Search Results (2,258)

Non-insulated heat exchangers in gas-to-gas service lose substantial energy to the surroundings. This study evaluates Al₂O₃ and ZnO ceramic coatings (200 $\mathsf{\mu }$m) as passive thermal retention layers on the inner surface of the outer tube in a copper double-pipe heat exchanger, using 3D CFD simulations verified for internal consistency against Log Mean Heat Transfer Rate analytical solutions. Six cases were modelled: three coating conditions across parallel-flow and counter-flow configurations under laminar conditions ($R{e}_i\approx 525$, $R{e}_o\approx 192$) with air as the working fluid. The coating elevates the outer tube inner wall temperature $T_3$, increasing the convective driving force to the cold fluid while suppressing ambient dissipation. In parallel flow, Al₂O₃ increases the net inter-fluid heat transfer rate by 35.7% and reduces ambient losses by 81.4%; ZnO achieves 30.9% and 70.4%, respectively. In counter-flow, Al₂O₃ yields a 26.6% enhancement and 73.2% loss reduction. The coated parallel-flow configuration outperforms the uncoated counter-flow baseline. Thermal circuit analysis shows that Al₂O₃ superiority arises from its higher conductivity (40 vs. 19 W m⁻¹ K⁻¹), which sustains a higher equilibrium $T_3$ and a heat partition ratio of 11.84 versus 7.17 for ZnO. These results show that a single ceramic coating layer can recover a large fraction of the thermal energy lost through non-insulated walls, offering a low-cost, retrofit-compatible pathway to improve the energy efficiency of gas-to-gas heat exchangers in HVAC, building energy recovery, and industrial process heat applications. Full article

Solution electrospinning (SES) and melt electrowriting (MEW) are complementary fiber-based fabrication platforms extensively investigated in tissue engineering. SES generates fibers typically ranging from the nanometer to the low-micrometer scale, producing fibrous networks that mimic the native extracellular matrix (ECM) and support key cellular functions. MEW, by contrast, operates solvent-free and enables precise, layer-by-layer deposition of microfibers with well-controlled geometry, conferring the mechanical integrity and open-pore architecture that SES constructs inherently lack. Despite growing interest, the body of peer-reviewed literature reporting original hybrid SES–MEW fabrication and biological outcome data remains limited, with no comprehensive cross-tissue synthesis available to date. This narrative review examines the current state of SES–MEW hybrid strategies across five tissue engineering targets selected for their clinical relevance: skin, vascular grafts, bone, cartilage, cardiac valves, and skeletal muscle. For each application, the architectural rationale, the fabrication approach, and the in vitro and in vivo biological outcomes are discussed in an integrated manner, with attention to how the spatial organization of nano- and microfibers translates into tissue-specific functional responses. A comparative analysis across tissue types highlights both the versatility of hybrid constructs and their persistent limitations, including suture retention values that remain below clinically accepted thresholds in vascular applications, incomplete cellular infiltration through dense nanofibrous layers, and the absence of validated, reproducible scale-up protocols compatible with clinical-grade manufacturing. The review concludes by identifying the most critical open questions in the field, encompassing process standardization, regulatory classification, and the emerging role of machine learning in closed-loop MEW process optimization. This work aims to provide an evidence-based perspective on the current state of hybrid SES–MEW scaffold engineering and the key translational gaps limiting clinical application. Full article

Modern agriculture depends heavily on machinery to maximize operational efficiency and, consequently, profitability, but the wear-and-tear on the mechanical components of machinery due to ageing can lead to reduced efficiency, more downtime, and higher maintenance expenses, thus raising the operative costs. These problems have been addressed by the use of specific lubricant additives for machinery; however, additives have known disadvantages, such as compatibility restrictions and environmental concerns, which represent critical issues especially in case of possible dispersion in the environment. Modern industry is always looking for techniques and solutions to increase efficiency and productivity, and this study investigates the possible advantages of employing nanotechnology in lubricant formulations. Amongst all possible substances, SiO₂ nanoparticles are increasingly promising as lubricant additives due to their unique properties, which include heat resistance, high levels of stability, and good biocompatibility. Moreover, biolubricants, derived from renewable sources, offer an environmentally friendly alternative to conventional lubricants. This article contributes to the field of agricultural technology by demonstrating the potential of SiO₂ nanoparticles in formulations of biolubricants thought to be used in agricultural machines. Key degradation parameters, including density, viscosity, total acid number (TAN), total base number (TBN), oxidation, and elemental composition, were systematically analysed. The results showed that SiO₂ nanoparticles mitigate viscosity loss and density increase, optimize TAN and TBN, reduce oxidation of the biolubricants by up to 17.7% at 1.00 wt% SiO₂, and stabilize elemental composition during ageing. Nanoparticles remained uniformly dispersed without sedimentation for over 30 days. This provides insights that can prevent machinery performance degradation over time, reduce lubricant changes, and suggest a more sustainable and environmentally friendly lubrication solution, thus promoting more sustainable industry. Full article

