Search Results (20,305)

Aluminium is one of the most carbon-intensive structural materials, making the direct reuse of aluminium members a highly effective strategy for reducing environmental impacts by avoiding primary production. Despite this potential, the reuse of aluminium structural members has received far less attention than steel reuse. This study addresses that gap through two complementary contributions. First, it develops a reuse pathway for aluminium structural members based on existing steel reuse frameworks while addressing aluminium-specific technical challenges. Second, it evaluates the environmental implications of this approach through a life cycle assessment of an aluminium portal frame tent structure in accordance with EN 15804+A2 and the EF 3.1 method, covering Modules A1–A5, C1–C4, and D. Three end-of-life scenarios are considered: a cut-off baseline, a recycling scenario, and a reuse scenario. Aluminium production accounts for 37.6% of the cradle-to-gate impact while representing only about 3.3% of the mass. Direct reuse lowers the net global warming potential by about 22% relative to recycling and is the lowest-impact option across all 16 impact categories. The results identify direct reuse as the environmentally preferable end-of-life route, although wider implementation depends on design for disassembly and a dedicated technical framework for reclaimed aluminium. Full article

Photocatalytic degradation of organic pollutants has emerged as a promising approach for wastewater treatment due to its environmental friendliness and high efficiency under mild conditions. This study focuses on evaluating materials for the decolorization of methylene blue (MB) and methyl orange (MO), which are commonly used cationic and anionic dyes, respectively, known for their persistence and toxicity in aquatic environments. The research investigates the synthesis of a Mott–Schottky junction at the interface of two materials using MXene as a dopant. We synthesized three MXene-containing Porous Organic Polymers (POP-2MX, POP-6MX, and POP-10MX), incorporating 2%, 6%, and 10% MXene, respectively. UV–Vis spectroscopy tests revealed that all polymers exhibited high degradation efficiency; however, POP-6MX demonstrated the best overall activity. Under illumination of a 500 W Xenon lamp (λ > 420 nm) with a catalyst loading of 1 mg/mL, POP-6MX achieved complete adsorption-corrected degradation of MB and MO within 10 and 45 min, respectively. This research also investigated the influence of pH on photocatalytic performance under homogeneous aqueous conditions, revealing that neutral pH provides the optimal environment for degradation activity. The photocatalytic mechanism follows a reactive oxygen species (ROS)-dominated pathway, primarily driven by superoxide radicals (•O₂⁻) and hydroxyl radicals generated through photochemical reactions. These results demonstrate the potential of POP-1/MXene composites as efficient and recyclable photocatalysts for sustainable dye wastewater treatment applications. Full article

The engineering, resource, and financial constraints in space and spacecraft so far have not allowed the incorporation of biological components into a closed-loop bioregenerative life support system (BLSS), despite decades of research. The expected increase in deep-space exploration and planetary bases with limited access to Earth-based resources necessitates the development of self-sustaining hybrid BLSS technology. The created physicochemical systems, together with photosynthetic organisms and bacteria, aim to revitalize the air, produce food, and recycle nutrients and water in mutually beneficial mini-ecosystems. While plants are best in the function of food production and bacteria in waste recycling, the incorporation of microalgae would add immense benefits in optimizing the life support system (LSS) and increasing the degree of closure. Microalgal photobioreactors (PBRs) could perform wastewater treatment (WWT), removing the nitrogen (N) and phosphorus (P) in the human-derived wastewater (WW), and couple it with converting carbon dioxide (CO₂) from the cabin to oxygen (O₂) and food production. As microalgal WWT on Earth is an emerging field with engineering hurdles, power, mass, volume, microgravity fluid dynamics, and other constraints have also prevented their operations in space. However, in space vehicles, there is no need for large upscaling of a laboratory prototype system, and the WW effluent is easier to predict, facilitating microalgal extraplanetary use in comparison to Earth treatment plants. These factors, combined with the qualities of microalgae such as surface-to-volume efficiency, fast growth rate, high yield, and tolerability to WW, etc., have led to many preliminary testbeds, prototypes, and ground demonstrations from space agencies, space centers, and academia, which show promising results. Microalgal participation in space WWT is beyond current operational practice; however, PBRs are on the space agenda, and the scientific community is elaborating the technologies that would allow their successful implementation. Full article

