Search Results (1,524)

In modern multistory buildings, integrating beam web openings adjacent to beam–column connections (BCCs) is frequently required to accommodate utility ducts and piping. While this optimizes clear story height, it drastically alters the stress distribution within the BCCs under seismic loading. Consequently, this study evaluates the seismic performance of twenty-one exterior BCCs, with particular emphasis on the coupled effects of opening configuration (size and location) and concrete type: normal strength concrete (NSC, f_c′ = 25 MPa), high-strength concrete (HSC, f_c′ = 80 MPa), and ultra-high-strength concrete (UHPC, f_c′ = 120 MPa). For BCC specimens without openings, upgrading from NSC to HSC and UHPC increased the failure load (P_f) by about 66.67% and 111.11%, and the ultimate capacity (P_u) by 61.54% and 100.0%, respectively. Conversely, web openings reduced the (P_u) of HSC specimens by 14–34%, and UHPC specimens by 12–31%, respectively, when compared to the reference specimens without openings. Furthermore, the presence of web openings compromised cumulative energy dissipation capacity by 16–36% for (NSC), 13–31% for (HSC), and 12–28% for (UHPC), compared with the corresponding reference specimens without openings. Although HSC and UHPC provided superior absolute energy performance, they did not eliminate the structural deficiencies associated with openings positioned adjacent to the joint core. Consequently, a critical threshold value of S/D ≥ 0.5 (where S represents the distance from the column face to the edge of the opening, and D denotes the beam depth), is recommended for HSC and UHPC. In contrast, conventional NSC strictly requires a more conservative limit of S/D ≥ 1.0 to prevent severe cyclic shear degradation near the high-stress region. Full article

The particle size and dosage of quartz sand significantly affect the bleeding and segregation of UHPC mixtures, thereby influencing their strength and durability. However, the maximum particle size of quartz sand is a key focus of existing research, and the influence sensitivity of particle size gradation and dosage for UHPC performance are not clear. Based on this, this study systematically investigates the effects of particle size gradation and dosage of quartz sand on the slump flow and strength of UHPC, and the grey relational analysis method is employed to identify the sensitive particle size fractions. The results show that the compressive and flexural strength of UHPC with quartz sand mixing ratio of 40:40:20 and 40:50:10 is significantly improved at both 7 d and 28 d curing ages compared with those using coarse, medium, and fine quartz sand individually. The order of particle size affecting slump flow, flexural and compressive strength of UHPC is 0.6–1.18 mm > 0.3–0.6 mm > 1.18–2.36 mm > 0–0.075 mm > 0.075–0.15 mm > 0.15–0.3 mm. The key measure for enhancing strength and ensuring workability of UHPC lies in the proportion of quartz sand with particle size of 0.6–1.18 mm, which needs to be above 40% to serve a filler and framework function. When coarse, medium, and fine quartz sand mixing ratio equals to 40:40:20, the dosage increases lead to the decrease in UHPC slump flow, and as the quartz sand dosage varies from 900 kg/m³ to 1500 kg/m³, the 28 d compressive strength of UHPC first increases and then decreases. It is recommended to use a quartz sand dosage of 1050 kg/m³ ± 50 kg/m³ and mixing ratio of 0.6–1.18 mm quartz sand larger than 40% to produce UHPC exhibiting slump flow larger than 600 mm and compressive strength of 120–150 MPa. The findings provide important guidance for the preparation and performance regulation of UHPC. Full article

Hybrid RF-FSO-THz communication systems are promising candidates for future Internet of Things (IoT) and 6G networks because they combine the robustness of radio frequency links, the high-capacity potential of Free-Space Optical communications, and the ultra-wideband capabilities of terahertz transmission. Adaptive channel selection in such systems depends on multiple correlated environmental and physical-layer variables, including distance, rain intensity, humidity, visibility, turbulence strength, signal-to-noise ratio, channel capacity, and energy-efficiency metrics. This paper presents a physics-supported benchmark framework for supervised adaptive channel selection in hybrid RF-FSO-THz systems and systematically investigates the impact of linear and nonlinear dimensionality-reduction techniques on predictive performance, statistical robustness, computational complexity, and physical interpretability. A multi-scenario dataset comprising 5000 samples was generated using calibrated RF, FSO, and THz propagation models under clear, rain, fog, and worst-case environmental conditions. Principal Component Analysis (PCA) and Kernel PCA were evaluated together with Random Forest, Support Vector Machines (SVMs), XGBoost, Gradient Boosting (GB), Multi-Layer Perceptron (MLP), Logistic Regression, and Decision Trees. The results demonstrate that PCA preserves nearly all predictive capabilities while reducing the original 33-dimensional feature space by approximately 81.8%, maintaining accuracies close to 97–98% with the best-performing classifiers. Statistical significance analysis confirms that PCA introduces only modest degradations, whereas Kernel PCA consistently reduces the predictive performance while increasing memory requirements and inference latency. Additional environmental-only validation experiments indicate that adaptive channel selection remains highly learnable even when only pre-selection environmental descriptors are available, partially mitigating concerns regarding self-consistency bias. Overall, the results suggest that PCA provides an advantageous compromise among predictive accuracy, computational efficiency, statistical robustness, and physical interpretability for supervised adaptive channel selection in physics-supported hybrid wireless communication systems. Full article