In global navigation satellite systems (GNSS), the system time reference is maintained by the ground control segment and kept traceable to UTC, enabling inter-system compatibility and interoperability. Advances in onboard atomic-clock stability and inter-satellite time transfer accuracy make it feasible for a constellation to autonomously realize a space-based time reference, with periodic traceability updates and steering via satellite–ground links to enhance resilient time maintenance. BeiDou-3 (BDS-3) carries high-performance onboard hydrogen masers and Ka-band inter-satellite links (ISL) for time transfer, providing stable frequency sources and high-precision time transfer capability for establishing a space-based time reference. Using in-orbit BDS-3 clock offset data, we propose a space-based autonomous timekeeping approach that combines high-precision ISL synchronization with timekeeping by a small ensemble of hydrogen masers, together with a space–ground cooperative strategy with BeiDou time (BDT). The approach first performs constellation-wide synchronization using ISL, then selects a timekeeping ensemble based on in-orbit clock performance to generate a space-based ensemble atomic timescale, denoted TA(SPACE); when satellite–ground links are available, TA(SPACE) is steered to BDT to maintain consistency with the ground time reference. Based on this space-based time reference, satellite clock offsets are predicted to generate clock-parameter products. Experiments show that, in the autonomous mode, the time offset between TA(SPACE) and BDT is kept within 25.06 ± 41.47 ns over 90 days, whereas in the space–ground cooperative mode, satellite–ground steering stabilizes the offset within 10 ns. The proposed approach provides a practical solution for constellation time maintenance under disruptions such as anomalous ground injection, improving the resilience and reliability of GNSS services. Full article

Municipal solid waste (MSW) landfill site selection is a complex multi-criteria decision-making (MCDM) problem involving uncertainty and conflicting criteria. Although spherical fuzzy extensions of the Technique for Order Preference by Similarity to Ideal Solution (SF-TOPSIS) are widely used, existing studies rely on conventional distance measures that do not fully capture the geometric structure of spherical fuzzy sets. To address this limitation, this study proposes an enhanced SF-TOPSIS framework incorporating a novel spherical distance measure to improve consistency, discrimination capability, and structural compatibility. The framework integrates Spherical Fuzzy Weighted Arithmetic Mean (SWAM) and Spherical Fuzzy Weighted Geometric Mean (SWGM) operators and evaluates robustness using Spearman rank correlation. Additionally, a coefficient of variation (CV)-based analysis is conducted to examine the dispersion of closeness coefficients. The applicability of the approach is demonstrated through a landfill site selection case; however, the main contribution lies in a generalized distance-based formulation applicable to various MCDM problems. Results show that the proposed distance improves agreement between aggregation operators, increasing correlation values from 0.905 to 0.976, while producing a more stable distribution of closeness coefficients. Overall, the study advances spherical fuzzy MCDM by introducing a geometrically consistent distance formulation. Full article

Pelvic organ prolapse (POP) is a common benign gynecological disorder that substantially affects quality of life, particularly in aging female populations. Current management strategies, including standardized vaginal pessaries and synthetic surgical meshes, are often limited by poor anatomical adaptability, mechanical mismatch with native pelvic tissues, and long-term safety concerns. These limitations have driven increasing interest in personalized and biomechanically compatible therapeutic solutions. Three-dimensional (3D) printing, also known as additive manufacturing, has emerged as a promising bioengineering technology to address these unmet clinical needs. By enabling layer-by-layer fabrication directly from digital models, 3D printing allows for precise control over device geometry, mechanical properties, and material composition, facilitating patient-specific design. This narrative review summarizes recent progress in 3D printing for POP management across three major application domains: (i) next-generation meshes based on biodegradable polymers, elastomeric materials, natural biomaterials, and hydrogel systems; (ii) customized vaginal pessaries tailored to individual pelvic anatomy using imaging-assisted workflows; and (iii) imaging-based pelvic models and prototype devices for surgical planning, education, and exploratory assessment. Overall, existing studies demonstrate that 3D printing enables improved biomechanical compatibility, enhanced tissue integration, and multifunctional device design, including drug delivery capability. Although current evidence is largely pre-clinical or based on pilot studies, additive manufacturing holds strong potential to advance POP management toward safer, personalized, and functionally optimized clinical solutions. Full article