Microalgae–fungal pellets have been studied as a versatile and robust biotechnological platform, offering significant advantages for microalgal biomass harvesting, wastewater treatment, biofuels production and/or obtaining of value-added products. This review presents an integrated analysis of the mechanisms governing the formation, stability, and functionality of these systems, combining physicochemical, biological, and mathematical modelling approaches and aims to describe the current state of the art and main research needs. The aggregation process is strongly influenced by the complementarity of the surface properties of microalgae and filamentous fungi, including electrostatic interactions, production of extracellular polymeric substances (EPSs), and modifications in surface roughness. Recent advances in multiscale characterization techniques, such as confocal microscopy, micro-computed tomography, atomic force microscopy, and X-ray photoelectron spectroscopy, have allowed a more precise elucidation of the internal architecture and surface chemistry of the pellets. In parallel, biological characterization through enzymatic assays, oxidative stress biomarkers, and photosynthetic activity analyses has provided relevant information on the metabolic responses and functional resilience of the consortium. Additionally, the incorporation of mathematical flocculation models can contribute to the prediction of pellet growth, density, and stability, supporting process optimization and application. The understanding of these interaction phenomena is important for the design of high-yield and efficient systems, including their development and validation, to expand the use of microalgae–fungal pellets in bioprocesses, as evidenced by this review. Full article

To reveal the evolution laws of shear mechanical behavior and size effect of prestressed Recycled Aggregate Concrete (RAC) beams under dynamic loading conditions, a three-dimensional five-phase meso-scale numerical model was established based on the ABAQUS2020 software. The bond–slip behavior between steel bars and concrete was considered, and prestress was applied using the temperature cooling method. The effects of prestress level, cross-sectional size and strain rate on failure modes, load–displacement curves, ultimate shear capacity and nominal shear strength were systematically investigated. The results show that increasing the prestress level can significantly restrain the initiation and propagation of diagonal cracks, reduce the brittleness of the failure mode, and effectively mitigate the shear size effect. The nominal shear strength decreases obviously with an increase in cross-sectional size but increases significantly with an increase in strain rate, exhibiting a pronounced strain rate hardening characteristic. Large-scale beams are more sensitive to strain rate, and a high strain rate can reduce the disparity in shear performance among members of different sizes and further weaken the size effect. Based on Bažant’s Size Effect Law (SEL), a modified formula for dynamic shear strength considering the coupled effects of prestress level, strain rate and cross-sectional size was proposed by introducing a prestress enhancement coefficient γ and a strain rate enhancement coefficient β. The calculated results of this formula are in good agreement with the numerical results obtained in this study. Within the investigated parameter range, the present work can provide a reference for the shear design and safety assessment of prestressed recycled aggregate concrete beams under dynamic loading. Full article

Global warming is reshaping terrestrial water cycling and near-surface climate risks through atmospheric moistening, enhanced precipitation variability, rising evaporative demand, and more frequent compound extremes. This narrative review synthesizes recent advances in land–atmosphere interactions and atmospheric water cycle feedbacks, and its distinctive contribution is to connect physical feedback chains with human land surface perturbations, compound risk, and observation model machine learning evidence. We reviewed the literature from Web of Science, Scopus, Google Scholar, publisher databases, and Crossref metadata, prioritizing peer-reviewed studies published mainly during 2010–2026 while retaining foundational work on soil moisture feedbacks, moisture recycling, irrigation, aerosols, and boundary-layer processes. The synthesis emphasizes where evidence is robust, where feedback signs are regime dependent, and where uncertainty still propagates from evapotranspiration partitioning, boundary-layer diagnosis, aerosol–cloud interactions, human water management, and nonstationary climate conditions. The review concludes that the same land surface perturbation may cool locally, increase humid heat exposure, alter downwind precipitation, or intensify water depletion, depending on the climate regime, season, scale, and management. Future research should therefore move beyond single-variable correlation analyses toward causal, cross-scale, and risk-oriented attribution frameworks that integrate multi-source observations, process models, moisture tracking, and physically constrained machine learning. Full article

Advancing urban sustainability transitions through effective environmental policies requires understanding how residents perceive and respond to policies. While perceived policy effectiveness (PPE) has been studied in waste management and recycling programs, its role in shaping demand for bio-based materials remains underexplored. This study investigates whether and how PPE is associated with bamboo product consumption among 1121 urban residents in Zhejiang Province, China. Drawing on an extended Theory of Planned Behavior (TPB) framework, we use ordinary least squares estimators to examine the direct and interactive associations between PPE and actual bamboo consumption behavior. Results show that PPE is significantly and positively associated with bamboo product consumption. Interaction analysis reveals heterogeneous effects: PPE shows a weak positive interaction with environmental knowledge, but a negative interaction with environmental values. This suggests that policy signals may complement cognitive preparedness while partly compensating for low value-based motivation. A supplementary analysis indicates that this conditioning extends to economic resources, with the association concentrated among lower-income, more price-sensitive consumers. This study extends PPE research from post-consumption management to the purchasing stage of sustainable products. It highlights the role of policy perceptions in shaping demand-side adoption of lower-impact materials, with implications for urban sustainability transitions and city-level policies promoting bio-based alternatives. Full article

