Search Results (9,974)

Infrastructure construction is a major contributor to carbon emissions, primarily due to the extensive use of mineral materials such as cement and aggregates, which release significant amounts of carbon dioxide during production and use. While existing research has predominantly centered on the applications of concrete, the present study extends the investigation to encompass inorganic–organic composites, alloy materials, and wastewater treatment systems, with particular attention to bridging the gap between theoretical potential and practical implementation. This study identifies China, the USA, and India as leaders in this field, attributing their progress to abundant material resources and sustained policy support. Key findings reveal that while geopolymers can fully replace cement, substitution rates of less than 50% are optimal for high-performance concrete to maintain structural integrity and decarbonization benefits. Aggregate replacements using materials such as air-cooled blast furnace slag show 50–100% feasibility. This review further highlights the multifunctional potential of red mud, rice husk ash, fly ash, and blast furnace slag as cement replacements, aggregates, reinforcers, catalysts, adsorbents, and composite fillers. However, challenges such as unstable raw material supply, lack of standardization, and insufficient international collaboration persist; these issues have often been overlooked in prior research and viable solutions have not been proposed. To address these barriers, a triple-objective framework is introduced in this study, integrating sustainable infrastructure, resource recycling, and environmental remediation, supported by optimized production processes and policy models from leading nations. Future research directions emphasize comprehensive life cycle assessments and enhanced global cooperation to bridge the divide between resource-rich and resource-scarce regions. By synthesizing cross-disciplinary applications and actionable solutions, this work advances the transition toward sustainable infrastructure systems. Full article

The optimization of thermal performance in buildings is essential for sustainable urban development, yet the high cost and complexity of traditional thermal conductivity measurement methods limit broader research and educational applications. This study developed and validated a low-cost, replicable prototype that determines the thermal conductivity of roof tiles and composites using the Lee Disc method automated with Arduino-based acquisition. Standardized samples of ceramic, fiber–cement, galvanized steel, and steel coated with a castor oil-based polyurethane composite reinforced with miriti fiber (Mauritia flexuosa) were analyzed. The experimental setup incorporated integrated digital thermocouples and strict thermal insulation procedures to ensure measurement precision and reproducibility. Results showed that applying the biocompatible composite layer to metal tiles reduced thermal conductivity by up to 53%, reaching values as low as 0.2004 W·m⁻¹·K⁻¹—well below those of ceramic (0.4290 W·m⁻¹·K⁻¹) and fiber–cement (0.3095 W·m⁻¹·K⁻¹) tiles. The system demonstrated high accuracy (coefficient of variation < 5%) and operational stability across all replicates. These findings confirm the feasibility of open-source, low-cost instrumentation for advanced thermal characterization of building materials. The approach expands access to experimental research, promotes sustainable insulation technologies, and offers practical applications for both scientific studies and engineering education in resource-limited environments. Full article

The disposal of waste slurry in engineering construction and water environment remediation has become increasingly prominent. The physicochemical composite method integrating flocculation, solidification, and precompression has emerged as an efficient treatment approach, yet the permeability characteristics of slurry reinforced by this method remain insufficiently understood. This paper takes the high-moisture-content sludge generated from lake dredging projects reinforced by the physicochemical composite method as the research objective. Through permeability tests, the permeability characteristics of the physicochemical composite-modified slurry under different factors are tested, and its permeability characteristics are quantified through fitting methods. The research results show that the permeability coefficient decreases with the extension of curing time, decreases with the increase in curing agent dosage, increases with the increase in initial moisture content, and decreases with the increase in pre-stress. Full article

The integration of composite materials into commercial aviation has transformed the industry by providing superior performance benefits, including enhanced fuel efficiency, reduced emissions, and improved structural integrity. With a significant shift towards aircraft featuring high contents of composite materials, the focus has also turned to the challenges associated with the end-of-life management of these materials. Unlike metals, composites are notoriously difficult to recycle due to the strong bonding between fibres and resin, creating significant environmental and economic challenges. The methodology employed—consisting of an extensive literature review that prioritises a holistic approach—aims to provide an overview of the status of composite recyclability in aviation. With this, the report investigates the durability of composites under operational conditions, the associated environmental factors, and their impact on the recycling potential. The dismantling processes for decommissioned aircraft are analysed to identify strategies that preserve material integrity for effective recycling. Established recycling methods are critically evaluated alongside innovative approaches. The study highlights the limitations of current techniques in terms of costs, energy consumption, and material degradation while exploring emerging technologies that aim to overcome these barriers. It is concluded that currently available techniques do not possess the industrial maturity required to handle the amount of composite materials being employed in aviation. Moreover, there is a clear discontinuity between the developments in the usage of composites and their end-of-life recycling, which can cause serious environmental and economic challenges in future years. By combining information regarding composite usage and aircraft retirements, assessing the environmental and economic implications of composite recycling as well as available techniques, and proposing pathways for improvement, this research underscores the importance of adopting sustainable practices in aviation. The findings aim to contribute to the development of a circular economy within the aerospace sector, ensuring the long-term viability and environmental responsibility of future composite-intensive aircraft designs. This is performed by calling for a multi-stakeholder strategy to drive recycling readiness and facilitate the evolution towards a circular economy in aviation, leading to more sustainable design, production, and dismantlement of aircraft in the future. Full article