Emergency locator transmitters (ELTs) are key safety systems for post-crash aircraft localization and search-and-rescue operations. In more electric aircraft (MEA), however, their design and operation are increasingly influenced by complex electrical architectures, tighter equipment integration, and more demanding electromagnetic environments. This paper presents a narrative literature review of ELT technology from a MEA-oriented perspective. A practice-oriented narrative approach is adopted, examining ELTs through a dual lens: the evolution of the search and rescue (SAR) ecosystem and the progressive electrification of aircraft systems. The review addresses ELT fundamentals, classifications, operating principles, and interaction with the Cospas-Sarsat infrastructure, and examines the transition from legacy analog beacons to modern 406 MHz digital systems incorporating GNSS positioning, MEOSAR capabilities, second-generation beacon functionalities, and distress tracking features. Particular attention is given to integration challenges in MEA platforms, including autonomous energy supply, battery endurance, power quality disturbances, electromagnetic compatibility, installation robustness, antenna survivability, and certification constraints. The analysis highlights that ELT performance in MEA depends not only on the beacon itself, but also on the coupled interaction among device design, installation conditions, and the electrical environment. Finally, the review outlines research priorities for next-generation ELTs, including improved survivability assessment, energy-aware architectures, integration strategies based on electromagnetic compatibility, and certification-ready solutions compatible with future aircraft platforms. Full article

Masonry arch bridges are critical assets in aging transportation networks, yet their Structural Health Monitoring (SHM) remains challenging. Smart bricks—piezoresistive sensing units compatible with masonry structures and capable of acting simultaneously as load-bearing components and strain sensors—offer a promising solution for embedding self-sensing capability directly within the masonry. While previous work by the authors has investigated their use in masonry walls, their application to arched structures remains unexplored. This gap is particularly significant given that arches, characterized by a predominantly compressive stress state, represent a natural context for smart-brick implementation. This study presents a numerical investigation assessing the potential of smart bricks for strain-based SHM of masonry arch bridges. A Finite Element (FE) model, derived from a validated experimental benchmark representative of typical Italian railway arch bridges, was used to virtually embed smart bricks at selected cross-sections along the arch. Damage progression was simulated through cyclic loading–unloading stages, enabling direct correlation between strain evolution and structural deterioration. Results demonstrate that smart bricks accurately capture damage-driven strain redistributions, closely mirroring both the sequence of damage formation and the associated collapse mechanism. These findings support the use of smart bricks for early detection of localized structural changes in masonry arches, providing a foundation for future experimental validation and real-world deployment of minimally invasive SHM systems. Full article

Zinc oxide (ZnO) is currently one of the most significant wide-bandgap semiconductor materials, attracting extensive research across diverse fields including materials science, chemistry, physics, medicine, electronics, and power engineering. Its exceptional properties, such as high optical transparency, high electron mobility, chemical stability, and compatibility with low-cost fabrication techniques, have established ZnO as a versatile material with immense application potential. A critical application for ZnO is its role as a transparent conducting oxide (TCO) in modern optoelectronic and photovoltaic devices, as well as in sensors, transparent electronics, and spintronics. To meet the requirements of these advanced applications, precise control over the structural, optical, and electrical properties of ZnO thin films is essential. This is effectively achieved through the selection of specific synthesis methods and intentional modification techniques, such as doping. This review provides a comprehensive overview of the synthesis and modification of ZnO thin films, with a particular focus on how various dopants influence their fundamental characteristics. The work discusses a range of deposition techniques, including physical vapor deposition (PVD), chemical vapor deposition (CVD), atomic layer deposition (ALD), sol–gel methods, spray pyrolysis, and other solution-based approaches. The novelty of this review lies in its comparative analysis of different doping strategies combined with various thin-film deposition techniques, highlighting how specific synthesis routes influence dopant incorporation and ultimately determine functional properties. Furthermore, recent advances in tailoring ZnO thin films are summarized, alongside the identification of key challenges and future research directions. Ultimately, this work aims to provide researchers with a systematic perspective on the synthesis–structure–property relationships in doped ZnO thin films to support the development of optimized materials for next-generation electronic and optoelectronic devices. This review, thus, serves as a comprehensive reference for researchers and engineers seeking to optimize the functionality of ZnO-based thin films for emerging technological applications. Full article