Carbonation treatment can effectively address defects in recycled aggregates (RA) while achieving CO₂ sequestration, thereby improving properties of recycled aggregate concrete (RAC). However, the compressive strength of carbonated recycled aggregate concrete (CRAC) is governed by complex interactions among multiple parameters, and existing machine learning (ML) studies often rely on heterogeneous literature data with limited parameter coverage, resulting in constrained predictive accuracy. To address this issue, this study established a robust ML framework for precise strength prediction. By integrating published literature with original experimental results, a dataset of 226 groups was constructed, incorporating 12 key parameters across RA properties, carbonation processes, mix proportions, and concrete age to systematically compare three ML models (GPR, SVM, EDT). To enhance model transparency, global sensitivity analysis used the SHapley Additive exPlanations (SHAP) method, while X-ray diffraction (XRD), scanning electron microscopy (SEM), and microhardness tests were employed to reveal reinforcement mechanisms at the phase, microstructural, and micromechanical levels, supporting the connection between intelligent prediction and mechanistic explanation. Results show that the GPR model exhibited the highest predictive performance and generalization capability (R² = 0.98 for training, R² = 0.94 for testing; RMSE = 1.08 MPa), outperforming comparative models in handling high-dimensional nonlinear relationships. SHAP analysis identified concrete age, water–cement (W/C) ratio, and the initial crush index of the RA as the primary factors, while carbonation process parameters, particularly relative humidity, carbonation pressure, and carbonation time, exerted significant regulatory effects on strength. XRD results qualitatively confirmed the formation of CaCO₃ after carbonation, while SEM and microhardness analyses indicated that carbonation products contributed to pore filling and interfacial transition zone (ITZ) strengthening, providing a physical basis for both macroscopic performance improvement and model reliability. This study provides a scientific, data-driven solution for the mix design optimization and performance prediction of CRAC, delivering substantial environmental and economic benefits. Full article

The increasing demand for sustainable materials has intensified efforts to enhance the performance of recycled polymers for engineering applications. This study investigates the effect of nanoclay reinforcement on the mechanical properties of recycled high-density polyethylene (rHDPE). Nanoclay was incorporated into rHDPE at varying loadings through melt blending, and the resulting composites were evaluated in terms of tensile, flexural, impact, and hardness properties. The tensile strength and tensile modulus improved significantly with increasing nanoclay content, reaching maximum values of 31.27 MPa and 2.39 GPa, respectively, at 1.5 wt% nanoclay, corresponding to increases of 23.11% and 47.53% relative to unreinforced rHDPE. Similarly, the flexural strength and flexural modulus attained peak values of 25.88 MPa and 1105.08 MPa at 1.5 wt% nanoclay, representing improvements of 12.57% and 15.49%, respectively. Impact strength exhibited a different trend, achieving a maximum value of 73.58 kJ/m² at 0.5 wt% nanoclay before decreasing at higher loadings, indicating a transition towards more brittle behaviour. Hardness increased progressively with nanoclay addition and reached a maximum value of 68.06 Shore D at 1.5 wt%, exceeding both unreinforced rHDPE and virgin HDPE. The overall results demonstrate that nanoclay effectively compensates for the mechanical degradation associated with recycling by enhancing stiffness, strength, and surface hardness. Among the investigated formulations, 1.5 wt% nanoclay provided the optimum balance of mechanical performance, while higher loadings led to reduced reinforcement efficiency due to particle agglomeration. These findings highlight the potential of nanoclay-reinforced rHDPE as a sustainable, high-performance material for applications in packaging, construction, and automotive components, thereby supporting circular economy initiatives and resource-efficient material development. Full article