The growing demand for sustainable construction materials has led to significant advancements in ultra-high-performance concrete (UHPC), with a particular focus on geopolymer-based systems as an alternative to conventional cementitious binders. This review explores the latest developments in sustainable Ultra-High-Performance Geopolymer Concrete (UHPGPC) by analysing key material composition, mechanical, durability and microstructural properties. The incorporation of ground granulated blast furnace slag (GGBFS), silica fume (SF), and fly ash (FA) has demonstrated notable improvements in compressive strength, durability, and workability. Additionally, the use of activators such as sodium silicate and sodium hydroxide optimizes geopolymerization, resulting in a denser microstructure and enhanced mechanical performance. This review highlights the critical role of fibre reinforcement in UHPGPC, where steel fibres (SFs) and hybrid fibres significantly enhance compressive and tensile strength, as well as crack resistance. The inclusion of waste materials such as rice husk ash and recycled glass promotes sustainability by reducing CO₂ emissions while maintaining structural integrity. However, higher waste-glass content may adversely affect bonding due to its smooth surface texture. The findings highlight the potential of UHPGC as a high-performance, eco-friendly alternative to traditional cement-based UHPC. By integrating industrial by-products and alternative activation techniques, UHPGPC can contribute significantly to the global shift towards sustainable and low-carbon construction materials. Full article

The sluggish kinetics of alkaline hydrogen oxidation reaction (HOR) and high cost of Pt–based catalysts have long hindered large–scale deployment of alkaline membrane fuel cells. Via first–principles calculations, we designed a series of 3d transition metal single atoms anchored on PdN₂ monolayer (TM–PdN₂, TM = Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn) and evaluated their alkaline HOR performance. Ti-, Cr-, Fe-, Co-, Ni-modified systems exhibit excellent thermodynamic and electrochemical stability under operating conditions. Single-atom doping tunes the p-band center of N and d-band center of metal sites, enabling precise modulation of H and OH adsorption strengths. Mechanistic analysis reveals HOR follows H₂ + 2OH* → H* + OH* + H₂O → 2H₂O, with the final step as rate-determining step. H adsorption contributes 3.45 times more to HOR activity than OH adsorption. Fe–PdN₂ delivers the best performance, with an ultra–low barrier of 0.11 eV and a rate constant of 2.82 × 10¹⁰ s^–1·site⁻¹, values that significantly outperform those of Pt(111) (0.22 eV, 4.5 × 10⁹ s⁻¹·site⁻¹). This work provides theoretical guidance for rational design of high–performance alkaline HOR electrocatalysts. Full article

The excessive emission of greenhouse gases (CO₂, CH₄, SF₆, and CF₄.) is a primary driver of global climate change, making the development of efficient adsorption and separation technologies critically important for achieving carbon reduction goals. Metal–organic frameworks (MOFs) have attracted considerable attention in this field due to their crystalline porous structures, ultrahigh surface areas, and tunable pore architectures. However, pristine MOFs face significant bottlenecks including poor water stability, high bed pressure drops caused by their powdered form, and limited mass transfer, which severely hinder their industrial application. The integration of MOFs with functional materials such as carbon materials, polymers, metal oxides, and porous SiO₂ offers a synergistic strategy to overcome these limitations. Carbon materials provide hydrophobic barriers and mesoporous transport channels, polymers enhance processability and mechanical strength, metal oxides introduce basic sites for enhanced chemisorption, and MOF-on-MOF heterostructures enable atomic-level interfacial integration and pore synergy. This review systematically summarizes recent advances in MOF composites for the separation of CO₂, CH₄, and fluorinated greenhouse gases (SF₆, CF₄.), with an emphasis on design strategies, structure–performance relationships, and synergistic mechanisms across different composite types. Finally, the current challenges including scalable synthesis, long-term stability, and separation performance under realistic conditions are discussed, and future directions toward rational design and functional synergy for industrial carbon capture and fluorinated gas emission reduction are envisioned. Full article

