro-TWT achieves a pulse power of 150 kW. Simulation results show that the maximum temperature is 348 °C at a 45% duty cycle, reduced by 159 °C. The power capacity of the Ka-band gyro-TWT increases by 40.6%. Full article

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

Aerospace power systems, including satellites in low earth orbit (LEO) and geostationary earth orbit (GEO), face stringent thermal constraints to minimize size, weight, and power (SWaP). Gallium nitride (GaN) devices offer superior radiation hardness—critical for the harsh space environment—and MHz-level switching capabilities. This high-frequency operation minimizes passive components, particularly magnetics, thereby reducing the overall volume. However, above 10 MHz, magnetic cores become impractical due to material limitations. To address these issues, this article proposes a design methodology for a GaN-based quasi-square-wave (QSW) buck converter integrated with a PCB air-core inductor. First, the impact of the switching frequency and dead time on the zero-voltage switching (ZVS) condition is elaborated. Then, a power loss model accounting for various loss mechanisms is presented. To overcome high GaN body diode reverse conduction loss, an auxiliary diode is employed. Based on the model, a design procedure is developed to optimize the inductor for 10 MHz operation while maximizing efficiency. To validate the design, a 28 V/12 V, 18 W prototype was built and tested. Experimental results demonstrate a peak efficiency of 86.5% at 10 MHz. The auxiliary diode improves efficiency by 4%, verifying reverse conduction loss mitigation. Thermal analysis confirms a full-load case temperature of 62.2 °C, providing a 47.8 °C safety margin compliant with aerospace derating standards. These findings validate the solution for high-frequency, space-constrained aerospace applications. Full article

Promoting the development of aerospace vehicles toward structural–functional integration and intelligent sensing is a key strategy for achieving lightweight, high-reliability, and autonomous operation and maintenance of next-generation aircraft. However, traditional external sensors face significant limitations because of their bulky size, installation challenges, and incompatibility with aerodynamic surfaces. These issues are particularly pronounced on complex, high-curvature substrates, where achieving conformal bonding is difficult, thus restricting their application in critical components. In this study, aerosol jet printing (AJP) was employed to directly fabricate silver nanoparticle-based temperature sensors with real-time monitoring capabilities on the surface of high-curvature stainless steel sleeves, which serve as typical engineering components. This approach enables the in situ manufacturing of high-precision conformal sensors. Through optimized structural design and thermal treatment, the sensors exhibit reliable temperature sensitivity. Microscopic characterization reveals that the printed sensors possess uniform linewidths and well-defined outlines. After gradient sintering at 250 °C, a dense and continuous conductive path is formed, ensuring strong adhesion to the substrate. Temperature-monitoring results indicate that the sensor exhibits a nearly linear resistance response (R² > 0.999) across a broad detection range of 20–200 °C. It also demonstrates high sensitivity, characterized by a temperature coefficient of resistance (TCR) of 2.15 × 10^−3/°C at 20 °C. In repeated thermal cycling tests, the sensor demonstrates excellent repeatability and stability over 100 cycles, with resistance fluctuations kept within 0.5% and negligible hysteresis observed. These findings confirm the feasibility of using AJP technology to fabricate high-performance conformal sensors on complex surfaces, offering a promising strategy for the development of intelligent structural components in next-generation aerospace engineering. Full article

Metal additive manufacturing (AM) generates complex microstructures through extreme thermal gradients and rapid solidification, critically influencing mechanical performance and industrial qualification. This review synthesizes recent advances in cellular automata (CA) and phase-field (PF) modeling to predict grain-scale microstructure evolution during AM. CA methods provide computational efficiency, enabling large-domain simulations and excelling in texture prediction and multi-layer builds. PF approaches deliver superior thermodynamic fidelity for interface dynamics, solute partitioning, and nonequilibrium rapid solidification through CALPHAD coupling. Hybrid CA–PF frameworks strategically balance efficiency and accuracy by allocating PF to solidification fronts and CA to bulk grain competition. Recent algorithmic innovations—discrete event-inspired CA, GPU acceleration, and machine learning—extend scalability while maintaining predictive capability. Validated applications across Ni-based superalloys, Ti-6Al-4V, tool steels, and Al alloys demonstrate robust process–microstructure–property predictions through EBSD and mechanical testing. Persistent challenges include computational scalability for full-scale components, standardized calibration protocols, limited in situ validation, and incomplete multi-physics coupling. Emerging solutions leverage physics-informed machine learning, digital twin architectures, and open-source platforms to enable predictive microstructure control for first-time-right manufacturing in aerospace, biomedical, and energy applications. Full article