Viscosity reducers are essential additives for water-based drilling fluids (WBDFs), serving to counteract the rheological degradation induced by the high-temperature and high-salinity conditions commonly encountered in deep and ultra-deep well drilling. This paper systematically reviews the research progress in this field, categorizing viscosity reducers into three major systems: modified natural materials, industrial waste utilization, and synthetic polymers. Modified natural material viscosity reducers, derived from renewable materials such as lignin and humic acid via chemical modification, are environmentally friendly products. The preparation of viscosity reducers from industrial wastes realizes both resource recycling and economic benefits. Synthetic polymer viscosity reducers, incorporated with functional monomers such as sulfonic and carboxylic groups, achieve high performance with temperature resistance exceeding 220 °C as well as excellent salt and calcium tolerance via rational molecular design, and represent the current mainstream research direction in the field. This paper provides an in-depth analysis of the action mechanisms of various viscosity reducers, summarizes the performance characteristics, synthesis methods and application status, and identifies challenges in structure–property relationship elucidation, extreme working condition adaptability, and technology transfer efficiency. Finally, future development trends are discussed, with emphasis on precision molecular design, ultimate performance requirements for ultra-deep wells, environmentally sustainable approaches, and the establishment of standardized evaluation protocols. This review aims to provide both theoretical insights and practical guidance to support the efficient development of deep oil and gas resources. Full article

As e-commerce expands, packaging increasingly serves as a communication interface in at-home consumer environments, where it may influence how consumers interpret sustainability. Unlike retail settings, where disposal decisions may be externally guided, consumers in e-commerce contexts rely on material cues and on-package information to interpret recyclability and brand intent. This study aims to examine how paper-based and plastic packaging influence visual attention, disposal behavior, and brand perception in apparel e-commerce. A controlled experimental study (n = 91) was conducted using mobile eye-tracking, behavioral observation, post-experience surveys, and follow-up interviews. Participants were randomly assigned to one of three packaging conditions: a low-density polyethylene (LDPE) plastic bag, a translucent paper bag, or a hybrid paper-based bag combining kraft and translucent materials. Results show that paper-based formats generated greater visual engagement than plastic, with translucent paper eliciting longer fixation duration and higher fixation count (p < 0.05). Recycling rates were higher for paper-based formats (70–77%) than plastic (53%), though not statistically significant. Perceived eco-friendliness differed significantly, with the hybrid paper format more strongly associated with environmental responsibility (p < 0.001). Qualitative findings indicate that material statements and disposal instructions improve confidence in interpreting recyclability. These results suggest that packaging material plays a role in shaping consumer attention and perceived eco-friendliness in e-commerce contexts. Full article

Reusing industrial byproducts to prepare recycled aggregate concrete (RAC) is a sustainable approach that can protect the ecological environment. This study tested the possibility of preparing an eco-efficient recycled concrete containing steel slag (SS), ground-granulated blast-furnace slag (GGBS), and polypropylene (PP) fibers to avoid resource waste and depletion and decrease CO₂ emissions. To this end, 12 mix proportions were designed to analyze the effects of SS, GGBS, and PP fibers on the macro- and micro-performances of the developed RAC. The experimental results showed that increasing the SS content decreased the RAC mechanical strength, whereas partially substituting SS with GGBS in the RAC improved the mechanical properties, especially at a later stage. Adding PP fibers to the RAC containing SS and GGBS significantly increased the splitting tensile strength. However, it had little effect on the compressive strength as the PP fiber content was less than 0.6%. The microscopic experiment revealed that adding GGBS promoted the degree of hydration of SS, reduced the Ca (OH)₂ content, made the ITZ structure more compact, and optimized the pore characteristics of the RAC. Furthermore, according to the raw materials and results of mechanical properties, a hybrid Genetic Algorithm/Artificial Neural Network (GA-ANN) technique was proposed to predict the compressive strength of the RAC containing SS, GGBS, and PP fibers. We found that the proposed GA-ANN model effectively predicts the compressive strength. The findings of this study demonstrate that preparing RAC incorporating SS, GGBS, and PP fibers is promising for the reuse of industrial byproducts and construction waste. Full article

Low-frequency impact sound control remains a critical challenge for floating floor systems. Conventional resilient underlayment materials exhibit insufficient damping and are prone to long-term deformation, making stable low-frequency sound insulation difficult to achieve. This study presents the development of a composite floating floor underlayment comprising recycled rubber granules, polymer resin, and quartz sand. Based on the constrained layer damping-inspired (CLD-inspired) perspective, the vibration attenuation and noise reduction mechanism is elucidated, and the material’s physical properties, mechanical behavior, microstructure, and acoustic performance are systematically investigated. The results indicate that excessively large rubber granules aggravate curing shrinkage cracking. Optimal processing characteristics are achieved with a binder content of 20 wt% and a rubber granule size of 50 mesh. Laboratory characterization reveals that, compared with conventional cross-linked polyethylene (XLPE) foam underlayments, the proposed composite underlayment reduces the impact sound pressure level by an average of 3–5 dB in the low-frequency band below 250 Hz, and the overall sound insulation performance is improved by 10.77%. Dynamic mechanical analysis shows the composite storage modulus declines from 280 MPa at −20 °C to 10 MPa at 80 °C, while the loss factor remains above 0.2 under typical indoor conditions. Such stable viscoelastic behavior enables efficient shear dissipation of low-frequency vibration energy under the CLD-inspired mechanism. Full-scale field testing combined with long-term observation over 3000 loading cycles demonstrates excellent structural compatibility between the underlayment and the gypsum screed, with no cracking or appreciable deformation observed during prolonged service. The weighted impact sound improvement index (ΔLw) attains 15 dB. These findings verify that the CLD-inspired composite underlayment simultaneously achieves efficient low-frequency impact sound control and superior long-term structural stability, providing an innovative material solution and design strategy for impact noise mitigation in residential floating floor applications. Full article