Ultra-high-performance concrete (UHPC) is known for its exceptional compressive strength and durability; however, its brittle nature requires fiber reinforcement to improve toughness and tensile performance. This study investigates the synergistic effects of triple fiber reinforcement, including desized and sized carbon fibers (0.2–1.0 vol%), steel fibers (1.0 vol%), and polypropylene fibers (0.2 vol%) on the fresh, mechanical, durability, microstructure, and fire resistance properties of UHPC. The experimental program included workability, compressive and flexural strength, load-deflection behavior, electrical resistivity, dynamic modulus of elasticity, SEM analysis, and fire resistance at elevated temperatures (425 and 900 °C). The results showed that desized carbon fibers performed better than sized fibers by improving workability, fiber dispersion, flexural behavior, and fiber–matrix bonding. The optimal triple-fiber composition, DC1.0P0.2S1.0, achieved the highest flexural strength of 24 MPa while maintaining compressive strength above 141 MPa. The triple-fiber system provided effective multi-scale crack control, where PP fibers prevented explosive spalling, carbon fibers bridged meso-crack control, and steel fibers enhanced macro-crack load transfer and ductility. SEM analysis further confirmed better dispersion and stronger interfacial bonding of desized carbon fibers. Overall, the optimized triple-fiber system significantly improved flexural performance, toughness, workability, and fire resistance without notably reducing compressive strength, demonstrating strong potential for advanced structural applications. Full article

In response to the current limitation where conventional constant volume combustion apparatuses are generally confined to pressure ratings of 5–20 MPa, insufficient for the demands of ultra-high-pressure combustion fundamental research, this study designs and verifies a high-pressure-resistant constant volume combustion apparatus with a rated working pressure of 250 MPa. The strength design and safety factor calculation for the combustion chamber main body were conducted based on the Lame thick-walled cylinder elastic theory. A finite element numerical simulation method was systematically employed to perform static analysis, transient impact response analysis, and high-cycle fatigue-life assessment of the key components of the apparatus. The results indicate that under a 250 MPa design internal pressure load, the maximum circumferential stress at the inner wall of the combustion chamber main body is 328.0 MPa, with a safety factor greater than 1.5, complying with relevant safety codes for high-pressure vessels. Under transient loading simulating combustion impact, the maximum equivalent stress of all structural components is below the material yield strength, with a maximum elastic deformation of less than 0.06 mm, demonstrating excellent structural stiffness and impact resistance. Fatigue assessment with a design-life target of 1.0 × 10⁶ pressure cycles shows that the cumulative damage values for all components are significantly less than 1.0, meeting the reliability requirements for long-term cyclic service. This apparatus integrates functional modules such as high-pressure precision gas mixing, high-energy reliable ignition, high-speed transient parameter acquisition, and safe product collection, providing a stable, controllable, and safe experimental platform for in-depth research on the combustion mechanisms of gaseous fuels under ultra-high-pressure conditions. Full article

Background/Objectives: The increasing burden of non-communicable diseases, together with accelerating environmental degradation, highlights the urgent need for sustainable dietary patterns that promote both human and planetary health. The Mediterranean diet (MedDiet), traditionally followed in countries bordering the Mediterranean basin, has gained recognition as a model of sustainable nutrition due to its well-documented health benefits and relatively low environmental impact. However, its broader role within sustainable food systems requires comprehensive and interdisciplinary evaluation. The aim of this review is to provide a state-of-the-art synthesis of the evidence on the MedDiet as a sustainable dietary pattern, integrating its health, environmental, economic, and socio-cultural dimensions. Methods: This state-of-the-art narrative review synthesizes evidence from peer-reviewed literature on the MedDiet and sustainability. Relevant studies were identified through major scientific databases, focusing on publications addressing nutritional, environmental, economic, and socio-cultural dimensions. Both observational and interventional studies, as well as modeling and life cycle assessment analyses, were included. Additional sources from international organizations and policy reports were incorporated to contextualize global trends and challenges. Results: High adherence to the MedDiet is consistently associated with a reduced risk of cardiovascular disease, type 2 diabetes, cancer, and all-cause mortality. From an environmental perspective, the MedDiet is associated with lower greenhouse gas emissions, reduced land and water use, and enhanced biodiversity conservation compared with Western dietary patterns. Economically, it may represent a cost-effective dietary model and support local food systems when grounded in traditional practices, although affordability varies across contexts. Socio-culturally, the MedDiet promotes food heritage, culinary skills, and social cohesion. Nevertheless, globalization, urbanization, and the increasing consumption of ultra-processed foods have contributed to declining adherence, posing significant challenges to its sustainability and scalability. Moreover, the sustainability benefits of the MedDiet seem to be context-dependent rather than intrinsic, raising several challenges and limitations for its adoption. Conclusions: The MedDiet should be viewed not as a definitive solution to global food-system challenges but as a valuable reference model that illustrates how dietary practices can contribute simultaneously to human health, environmental sustainability, and cultural continuity. Modern sustainable dietary strategies should build upon the strengths of the MedDiet while recognizing its limitations, embracing contextual adaptation, and addressing the structural determinants that shape food choices. Full article