Thermoplastic starch (TPS) blended with biodegradable polyesters such as polyhydroxybutyrate (PHB), polylactic acid (PLA), polybutylene succinate (PBS), and polycaprolactone (PCL) represents a promising route toward sustainable alternatives to petroleum-based plastics. TPS offers advantages related to abundance, low cost, and biodegradability, while polyesters provide improved mechanical strength, thermal stability, and barrier performance. However, the intrinsic incompatibility between hydrophilic TPS and hydrophobic polyesters typically leads to immiscible systems with poor interfacial adhesion and limited performance. This review critically examines recent advances in the development of TPS/polyester blends, with emphasis on compatibilization strategies based on chemical modification, natural and synthetic compatibilizers, bio-based additives, and reinforcing agents. Particular attention is given to the role of organic acids, essential oils, phenolic compounds, nanofillers, and natural reinforcements in controlling morphology, crystallinity, interfacial interactions, and thermal–mechanical behavior. In addition, the contribution of bioactive additives to antimicrobial and antioxidant functionality is discussed as an emerging multifunctional feature of some TPS/polyester systems. Finally, current limitations related to long-term stability, scalability, and life cycle assessment are highlighted, identifying key challenges and future research directions for the development of advanced biodegradable materials with tailored properties. Full article

Microplastics (MPs) are pervasive environmental pollutants, widely distributed from aquatic ecosystems to the terrestrial food chain, and represent a potential route of human exposure. Although several reviews have addressed MP contamination, a critical synthesis focusing on pathways through which consumer goods directly enter food and beverages, along with corresponding industry and regulatory responses, is lacking. This review fills this gap by proposing the direct release of MPs from common sources such as food packaging, kitchen utensils, and household appliances, linking the release mechanisms to human health risks. The release mechanisms of MPs under thermal stress, mechanical abrasion, chemical leaching, and environmental factors, as well as a risk-driven framework for MP release, are summarized. Human exposure through ingestion is the predominant route, while inhalation and dermal contact are additional pathways. In vitro and animal studies have associated MP exposure to inflammatory responses and oxidative stress, neurotoxicity, and genomic instability as endpoints, though direct causal evidence in humans remains lacking, and extrapolation from model systems necessitates caution. This review revealed that dietary intake from kitchen sources is the primary pathway for MP exposure, higher than the inhalation pathway. Most importantly, this review critically sheds light on the initiatives that should be taken by industries with respect to global strategies and new policies to alleviate these challenges. However, while there has been an upsurge in research commenced in this area, there are still research gaps that need to be addressed to explore food matrices such as dairy products, meat, and wine in the context of the supply chain. In conclusion, we pointed out the challenges that limit this research with the aim of improving standardization; research approaches and a risk assessment framework to protect health; and the key differences between MP and nanoplastic (NP) detection, toxicity, and regulatory strategies, underscoring the need for size-resolved risk assessments. Full article

Achieving high reliability remains the critical challenge for pulsed power supplies (PPS), whose core components are susceptible to severe degradation and catastrophic failure due to long-term operation under electrical, thermal and magnetic stresses, particularly those associated with high voltage and high current. This reliability challenge fundamentally limits the widespread deployment of PPSs in defense and industrial applications. This article provides a comprehensive and systematic review of the reliability challenges and recent technological progress concerning PPSs, focusing on three hierarchical levels: component, system integration, and extreme operating environments. The review investigates the underlying failure mechanisms, degradation characteristics, and structural optimization of key components, such as energy storage capacitors and power switches. Furthermore, it elaborates on advanced system-level techniques, including novel thermal management topologies, jitter control methods for multi-module synchronization, and electromagnetic interference (EMI) source suppression and coupling path optimization. The primary conclusion is that achieving long-term, high-frequency operation depends on multi-physics field modeling and robust, integrated design approaches at all three levels. In summary, this review outlines important research directions for future advancements and offers technical guidance to help speed up the development of next-generation PPS systems characterized by high power density, frequent repetition, and outstanding reliability. Full article

