Search Results (30,623)

NO₂ sensing is shifting from the optimization of individual receptor materials toward integrated systems in which surface chemistry, interfacial charge transfer, transducer architecture, operating environment, and regeneration jointly determine performance. This review argues that deployment readiness is set not by peak response but by the coupled performance of five layers: (i) receptor and interface chemistry, (ii) transducer and device architecture, (iii) gas delivery and environmental conditions, (iv) regeneration and aging, and (v) calibration, uncertainty, and system integration. Within this mechanism-to-deployment framework, we examine how oxygen adsorption, depletion and accumulation layers, heterojunction and Schottky barriers, defects, catalytic sensitization, and percolation govern the electrical signal across metal oxides, carbon materials, transition-metal dichalcogenides, MXenes, porous and MOF-derived architectures, and organic semiconductors and how MEMS microheaters, FET/TFT/MOSFET transducers, flexible platforms, optical and electrical regeneration, and AI-assisted arrays read it out. Despite this progress, translation remains limited by environmental interference, incomplete recovery, transport-dependent response, aging, and device-to-device variability so that record responses seldom survive realistic operation. Reliable NO₂ monitoring therefore requires application-specific validation of the complete measurement cycle—exposure, readout, recovery, environmental perturbation, calibration, and long-term operation—rather than isolated sensitivity metrics. Full article

The rapid advancement of information technology and pervasive use of electronic devices has exacerbated electromagnetic radiation pollution and interference, driving the demand for lightweight, flexible, and high-efficiency electromagnetic shielding materials in materials research. As a high-performance elastomer, thermoplastic polyurethane (TPU) possesses excellent elasticity, wear resistance, oil resistance and processability, making it promising for flexible electronics and wearable devices. However, pure TPU is electrically insulating and exhibits nearly no electromagnetic shielding capability, which requires conductive filler incorporation for functional modification. Herein, ternary TPU/MWCNT/BiFeO₃ composites were fabricated via solution blending and hot pressing, using multi-walled carbon nanotubes (MWCNTs) and bismuth ferrite (BiFeO₃) as conductive and dielectric fillers within the TPU matrix. The effects of filler content on the microstructure, thermal stability, mechanical properties and electromagnetic shielding performance of composites, together with the relevant mechanisms, were systematically studied. For the ternary TPU/MWCNT/BiFeO₃ system, the introduction of BiFeO₃ continuously increases the char residue rate of the composites to 16.01%, while accelerating the reaction process during the main thermal decomposition stage. The mechanical properties gradually deteriorate with the increase in BiFeO₃ content, and the composite with 5 wt% BiFeO₃ almost loses its elastomeric characteristics. The electromagnetic shielding effectiveness (SE) presents a trend of initial increase and subsequent decrease. The composite with 3 wt% BiFeO₃ exhibits the optimal shielding performance, with a 24.7% enhancement in total SE compared with the reference TPU/MWCNT composite containing 1% MWCNT. This improvement is attributed to the interfacial polarization and dipole polarization induced by the appropriate amount of BiFeO₃, which effectively strengthen the electromagnetic wave absorption loss capacity of the composites. Full article

In this work, a sustainable approach is proposed for upcycling recycled Acrylonitrile–Butadiene–Styrene (ABS) derived from electrical and electronic waste (e-waste) through a combination of electron beam irradiation (EBI) technique and halloysite nanotubes (HNTs) used as reinforcement. The study reveals that the application of EBI at an optimal dose of 10 kGy enhances the tensile properties of unfilled e-waste ABS, achieving an increase of almost 9% in tensile strength (TS) and about 40% in Young’s modulus (E). Incorporating 5 wt% HNTs into e-waste ABS not only improves the thermal stability of the composite material, but also modifies its behavior towards irradiation, shifting the optimal dose to 5 kGy. Another effect of the combination of HNTs and irradiation is noted with regard to the increase in storage modulus (E’). The findings present a promising and eco-friendly route to transform e-waste ABS into a higher-value engineering material. Full article