Epoxy resins used in reactors are prone to cracking and failure due to mechanical vibration, thermal stress, and ultraviolet radiation. Improving their resistance to damage is important to extend the service life of reactors. This investigation develops a self-healing imidazole-cured epoxy resin for reactors using epoxy microcapsules and amine microcapsules prepared by electrospraying-interfacial polymerization (ES-IP) microencapsulation technique. Firstly, this investigation studies the feasibility of using double nozzles for simultaneous spraying to improve the preparation of small-sized microcapsules. After successful synthesis, the healing performance of self-healing imidazole-cured epoxy based on the microencapsulated epoxy-amine chemistry was studied, focusing on the influence of the ratio, concentration, and size of the two microcapsules on the healing efficiency, and further exploring the thermal stability of the self-healing performance. The addition of microcapsules to the mechanical properties was also investigated. Results show that the double-nozzle technique can prepare microcapsules with controllable sizes (20~200 μm). The self-healing imidazole-cured epoxy exhibits high self-healing performance, reaching 100% at the optimal ratio with 10.0 wt% 50~100 μm microcapsules. Although the added microcapsules reduce the tensile strength of the material, they improve its high-temperature aging resistance. The above investigation is significant for developing self-healing fiber-reinforced epoxy-based composite materials for reactors. Full article

Accurate prediction of shear strength at the interface between new and old concrete is vital for the structural performance of repaired and composite systems. However, the underlying shear transfer mechanism is highly nonlinear and influenced by multiple interdependent factors, which limit the applicability of conventional empirical models. To address this challenge, an interpretable machine-learning (ML) framework is proposed. The latest database of 247 push-off specimens was compiled from the recent literature, incorporating diverse interface types and design parameters. The hyperparameters of the adopted ML models were optimized via a grid search to ensure the predictive performance on the updated database. Among the evaluated algorithms, eXtreme Gradient Boosting (XGBoost) demonstrated the best predictive performance, with R² = 0.933, RMSE = 0.663, MAE = 0.486, and MAPE = 12.937% on the testing set, outperforming Support Vector Regression (SVR), Random Forest (RF), and adaptive boosting (AdaBoost). Compared with the best empirical model (AASHTO, R² = 0.939), XGBoost achieved significantly lower prediction errors (e.g., RMSE was reduced by 67.8%), enhanced robustness (COV = 0.176 vs. 0.384), and a more balanced mean ratio (1.054 vs. 1.514). The SHapley Additive exPlanations (SHAP) method was employed to interpret the model predictions, identifying the shear reinforcement ratio as the most influential factor, followed by interface type, interface width, and concrete strength. These results confirm the superior accuracy, generalizability, and explainability of XGBoost in modeling the shear behaviors of new–old concrete interfaces. Full article

This study examines the effects of incorporating recycled carbon fibers obtained from decommissioned wind turbine blades into cementitious composites. An extensive experimental program was carried out, varying fiber content (0–8 kg/m³), fiber length (25, 38, 50 mm), water-to-cement ratio (0.4, 0.5), and cement type (CEM I 42.5, CEM II 42.5R/A-V). The mechanical properties of the fiber-reinforced concretes, including compressive strength, flexural strength, splitting tensile strength, and modulus of elasticity, were evaluated. The addition of recycled carbon fibers significantly improved flexural and splitting tensile strengths, with increases exceeding 60% and 100%, respectively, at the highest fiber dosage (8 kg/m³), attributed to efficient crack-bridging capability. Compressive strength was mainly influenced by the water-to-cement ratio, while the modulus of elasticity showed slight reductions in some mixes due to fiber clustering and increased micro-porosity. Regression analysis indicated that shorter fibers (25 mm) were more effective in enhancing flexural strength, whereas longer fibers (50 mm) improved splitting tensile strength. Classical predictive models generally underestimated the flexural capacity of recycled-carbon-fiber-reinforced concretes, highlighting the need for recalibration. Optical microscopy confirmed uniform fiber dispersion at lower dosages and a dominant pull-out failure mechanism. The findings demonstrate the feasibility of using recycled carbon fibers to enhance the mechanical performance of concrete while supporting sustainability through waste diversion and circular economy strategies. Full article