Heating, ventilation, and air-conditioning (HVAC) systems dominate energy consumption in hot-climate buildings, where maintaining occupant comfort under extreme outdoor conditions remains a critical challenge, particularly under emerging time-of-use (TOU) electricity pricing schemes. While deep reinforcement learning (DRL) has shown promise for adaptive HVAC control, existing approaches often suffer from comfort violations, myopic decision making, and limited robustness to uncertainty. This paper proposes a comfort-first hybrid control framework that integrates Soft Actor–Critic (SAC) with a Cross-Entropy Method (CEM) refinement layer, referred to as SACEM. The framework combines data-efficient off-policy learning with short-horizon predictive optimization and safety-aware action projection to explicitly prioritize thermal comfort while minimizing energy use, operating cost, and peak demand. The control problem is formulated as a Markov Decision Process using a simplified thermal model representative of commercial buildings in hot desert climates. The proposed approach is evaluated through extensive simulation using Saudi Arabian summer weather conditions, realistic occupancy patterns, and a three-tier TOU electricity tariff. Performance is assessed against state-of-the-art baselines, including PPO, TD3, and standard SAC, using comfort, energy, cost, and peak demand metrics, complemented by ablation and disturbance-based stress tests. Results show that SACEM achieves a comfort score of 95.8%, while reducing energy consumption and operating cost by approximately 21% relative to the strongest baseline. The findings demonstrate that integrating comfort-dominant reward design with decision-time look-ahead yields robust, economically viable HVAC control suitable for deployment in hot-climate smart buildings. Full article

The interaction between moisture and textile materials plays a critical role in transient thermal comfort, particularly through the exothermic heat released during wetting. While the heat of wetting has been extensively characterized at the fiber level, its behavior in finished fabrics, where structure, porosity, and air gaps influence moisture uptake, remains poorly understood. This study quantifies the heat of wetting of clothing fabrics using a TAM Air isothermal microcalorimeter under controlled isothermal conditions (23 °C). Five fabric types representing different fiber chemistries (Merino wool, cotton, viscose, and polyester) were evaluated in both folded and dissected forms to assess the influence of sampling methods. Wool fabrics exhibited the highest heat release, followed by viscose and cotton, whereas polyester showed negligible exothermic response due to its non-hygroscopic nature. Overall, fabric-level heat of wetting values were lower and more variable than the corresponding fiber-level values reported in the literature, reflecting the combined effects of fabric structure, air permeability, surface hydrophilicity, and sampling uniformity. These findings demonstrate the feasibility and limitations of isothermal microcalorimetry for characterizing moisture–fabric interactions and highlight the need for improved sampling and measurement protocols to more accurately capture fabric-level sorption heat relevant to clothing comfort. Full article

The detection of trace nitrogen dioxide (NO₂) is critical for environmental monitoring and industrial safety. Among various sensing technologies, chemiresistive sensors based on semiconducting metal oxides are prominent due to their high sensitivity and fast response. However, their application is hindered by inherent limitations, including low selectivity and elevated operating temperatures, which increase power consumption. Two-dimensional metal oxysulfides have recently attracted attention as room-temperature sensing materials due to their unique electronic properties and fully reversible sensing performance. Meanwhile, their combination with optoelectronic gas sensing has emerged as a promising solution, combining higher efficiency with minimal energy requirements. In this work, we introduce non-layered 2D indium oxysulfide (In₂S_xO_3−x) synthesized via a two-step process: liquid metal printing of indium followed by thermal annealing of the resulting In₂O₃ in a H₂S atmosphere at 300 °C. The synthesized material is characterized by a micrometer-scale lateral dimension with 6.3 nm thickness and remaining n-type semiconducting behavior with a bandgap of 2.53 eV. It demonstrates a significant response factor of 1.2 toward 10 ppm NO₂ under blue light illumination at room temperature. The sensor exhibits a linear response across a low concentration range of 0.1 to 10 ppm, alongside greatly improved reversibility, selectivity, and sensitivity. This study successfully optimizes the application of 2D metal oxysulfide and presents its potential for the development of energy-efficient NO₂ sensing systems. Full article

The proliferation of unmanned aerial vehicles (UAVs) poses escalating security threats across critical infrastructures, necessitating robust real-time detection systems. Existing vision-based methods predominantly rely on single-modality data and exhibit significant performance degradation under challenging scenarios. To address these limitations, we propose DCAM-DETR, a novel multimodal detection framework that fuses RGB and thermal infrared modalities through an enhanced RT-DETR architecture integrated with state space models. Our approach introduces four innovations: (1) a MobileMamba backbone leveraging selective state space models for efficient long-range dependency modeling with linear complexity $\mathcal{O}\left(n\right)$; (2) Cross-Dimensional Attention (CDA) and Cross-Path Attention (CPA) modules capturing intermodal correlations across spatial and channel dimensions; (3) an Adaptive Feature Fusion Module (AFFM) dynamically calibrating multimodal feature contributions; and (4) a Dual-Attention Decoupling Module (DADM) enhancing detection head discrimination for small targets. Experiments on Anti-UAV300 demonstrate state-of-the-art performance with 94.7% mAP@0.5 and 78.3% mAP@0.5:0.95 at 42 FPS. Extended evaluations on FLIR-ADAS and KAIST datasets validate the generalization capacity across diverse scenarios. Full article