Global demand for alfalfa, a vital forage resource for ruminants, is growing. Currently, ruminant production is expanding rapidly in parts of Asia and Africa, further driving demand for high-quality alfalfa forage. Nevertheless, long-term indiscriminate fertilization and imbalanced nutrient input ratios in alfalfa production not only lower fertilizer use efficiency and crop productivity but also induce a range of soil degradation and environmental issues, thereby constraining the sustainable development of the forage-livestock industry. In this study, the alfalfa cultivar ‘Xinmu No. 4’ (Medicago sativa cv. ‘Xinmu No. 4’) was used as the experimental material. A two-year field block experiment was performed to investigate the effects of different organic–inorganic fertilizer ratios on the nutrient use efficiency of alfalfa, with six fertilization treatments: CM0 (100% cow manure), CM1 (75% cow manure + 25% chemical fertilizer), CM2 (50% cow manure + 50% chemical fertilizer), CM3 (25% cow manure + 75% chemical fertilizer), CM4 (100% chemical fertilizer), and CK (no fertilization application). The results demonstrated that the CM3 treatment (25% cow manure combined with 75% chemical fertilizer) significantly enhanced nitrogen, phosphorus, and potassium accumulation in alfalfa relative to the CK, sole cow manure (CM0), and sole chemical fertilizer (CM4) treatments (p < 0.05). Additionally, plant nutrient accumulation in 2025 was markedly higher than that in 2024 across treatments (p < 0.05). Combined organic and inorganic fertilization substantially improved the agronomic use efficiency of nitrogen, phosphorus, and potassium in alfalfa, with the CM3 ratio exhibiting the most pronounced beneficial effect. For alfalfa cultivation in Xinjiang, the combined application of 25% cow manure and 75% chemical fertilizer is recommended to optimize nutrient accumulation and utilization efficiency, ultimately boosting alfalfa yield and quality. Full article

Digital twins (DTs) based on agent-based artificial intelligence (Agentic AI) provide a transformative framework for streamlining nondestructive testing (NDT) of 3D-printed rehabilitation equipment. This study applies a conceptual research methodology based on the integration and analysis of recent advances in Agentic AI, digital twin architectures, additive manufacturing, NDT technologies, and intelligent rehabilitation systems to establish a framework for autonomous quality monitoring and lifecycle management of 3D-printed medical devices. By creating intelligent virtual replicas of physical devices, these systems enable continuous monitoring of structural integrity, functional performance, and degradation mechanisms throughout the product lifecycle. Unlike conventional AI-based DTs, Agentic AI-driven DTs can autonomously perceive, reason, plan, and execute corrective actions based on real-time sensor data, NDT results, manufacturing information, and historical knowledge. The main conclusion of this work is that Agentic AI-enhanced DTs have the potential to transform NDT from a passive inspection approach into an intelligent, predictive, and autonomous decision-support system for rehabilitation equipment. Advanced machine learning and autonomous decision-making algorithms enable the identification of early signs of material degradation, manufacturing defects, fatigue accumulation, and performance anomalies, supporting predictive maintenance and proactive quality assurance. Integrating Agentic AI DTs with additive manufacturing processes enables real-time optimization of printing parameters, adaptive process control, and continuous refinement of inspection strategies without production interruption or destructive sampling, thereby supporting Industry 4.0 and smart manufacturing principles. The main innovation of this research lies in proposing an autonomous closed-loop framework that combines Agentic AI, DTs, additive manufacturing, and NDT into a unified system capable of continuous learning, reasoning, and operational optimization. Compared with existing studies that mainly focus on AI-assisted defect detection or static digital twin models, this approach introduces autonomous agents capable of coordinating sensing, simulation, diagnosis, prediction, and corrective actions across the entire lifecycle of 3D-printed rehabilitation devices. The proposed concept extends current digital twin applications by incorporating virtual stress testing, autonomous simulation, patient-specific customization, and adaptive device management, reducing dependence on physical prototypes, minimizing material waste, and accelerating design validation. By combining autonomous reasoning with predictive analytics, Agentic AI-based DTs represent a next-generation solution for intelligent, adaptive, and sustainable nondestructive testing, advancing both additive manufacturing technologies and personalized rehabilitation engineering. Full article

Lithium aluminosilicate (LAS) ultra-low-expansion glass ceramics are core materials for precision optical systems, whose quality and dimensional stability are critically constrained by the uniformity of the coefficient of thermal expansion (CTE). This work proposes a nondestructive ultrasonic immersion pulse reflection (UIPR) method for rapid and low-cost characterization of the CTE in LAS glass ceramics. Key parameters of the ultrasonic measurement system are optimized via finite element method (FEM) simulations and experimental validation. Employing the correlation method, the ultrasonic longitudinal wave velocity is measured in LAS glass ceramic samples with distinctly different CTE values. The proposed method achieves an ultrasonic longitudinal wave velocity measurement uncertainty of 0.49 m/s, contributing 4.78 ppb/°C to the overall uncertainty of ultrasonic CTE determination. Within the investigated sample set, a negative relationship is observed between ultrasonic longitudinal wave velocity and the mean CTE (0–50 °C). The linear fit yields a slope of −9.75736 (ppb/°C)/(m/s), with a Pearson correlation coefficient of −0.84303. Featuring noncontact and nondestructive capabilities, this method lays a solid methodological foundation for CTE evaluation and efficient iterative optimization of material fabrication processes. Meanwhile, it shows great potential for rapid full-aperture characterization of CTE uniformity in large-size LAS glass ceramics. Full article