Driven by the growing demand for sustainable materials, spent coffee grounds have emerged as a promising bio-based reinforcement in polymer composites, particularly for additive manufacturing applications. As a readily available byproduct of the coffee industry, spent coffee grounds contain cellulose, hemicellulose, lignin, proteins, and oils, making them attractive fillers for both thermoplastic and thermoset matrices. Incorporating spent coffee grounds into composites supports waste valorization, cost reduction, and environmental sustainability by transforming organic waste into functional materials. This review first examines the issue of spent coffee ground waste, addressing its environmental footprint and disposal challenges. It then explores the composition and properties of spent coffee grounds. The paper provides a comprehensive overview of composites based on spent coffee grounds for 3D printing, covering processing methods, potential applications, and current challenges in additive manufacturing. Special attention is given to the preparation and processing of these composites, including key steps such as drying, grinding, sieving, and surface modification to enhance compatibility with polymer matrices. Various additive manufacturing techniques influence the printability, processability, and mechanical performance of such composites. While spent coffee grounds offer notable sustainability advantages, challenges such as weak interfacial adhesion, moisture sensitivity, and reduced mechanical properties necessitate optimized processing conditions, surface treatments, and tailored material formulations. This review highlights recent advancements and outlines future research directions, emphasizing the need for stronger interactions between spent coffee grounds and polymer matrices, improved recyclability, and scalable additive manufacturing solutions to establish spent coffee grounds as a viable and eco-friendly alternative for 3D printing applications. Full article

This study explores the influence of various nano-inclusions on the electrical and thermal properties of cement-based materials. Specifically, it investigates the incorporation of Multi-Walled Carbon Nanotubes (MWCNTs) and Graphene Nanoplatelets (GNPs) as reinforcement materials in cement composites. These advanced nanomaterials enhance the mechanical strength, durability, and functional properties of cementitious matrices. A series of experimental tests was conducted to evaluate the thermal and electrical behavior of nano-reinforced concrete, employing nondestructive evaluation techniques, such as Infrared Thermography (IRT) and Electrical Resistivity measurements. The results indicate that increasing the concentration of nanomaterials significantly improves both the thermal and electrical conductivity of the composites. Optimum performance was observed at a CNT dosage of 0.6% and a GNP dosage of 1.2% by weight of cement in cement paste, while in concrete, both nanomaterials showed a significant decrease in resistivity beginning at 1.0%, with optimal performance at 1.2%. The study also emphasizes the critical role of proper dispersion techniques, such as ultrasonication, in achieving a homogeneous distribution of nanomaterials within the cement matrix. These findings highlight the potential of carbon nanotubes (CNTs) and GNPs to enhance the multifunctional properties of cement-based materials, paving the way for their application in smart and energy-efficient construction applications. Full article

The growing concerns over nuclear power plant safety in the wake of extreme impact events have highlighted the need for containment structures with superior resistance to large commercial aircraft strikes. Conventional reinforced concrete containment has shown limitations in withstanding high-mass and high-velocity impacts, posing potential risks to structural integrity and operational safety. Addressing this challenge, this study focuses on the dynamic impact resistance and vibration behavior of steel–ultra-high-performance concrete (S-UHPC) composite containment, aiming to enhance nuclear facility resilience under beyond-design-basis aircraft impact scenarios. Validated finite element models in LS-DYNA were developed to simulate impacts from four representative large commercial aircraft types, considering variations in wall and steel plate thicknesses, UHPC grades, and soil–structure interaction conditions. Unlike existing studies that often focus on isolated parameters, this work conducts a systematic parametric analysis integrating multiple aircraft types, structural configurations, and foundation conditions, providing comprehensive insights into both global deformation and high-frequency vibration behavior. Comparative analyses with conventional reinforced concrete containment were performed, and floor response spectra were evaluated to quantify high-frequency vibration characteristics under different site conditions. The results show that S-UHPC containment reduces peak displacement by up to ~24% compared to reinforced concrete of the same thickness while effectively localizing core damage without through-thickness failure. In addition, aircraft impacts predominantly excite 90–125 Hz vibrations, with soft soil conditions amplifying acceleration responses by more than four times, underscoring the necessity of site-specific dynamic analysis in nuclear containment and equipment design. Full article

This review provides a comprehensive analysis of recent developments in the additive manufacturing of green composites, with a particular focus on their mechanical behavior. A bibliometric analysis of 482 research articles indexed in the Web of Science Core Collection and published between 2015 and 2025 reveals a sharp increase in publications, with dominant contributions from countries such as China, India, and the United States, as well as strong collaboration networks centered on materials science and polymer engineering. Thematic clustering highlights a growing emphasis on natural fiber reinforcement, biodegradable matrices, and performance optimization. Despite these advances, few studies have combined bibliometric analysis with a technical evaluation of mechanical performance, leaving a gap in understanding the relationship between research trends and material or process optimization. Building on these insights, the review synthesizes current knowledge on material composition, print parameters, infill design, and post-processing, identifying their combined effects on tensile strength, stiffness, and durability. The study concludes that multi-variable optimization—encompassing fiber-matrix compatibility, print architecture, and thermal control—is essential to achieving eco-efficient and high-performance green composites in additive manufacturing. Full article