Illegal drone intrusion near airport runways poses a critical threat to civil aviation safety, creating an urgent need for runway-side vision systems that can detect intruding UAVs early enough for safety warning and collision-risk mitigation. However, the development of such detectors is severely hindered by the scarcity of annotated real-world data in this high-security scenario. To address this bottleneck, we present SynthAirDrone, the first high-fidelity synthetic dataset for UAV intrusion detection in airport runway environments, together with an intelligent data generation framework integrating scene-aware placement and multi-criteria quality assessment. The proposed method uses sky-region segmentation to guide physically plausible drone placement, and combines perspective-aware scaling, Poisson image editing, and a four-dimensional quality scoring system—covering sky overlap, lighting consistency, size plausibility, and edge continuity—to improve visual plausibility and semantic consistency. The resulting dataset comprises 6500 high-quality images, all annotated in YOLO-compatible format. Using the lightweight YOLOv11n model, we show that models trained solely on SynthAirDrone exhibit non-trivial cross-domain transfer to Anti-UAV, while mixed training with limited real data provides the strongest real-world performance under the present setting. Ablation studies further confirm that a quality threshold of $\tau =0.6$ achieves the best trade-off between diversity and fidelity. Overall, this work delivers a reproducible and efficient synthetic data solution for UAV detector development in high-security, data-scarce airport-runway scenarios. Full article

The weight of battery modules keeps hindering them from being commercially attractive as the sole power supply for short-range electric passenger flights. Furthermore, the challenging requirements for aerospace applications limit the range of options for module elements and complicate the implementation of lightweight solutions. Hence, the objective of this study is to elaborate and evaluate concepts for battery modules to identify promising solutions for electrified aircraft propulsion systems. For that purpose, a house of quality is compiled to assess the relations between options for module elements and module requirements, as well as correlations between options. Potential concepts are elaborated by combining suitable elements. Finally, the concepts are evaluated to highlight the most preferable and compatible ones for aircraft battery modules. Full article

The rapidly growing concern over the hazardous impact of phthalates on the environment and public health has led to a critical need for alternative and environmentally friendly plastics. Plasticizers developed from natural materials represent one possible solution. This paper explores four types of renewable feedstocks (sorbitol/polyols, glycerin, cardanol from cashew nutshell liquid, and limonene from citrus peels) as sources for developing alternative plasticizer systems. Key areas explored include the type of feedstock utilized, the methods used for extracting or processing the feedstocks, the nature of the chemical modification processes (e.g., esterification, epoxidation, etherification, or reactive grafting) applied to generate the respective plasticizers, and the resultant physical and mechanical properties. The performance of each plasticizer system in polymers such as PVC, PLA, and polysaccharide-based bioplastics is evaluated, alongside the compatibility with biological tissues, toxicological properties, biodegradability, and chemical migration into food simulants. The feasibility of each family of plasticizers is also assessed from an economic perspective, including availability of the feedstocks, economies of scale associated with large-volume production, and competitive pricing relative to established petroleum-derived plasticizers. Overall, sorbitol/polyol and glycerin derivative families have reached a level of maturity that provides a good balance of processability, food-contact safety, and biodegradability. Cardanol-based systems provide an attractive option where aromatic functional groups and combined plasticization–stabilization effects are needed. Limonene-derived plasticizer systems appear promising for use in PLA, but their broader utility may be limited by volatility, strong odors, and susceptibility to oxidation. Common issues identified across all four families include chemical migration into food products, regulatory approval, and the need for detailed life-cycle assessments. Full article