Tin-based halide perovskites have emerged as one of the most promising classes of lead-free materials for next-generation photovoltaic technologies. Their favorable optoelectronic properties, narrow band gaps, and structural compatibility with the ABX₃ perovskite framework position them as viable alternatives to conventional lead-based absorbers. This review summarizes the fundamental structural principles governing Sn-based perovskites, including the role of A-site cations, halide composition, tolerance factor, and octahedral distortion in determining phase stability and electronic structure. Recent advances in material engineering—such as additive-assisted crystallization, interface modification, precursor chemistry optimization, and two-dimensional/three-dimensional heterostructure formation—have significantly improved film quality, reduced defect densities, and enhanced device performance. Despite these achievements, challenges remain, particularly the spontaneous oxidation of Sn²⁺ to Sn⁴⁺, uncontrolled crystallization, and limited operational stability. Strategies aimed at stabilizing the Sn²⁺ oxidation state, suppressing self-doping, and improving charge transport are discussed in detail. The review also highlights the strategic importance of tin as a sustainable element for renewable energy technologies and provides an overview of global tin resources relevant to future photovoltaic deployment. Overall, tin-based perovskites represent a compelling pathway toward environmentally responsible and high-efficiency solar cells, with continued research expected to accelerate their transition from laboratory materials to commercially viable technologies. Full article

South Africa is host to a significant number of young migrants who are in institutional care. This study aimed to understand how migrant youth access care, who provides it and their views about the quality of care they receive, given the precarity of urban life in South African cities. The study used a mixed methods, explanatory, sequential research design. In this paper, we present some of the research findings that help understand how young migrants access care in contexts of urban self-settlement and how they create family through everyday care practices to meet their needs. The results show that they maintain ties with family members and meet their needs through a combination of NGO-provided material support and family-provided emotional support. Notably State support was largely absent, making it impossible to meet their needs when the State had a monopoly on service provision (such as documentation and asylum). Being listened to and being able to take decisions regarding their care were extremely important to young migrants and were significantly correlated with better optimism for the future, happiness with the services they receive and optimism for life in South Africa. These findings underscore the adaptive and largely effective ways that young migrants and families meet their care needs in a precarious urban setting. They provide important understanding to ensure that the design of services for young migrants recognise existing care practices that are effective and support rather than supplant them. Full article

Thermal energy storage (TES) technologies are essential for renewable energy integration, industrial waste heat recovery, grid flexibility, and improved energy efficiency. Despite advances in sensible heat thermal energy storage (SHTES), latent heat thermal energy storage (LHTES), and thermochemical energy storage (TCES), practical deployment remains constrained by inadequate heat transfer rates, which limit charging and discharging processes, reduce storage utilization, and increase system size and cost. Conventional heat-transfer enhancement approaches, including fins, embedded heat exchangers, conductive additives, porous structures, and flow intensification techniques often introduce trade-offs related to manufacturability, complexity, durability, and energy consumption. Additive manufacturing (AM) has emerged as a promising approach for overcoming these limitations by enabling precise control of internal geometry, porosity, surface-area-to-volume ratio, and fluid pathways. Through the fabrication of architected structures, lattice networks, triply periodic minimal surface (TPMS) geometries, and multifunctional heat-transfer architectures, AM enables geometry-driven optimization of thermal performance that is difficult to achieve using conventional manufacturing methods. These capabilities support the development of compact TES systems with enhanced heat transfer, improved thermal uniformity, and increased energy utilization. This review examines additive manufacturing technologies relevant to TES applications, including powder bed fusion, directed energy deposition, material extrusion, vat photopolymerization, and binder jetting. The relationships among manufacturing processes, material selection, and thermal performance are discussed across SHTES, LHTES, and TCES systems. Particular emphasis is placed on AM-enabled heat-transfer enhancement strategies, phase change material (PCM)-integrated structures, architected thermal networks, embedded heat exchangers, and computational design methodologies such as topology optimization. Current challenges involving material compatibility, scalability, cost, and long-term durability are also evaluated. The review highlights how additive manufacturing is transforming TES design from a material-centered paradigm toward geometry-enabled thermal engineering, creating new opportunities for next-generation energy storage systems. Full article