Longitudinal data, characterized by repeated measurements on the same subjects over time, are ubiquitous in biomedical sciences, economics, social sciences, and engineering. Analyzing such data presents unique statistical and computational challenges, including within-subject correlation, time-varying covariates, irregular observation times, informative dropout, and high dimensionality. While traditional statistical methods, such as linear mixed-effects models and generalized estimating equations, remain foundational, they often struggle with complex nonlinear dynamics, ultra-high-dimensional feature spaces, and very large sample sizes. Over the past two decades, machine learning (ML) and artificial intelligence (AI) methods have emerged as powerful complementary approaches to address these limitations. This review provides a comprehensive survey of mathematical and computational methods for longitudinal data analysis. We cover classical statistical models, penalized regression techniques, tree-based ensemble methods, kernel machines, Bayesian hierarchical models, and modern deep learning architectures, including recurrent neural networks, temporal convolutional networks, attention-based Transformers, neural ordinary differential equations, and generative models. We propose a unified taxonomy that organizes existing methods along two primary axes: the underlying mathematical framework and the analytical objective. For each category, we present detailed mathematical formulations, discuss key theoretical properties, examine computational considerations, and summarize representative reported applications drawn from the published literature. To increase the practical value of this review, we provide a cross-cutting comparison of method families against five key challenges (within-subject correlation, irregular sampling, missing data, high dimensionality, and scalability) and offer concrete guidance on method selection according to sample size, dimensionality, and analytical objective. Finally, we critically evaluate the strengths and limitations of these approaches, with particular emphasis on interpretability, scalability, handling of missing data, robustness to covariance misspecification, and uncertainty quantification. Full article

Polyampholyte (PA) hydrogels have attracted considerable attention due to their unique dynamic network structures and favorable biocompatibility. However, their low modulus severely limits applications in load-bearing aspects. Herein, we report ultrastiff PA nanocomposite hydrogels through the synergistic strategy of effective aggregation of hydrophilic silica (SiO₂) nanoparticles and multi-bond networks. Specifically, a high content of SiO₂ nanoparticles is first incorporated into a dynamic ionic PA network via in situ polymerization. The resulting hydrogel is subsequently dialyzed in a zirconium salt solution with strong coordination capability, achieving the ultrastiff nanocomposite hydrogel. In this strategy, the dynamic PA network infiltrated between the aggregated SiO₂ nanoparticles enables effective particle aggregation, while the dynamic PA network, consisting of ionic and metal-coordination bonds, provides efficient energy dissipation, resulting in a synergistic reinforcement effect. The effects of dialysis time, concentration of zirconium salt, and particle content on the swelling and mechanical behaviors of the hydrogels are systematically investigated. The optimized nanocomposite hydrogel exhibits a Young’s modulus and a tensile strength as high as 87.9 ± 5.9 MPa and 7.9 ± 0.1 MPa, respectively, which are 976 and 8.8 times those of the original neat PA hydrogel. This work provides an effective strategy for designing hydrogels with ultrahigh mechanical performance. Full article

Electrodeposition of nanostructured metals often suffers from a trade-off between mechanical performance and efficiency. This study introduces ultranarrow slit-jet scanning electrodeposition (USJS-ECD), an additive-free technique employing a planar jet confined by a slit with opening width of <100 μm to scan the cathode. Numerical simulations coupling fluid flow and electric fields were conducted to optimize jet dynamics and scanning parameters. Experimental analyses reveal that USJS-ECD creates a highly localized, uniformly intensified energy field enabling direct fabrication of ultrahigh-strength nickel. The resulting deposits exhibit 98.82 wt% purity, an ultrafine grain size of 21.86 nm, and a mirror finish with surface roughness (Ra) of ~22 nm. Mechanical testing demonstrates a microhardness of 623 HV, a tensile strength of 756 MPa, and an elongation of 9.33%, achieving a superior strength-ductility synergy. Crucially, the deposition rate reaches 1.72 μm/min, significantly outperforming advanced ultrafine anode scanning electrodeposition (UAS-ECD) techniques. USJS-ECD presents a promising, efficient methodology for producing high-performance nanocrystalline metallic materials. Full article