Rapid and accurate calculation of lightning-induced electric fields in complex terrain is essential for lightning protection and electromagnetic compatibility analysis. Although conventional full-wave numerical methods such as the finite element method can achieve high-fidelity results, they are computationally expensive and inefficient for large-scale or repetitive engineering analysis. To enable efficient and reliable computation of lightning-induced electrostatic fields over complex terrain, this paper proposes a fast computational framework that integrates multi-level conformal mapping with a multi-objective optimization strategy based on the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). In the proposed method, irregular terrain boundaries are transformed into analytically tractable domains using multi-level conformal mapping, while the critical mapping parameter is reformulated as a dual-objective optimization problem that simultaneously minimizes the maximum local error and the mean global error. Unlike traditional approaches that rely on empirical tuning or exhaustive traversal of mapping parameters, the proposed framework establishes a closed-loop adaptive optimization process that generates a Pareto-optimal solution set, enabling flexible trade-off selection according to practical accuracy requirements. The method is validated against high-fidelity finite element simulations for representative terrain profiles. The results demonstrate that the proposed approach achieves comparable maximum-error performance while reducing mean error and significantly improving parameter-optimization efficiency relative to exhaustive search methods. The proposed framework provides an adaptive and efficient computational solution for preliminary assessment of lightning-induced electric fields in complex terrain environments, and lays a foundation for future extensions toward more realistic multi-dimensional and transient analyses. The improvements in computational accuracy and efficiency offer significant practical value for rapid lightning protection assessment in large-scale complex terrain engineering, enabling parametric analysis and scheme comparison during the preliminary engineering design stage with sufficient reliability. Full article

Marine biofouling remains a major challenge for maritime industries, affecting submerged structures and vessels worldwide. The long-standing reliance on biocidal coatings, together with their documented environmental impacts, has led to increasingly restrictive regulations and an urgent demand for environmentally compatible antifouling (AF) solutions. This study evaluates the AF potential and toxicological profile of two nucleoside analogues, hypoxanthine arabinoside (1′) and 2′-deoxyinosine (2′), selected based on the previously reported non-lethal AF activity of the naturally occurring nucleosides adenosine and 2′-deoxyadenosine from cyanobacteria. Both analogues inhibited the growth of Navicula sp. by approximately 60% without inducing mortality and significantly reduced settlement of Mytilus galloprovincialis plantigrades, with EC₅₀ values of 5.50 µM (1′) and 8.54 µM (2′), and no lethality detected (LC₅₀ > 200 µM). At near-EC₅₀ concentrations, both compounds increased acetylcholinesterase and tyrosinase activities, supported by molecular docking results, suggesting involvement of neurotransmission- and byssal formation-related pathways. Proteomic analysis revealed compound-specific molecular responses. No lethal effects were observed in non-target organisms (LC₅₀ > 32 µM for A. amphitrite and LC₅₀ > 50 µM for A. salina), and environmental fate modelling predicted low bioaccumulation and rapid degradation. Overall, substitution of the amino group by a carbonyl group preserved AF efficacy without increasing toxicity, highlighting nucleosides as promising low-toxicity AF agents. Full article

All-inorganic cesium lead iodide (CsPbI₃) has been investigated for more than a decade as an absorber for perovskite photovoltaics thanks to its attractive bandgap, thermal robustness compared with hybrid perovskites, and compatibility with tandem concepts. Yet, despite remarkable efficiency progress, CsPbI₃ remains far from widespread commercialization. The core roadblock is the metastability of the photoactive black perovskite phases (α/γ/β) against transformation to the photoinactive yellow δ-phase under realistic conditions, amplified by defect chemistry, ion migration, and interfacial reactions. Additional barriers arise from scale-up constraints (film uniformity, throughput, solvent management), long-term operational stability (humidity, heat, UV, bias), and environmental/safety requirements, especially lead containment, sequestration, and end-of-life strategies. This review critically analyzes the intertwined physical, chemical, and engineering factors that still limit CsPbI₃ deployment, with emphasis on how solutions in one domain can fail without co-design in others. This review summarizes state-of-the-art stabilization strategies (size/strain engineering, additive/doping routes, surface/interface passivation, and encapsulation), highlight scalable manufacturing pathways including solvent-minimized and vacuum-assisted approaches, and discuss lead-mitigation technologies such as Pb-adsorbing functional layers. Finally, I argue that artificial intelligence (AI)—from machine-learning stability models to process monitoring, robotic optimization, and digital twins—has become essential to navigate the enormous parameter space of CsPbI₃ materials and manufacturing. It concludes with actionable recommendations and future directions toward bankable, scalable, and sustainable CsPbI₃ photovoltaics. Full article