Topology optimization is an effective method for obtaining high-performance material distributions with novel configurations. However, its application to complex electromagnetic devices remains challenging because of the difficulty of deriving sensitivities and the low computational efficiency associated with repeated finite element method (FEM) evaluations for nonlinear materials. This paper proposes an efficient gradient-free topology optimization method that integrates superellipse curves with a multilayer perceptron (MLP) surrogate model while accounting for nonlinearity. First, based on the general superellipse curve, an improved expression is introduced, in which the size, shape, and position can be flexibly controlled by only seven parameters. Then, a parameterized superellipse-curve-based gradient-free topology optimization framework is established, which can be applied to complex electromagnetic devices with nonlinear materials and complex objective functions. Moreover, a lightweight MLP-based surrogate model is constructed using limited training samples generated by Latin hypercube sampling and FEM, and it can replace FEM for evaluating nonlinear material behavior with negligible computational cost. Finally, the proposed topology optimization framework is applied to the design of a magnetic actuator, both with and without considering nonlinear B–H characteristics, demonstrating its effectiveness. Full article

This study develops an analytical–evolutionary framework for optimizing the dynamic efficiency of bidirectional porous functionally graded beams. Touratier’s higher-order shear deformation theory is coupled with a real-coded genetic algorithm. The material-gradation indices in the thickness and width directions, the porosity coefficient, and the cross-sectional aspect ratio are treated as four coupled design variables. Dynamic efficiency is defined as the first modal frequency per unit mass, J = f₁/m (Hz/kg), with f₁ evaluated at β₁ = π/L for the simply supported finite beam. Uniform and non-uniform porosity laws are examined under three admissible design domains. After correcting and consistently implementing the modified rule of mixtures, the restricted-domain efficiencies are 117.819 and 96.766 Hz/kg for uniform and non-uniform porosity, respectively. Extending the material-gradation bounds increases them to 920.823 and 328.627 Hz/kg, while extension of the geometric domain gives 2302.058 and 821.568 Hz/kg. Thirty independent GA runs for each case yield 100% success under a 0.5% tolerance. Deterministic corner and one-at-a-time sampled checks confirm the observed boundary-directed trends within the investigated boxes. The results are mathematical optima for the stated objective and constraints, not production-ready designs. Full article

Addressing the challenges associated with partial renovation of existing residential interiors, including ordinary homeowners’ incomplete expression of design needs, limited access to professional design support, and the inability of conventional AIGC tools to accurately interpret complex design requirements, this study proposes an AI Agent-assisted design method for partial interior renovation. An AI Agent workflow was developed to establish an integrated process encompassing requirement acquisition, design semantic mapping, and design-scheme generation. The workflow automatically transforms natural-language requirements into structured design information and improves the quality and consistency of generated designs through multimodal information analysis and prompt-weight optimization. Experimental results show that the AI Agent-assisted method achieves improvements in requirement alignment, spatial structure preservation, spatial aesthetics, and generation stability. SUS analysis indicates that this method can provide relatively accessible design decision support for non-professional users. Overall, this study demonstrates that AI Agent-assisted human–AI collaborative design has the potential to support homeowners in independently designing and refining partial residential interior renovation schemes. Although this study did not directly measure indicators such as material consumption, embodied carbon, or service-life extension, the proposed workflow may also offer a potential decision-support pathway for more efficient and incremental renovation of existing homes. Full article