Steel–concrete composite beams are widely used in bridge infrastructure but are vulnerable to deterioration due to uniform and pitting corrosion, particularly at the lower flange. This study investigates the flexural behavior of corroded steel–normal strength concrete (NSC) composite beams and evaluates rehabilitation using ultra-high-performance concrete (UHPC) slab replacement, with and without additional steel plate strengthening. A comprehensive finite element analysis was conducted considering three beam spans (5, 7, and 9 m), two corrosion types, and three corrosion levels. The results indicate that both corrosion types significantly reduce flexural capacity due to cross-sectional loss, with pitting corrosion causing greater strength reduction than uniform corrosion at the same weight loss because of stress concentration effects. Replacing the NSC slab with a UHPC slab effectively restores and often enhances load-carrying capacity beyond that of intact beams while reducing dead load, demonstrating the superiority of the proposed rehabilitation approach. The combined use of UHPC slab replacement and welded steel plate strengthening provides the greatest improvement, revealing a strong synergistic effect. A case study of a corroded steel bridge in Pennsylvania confirms the practical applicability of the method, showing that UHPC-based rehabilitation increases the load rating from below unity to above unity. These findings highlight UHPC as an efficient and sustainable solution for extending the service life of aging steel bridges. Full article

High-performance and ultra-high-performance fiber-reinforced concretes (HPFRC/UHPFRC) have emerged as advanced cementitious composites capable of achieving superior mechanical performance, durability, and structural efficiency compared with conventional concrete. However, their widespread adoption remains challenged by relatively high material costs and significant embodied environmental impacts associated with elevated binder and fiber contents. This study presents a comprehensive life-cycle review of advanced high-performance cementitious composites, evaluating their sustainability from raw material extraction and mix design to structural application, service life, and end-of-life considerations. The review synthesizes current knowledge on material composition, production processes, structural performance, durability characteristics, and environmental impacts through the framework of life-cycle assessment (LCA). Particular attention is given to the influence of mix-design parameters, including binder composition, supplementary cementitious materials (SCMs), aggregate systems, and fiber type, on embodied carbon, energy demand, and mechanical performance. A dataset compiled from published experimental studies covering high-performance and ultra-high-performance concrete mixtures is analyzed to examine relationships between compressive strength, embodied energy, and carbon footprint, highlighting the dominant role of cementitious binders and fiber production in environmental impacts. Although advanced fiber-reinforced concretes generally exhibit higher cradle-to-gate emissions than conventional concrete, their superior mechanical properties, improved durability, reduced material demand, and extended service life can substantially reduce life-cycle environmental impacts at the structural level. The review further discusses emerging strategies for developing low-carbon high-performance cementitious composites, including clinker reduction, recycled and alternative fibers, optimized particle packing, and AI-assisted mix design. Finally, key research gaps are identified, particularly regarding standardized LCA methodologies, long-term durability data, harmonized performance-based functional units, and circular-economy strategies for material recycling and reuse. The findings highlight that performance-based life-cycle evaluation is essential for accurately assessing the sustainability potential of advanced high-performance cementitious composites in resilient and low-carbon infrastructure systems. Full article

Wire drawing is a key processing method for producing ultrahigh-strength stainless steel wires. In metastable austenitic steels, the strain-induced martensitic transformation is known to govern strain hardening. However, the transformation mechanism and kinetics behavior under wire drawing remain unclear due to the distinct deformation conditions compared to those of conventional loading modes. In this work, the microstructural evolution, transformation kinetics and strengthening behavior of the 304 stainless steel during cold wire drawing are systematically analyzed. The results show that the transformation is dominated by the austenite → twin→ α′-martensite pathway, with the ε-martensite effectively suppressed. The martensite fraction follows a sigmoidal evolution with the equivalent drawing strain and could be well described by the Olson–Cohen model. The yield strength is increased from 320 MPa to 2 GPa and exhibits a linear relationship with the martensite fraction, indicating a dominant composite strengthening mechanism. These findings clarify the deformation-mode-dependent transformation mechanism and its role in governing mechanical properties during wire drawing. Full article