Carbon fiber-reinforced composites (CFRCs) are widely used in aerospace, automotive, and defense applications due to their high strength-to-weight ratio and excellent mechanical performance. In this study, cores and sandwich panels were fabricated via fused filament fabrication (FFF) using co-polyester filaments reinforced with 20 wt.% short carbon fibers. The mechanical response of the structures was evaluated under low-velocity impact (LVI) conditions using instrumented drop weight testing at energy levels ranging from 2 to 20 J. A three-factor, three-level full factorial experimental design was employed, considering build orientation (flat vs. upright), infill pattern (trihexagonal vs. triangular), and impact energy as factors. The maximum contact force was selected as the primary response variable. The results revealed that upright-printed specimens exhibited significantly improved impact resistance compared to flat-printed ones, with increases in peak force of up to 28% for cores and over 68% for sandwich structures. Among the tested infill geometries, the triangular pattern outperformed the trihexagonal one across all configurations and energy levels. The combination of upright orientation and triangular infill proved to be the most effective, providing enhanced energy absorption and reduced rear-side damage, especially under higher impact energies. These findings offer valuable insights into the design of lightweight, impact-resistant structures produced by additive manufacturing, with direct implications for structural components in demanding engineering environments. Full article

The present study investigates the tensile properties of 3D-printed PA12 composites reinforced with short carbon fibers, focusing on the impact of printing parameters on material performance. We employed both experimental testing and machine learning-based predictive modeling to evaluate the influence of layer thickness, extrusion width, and raster angles on failure stress, failure strain, and stress–strain curves. Four machine learning models, including Gaussian process regression (GPR), gradient boosting regression (GBR), random forest (RF), and artificial neural network (ANN), were developed and trained on the experimental data. The results indicated that ANN and GPR models outperformed RF and GBR in predicting mechanical properties, with ANN demonstrating the highest accuracy across all tasks. A SHAP analysis was conducted to interpret the models, revealing that raster angles significantly influence failure stress predictions, while extrusion width predominantly affects failure strain predictions. The ability of the models to predict entire stress–strain curves provides a comprehensive understanding of the material’s mechanical behavior, which is crucial for applications requiring detailed material response data. This study highlights the potential of machine learning models, particularly ANN, in predicting the tensile properties of 3D-printed composites. The findings offer valuable insights for optimizing the 3D printing process to achieve desired material characteristics and pave the way for further research in integrating these predictive tools into additive manufacturing workflows for real-time optimization and quality control. Full article

This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, capturing the nonlinear interplay between temperature evolution, phase transformation, and mechanical deformation under Joule heating. The model incorporates phase-dependent material properties, heat effects, and geometric constraints, enabling accurate prediction of actuation dynamics. To validate the model, a morphing spoiler prototype has been fabricated using high-performance additive manufacturing with a carbon fibre-reinforced polymer. The SMA wires have been pretensioned and electrically actuated at different current levels (3 A and 6 A), and the resulting deformation has been recorded through video analysis with embedded timers. Experimental measurements confirmed the model’s ability to predict both actuation time and displacement, with maximum deflections of 33 mm and 40 mm corresponding to different current inputs. This integrated approach demonstrates an efficient and compact solution for active aerodynamic surfaces without the need for mechanical linkages, enabling future developments in adaptive structures for automotive and aerospace applications. Full article

Predicting the mechanical performance of Engineered Cementitious Composite (ECC)-strengthened reinforced concrete (RC) beams is both meaningful and challenging. Although existing methods each have their advantages, traditional numerical simulations struggle to capture the complex micro-mechanical behavior of ECC, experimental approaches are costly, and data-driven methods heavily depend on large, high-quality datasets. This study proposes a novel physics-informed machine learning framework that integrates domain-specific empirical knowledge and physical laws into a neural network architecture to enhance predictive accuracy and interpretability. The approach leverages outputs from physics-based simulations and experimental insights as weak supervision and incorporates physically consistent loss terms into the training process to guide the model toward scientifically valid solutions, even for unlabeled or sparse data regimes. While the proposed physics-informed model yields slightly lower accuracy than purely data-driven models (mean squared errors of 0.101 VS. 0.091 on the test set), it demonstrates superior physical consistency and significantly better generalization. This trade-off ensures more robust and scientifically reliable predictions, especially under limited data conditions. The results indicate that the empirical-guided framework is a practical and reliable tool for evaluating the structural performance of ECC-strengthened RC beams, supporting their design, retrofitting, and safety assessment. Full article