The optimization of agro-industrial products represents a key strategy to enhance their technological quality, stability, and market acceptance. The aim of this study was to evaluate the effect of different proportions of Allium ampeloprasum (elephant garlic, E) and Allium sativum genotypes Roselló 1 (R) and Taiwan 5 (T) on the nutritional, physicochemical, functional, rheological, and sensory properties of garlic paste formulations. Binary mixtures were prepared at E:A. sativum ratios of 25:75, 50:50, and 75:25 for each genotype, together with pastes containing 100% of each garlic material, resulting in nine formulations. The results showed that mixture proportion and A. sativum genotype influenced several product attributes. Among the mixtures, E₂₅T₇₅ showed the highest protein content (4.37%), whereas E₅₀T₅₀ exhibited the highest antioxidant capacity (41.71 ± 0.94 µmol TE 100 g⁻¹). Syneresis was significantly affected by formulation, storage time, and their interaction (p < 0.001), demonstrating formulation-specific changes during the 21-day storage period. Quadratic Scheffé mixture modeling showed a significant positive deviation from additivity for antioxidant capacity in the E + T system (β₁₂ = 19.0, p = 0.019), whereas the E + R system was consistent with additive behavior (β₁₂ = −10.2, p = 0.455). In the sensory analysis, the first two principal components explained 83.5% of the total variability, with Dim1 (49.4%) associated mainly with color and texture and Dim2 (34.1%) with flavor and aroma. Among the mixtures, E₇₅T₂₅ showed the highest mean aroma score (3.57), whereas E₇₅R₂₅ and E₂₅T₇₅ showed the highest mean flavor scores (3.45 and 3.48, respectively). Overall, sensory responses varied according to both mixture proportion and A. sativum genotype, with no single formulation maximizing all evaluated attributes. These findings demonstrate that combining A. ampeloprasum with different A. sativum genotypes generates formulation-specific technological, functional, and sensory responses. Full article

HVOF coatings based on tungsten and chromium carbides are widely used in aerospace, energy, and oil and gas industries. However, the selection between the wear resistance of WC–Co and the corrosion resistance of Cr₃C₂–NiCr is often hindered by a lack of systematic data on the effect of powder particle size. In this study, WC–12Co and Cr₃C₂–NiCr coatings were deposited onto 12Kh18N10T stainless steel substrates by HVOF spraying using three particle size fractions: <20, 20–32, and 32–40 μm. Individual spray parameters were selected for each material to ensure high-quality deposition (standoff distance 350 mm, one pass for WC–12Co; 250 mm, two passes for Cr₃C₂–NiCr). The influence of powder particle size distribution on coating properties was investigated using a comprehensive set of methods, including scanning electron microscopy, X-ray diffraction with Rietveld quantitative phase analysis, microhardness testing, tribological testing, electrochemical measurements, and numerical modeling of particle in-flight motion. It was found that the 20–32 μm fraction is optimal for both materials. Different degradation mechanisms were identified: for WC–Co, decarburization of WC with the formation of W₂C and η-phases dominates (maximum for the <20 μm fraction); for Cr₃C₂–NiCr, oxidation and carbide dissociation prevail (in the <20 μm fraction—13.7% Cr₂O₃ and 38.6% Cr₇C₃), leading to low coating thickness (~16 μm) due to loss of ductility and wettability. Numerical modeling confirmed that the high velocity of fine Cr₃C₂–NiCr particles (~680–720 m/s) does not compensate for their overheating, whereas for WC–12Co all fractions have velocities above the critical threshold, but coarse particles (32–40 μm) give porosity up to 3.15% due to insufficient deformation. Corrosion tests showed that under spraying conditions optimized for each material, the Cr₃C₂–NiCr coatings (corrosion rate 0.066–0.102 mm/year) are an order of magnitude superior in corrosion resistance to WC–12Co coatings (corrosion rate 0.353–0.651 mm/year), owing to the passivation of the γ-Ni(Cr) matrix; for WC–Co, the main protective barrier is provided by the structural density. Full article

Improving the energetic performance of established explosives through rational structural modification provides an alternative strategy for the development of entirely new energetic molecules. In this work, bromine substitution was employed to regulate the solid-state properties of TNT derivatives, and two compounds, 3-bromo-2,4,6-trinitrotoluene (3-BrTNT) and 3,5-dibromo-2,4,6-trinitrotoluene (3,5-BrTNT), were synthesized and characterized. Single-crystal X-ray diffraction revealed that different bromination patterns lead to distinct crystal structures and packing characteristics. Electrostatic potential analysis and Hirshfeld surface analysis further revealed that bromine substitution modifies molecular surface characteristics and intermolecular contact distributions within the crystals. Compared with 3-BrTNT, 3,5-BrTNT exhibits a higher crystal density of 2.312 g cm⁻³ and improved calculated detonation performance, with a detonation velocity of 7915 m s⁻¹ and a detonation pressure of 31.86 GPa. Meanwhile, both brominated derivatives exhibit reduced impact sensitivity compared with TNT. These results demonstrate that the bromination pattern, rather than bromine incorporation alone, plays an important role in regulating crystal structures and energetic properties. This study provides insight into substitution-pattern-controlled crystal engineering as a strategy for optimizing TNT-based energetic materials. Full article