The worldwide spread of semiconductor devices has driven a surge in electronic waste (e-waste), which reached 62 million metric tons in 2022 and is projected to exceed 80 million metric tons by 2030. E-waste contains hazardous substances such as cadmium and mercury, yet also represents a $57 billion annual opportunity through the recovery of valuable and critical raw materials (CRMs). However, formal recycling rates remain stagnant at 22.3%, largely due to limitations of current automated sorting methods. These systems primarily rely on visible-light (RGB) imaging, which lacks the spectral resolution needed to distinguish chemically similar polymers, complex metal alloys, and composite substrates on printed circuit boards (PCBs). This paper presents a multidisciplinary synthesis of AI-driven detection and classification for e-waste, bridging materials science and computer vision through three interconnected themes. 1. Material and Economic Context: The toxicological risks and economic drivers of semiconductor recycling are characterized, framing fine-grained material identification as essential for a circular economy. 2. Multispectral Sensing & Fusion: Sensing modalities such as near-infrared (NIR), hyperspectral imaging (HSI), and X-ray fluorescence (XRF) are assessed, and sensor fusion strategies, including early, late, and intermediate fusion, are reviewed for high-throughput industrial settings. 3. Deep Learning Benchmarking: 11 publicly available PCB datasets are analyzed, and the YOLO series (YOLOv3–YOLOv12) is compared with leading non-YOLO detectors, including Faster R-CNN, RT-DETR-L, and RetinaNet. The results show that while YOLOv9s achieves a peak mAP@0.5 of 56.5% and YOLOv11s offers an optimal industrial profile (37.2% mAP@0.5:0.95 at 115 ms edge inference), all RGB-based models fail to detect visually ambiguous surface-mount devices (SMDs), with mAP values below 12%. This confirms a performance ceiling for purely visual systems. The review concludes that transitioning from RGB-centric to multispectral fusion architectures is the primary research frontier and proposes a roadmap for standardized multimodal datasets and edge-deployable fusion models to enable next-generation, high-recovery automated recycling. Full article

This study aims to systematically evaluate the balancing mechanism between road performance, carbon emissions, and economic cost when selecting asphalt materials for severe cold regions, filling the gap in multi-criteria decision-making for composite chemical modifications. To address alternating temperatures, heavy traffic, and modified asphalt transport difficulties, this study presents a novel evaluation framework focusing on the performance–environmental–cost nexus of a desulfurized rubber powder composite SBS-modified asphalt mixture, which provides a clear technological breakthrough for high-ratio scrap tire recycling in seasonal frost zones. Two reference mixtures serve as comparisons: a conventional rubber powder composite SBS (styrene–butadiene–styrene triblock)-modified asphalt mixture (CR-SBS) and an SBS-modified asphalt mixture (SBS). A comparative experiment was conducted between the two materials and the SBS-modified asphalt mixture (ACR-SBS) compounded with desulfurized rubber powder. High-temperature stability was tested by the rutting test, low-temperature crack resistance by the beam bending test, and water stability by the immersion Marshall and freeze–thaw splitting tests. Life cycle carbon emissions and economic costs were quantified from raw material acquisition to construction. The results show that desulfurized rubber powder composite with ACR-SBS delivers the most superior overall road performance. However, it also generates the highest life cycle carbon footprint. Its total carbon emission reaches 162,800 kgCO₂eq, which is 13.7% (19,600 kgCO₂eq) higher than SBS (143,200 kgCO₂eq) and 7.7% (11,600 kgCO₂eq) higher than CR-SBS (151,200 kgCO₂eq). The total cost of ACR-SBS is 391,000 CNY, which is 1.5% (6000 CNY) higher than SBS (385,000 CNY) and 1.3% (5000 CNY) lower than CR-SBS (396,000 CNY). These findings provide a basis for the selection of high-performance, low-carbon, and economical composite-modified asphalt in severe cold regions. Full article