Search Results (938)

In the present study, we evaluate the CO₂ uptake capacities of four activated carbons (ACs) obtained from olive stones. Two of the samples were generated using a chemical process utilizing phosphoric acid, thereafter undergoing carbonization in a nitrogen steam, yielding both granular and pellet forms, designated CH-ACG-410 and CH-ACP-410, respectively. The third sample, labeled CO-ACG-390, was produced by carbonization under a steam-nitrogen flow, while the fourth sample, designated PH-ACG-850, was prepared by a physical process involving water vapor at 850 °C. The carbon materials obtained in granular and pellet form were subjected to textural characterization using N₂ and CO₂ adsorption isotherms at 77 K and 273 K, respectively. Additionally, surface chemistry was analyzed using FTIR, Boehm titration, and TPD-MS. The materials were also assessed for CO₂ adsorption in a binary mixture consisting of 10% CO₂ and 90% N₂ at two temperatures, 25 and 50 °C. The results demonstrated that all prepared adsorbents exhibited competitive CO₂ capture performance, with the CH-ACP-410 sample (pellet form), showing the highest adsorption capacities, achieving approximately 4.6 wt. % at 25 °C and 2.2 wt. % at 50 °C. This superior behavior can be attributed to the conditioning methods applied to this material, which significantly influenced its textural properties and, consequently, its CO₂ adsorption capability. Full article

The inherent hydrophobicity of polyolefin separators significantly impedes rapid electrolyte wetting, thereby limiting the electrochemical performance of lithium-ion batteries. Cellulose, as a hydroxyl-rich natural polymer, serves as an ideal material for enhancing the interface properties of separators. However, there is still a lack of systematic understanding regarding how the morphological structures of cellulose (such as granular, fibrous, or network-like forms) influence the coating structure and ion transport mechanisms. Here, three representative cellulose derivatives—microcrystalline cellulose (MCC), cellulose nanofibers (CNF), and bacterial cellulose (BC)—were selected to construct functionalized polypropylene (PP) composite separators through vacuum filtration. Experimental results demonstrate that all three cellulose coatings reduced contact angles from 50.8° to below 10°, significantly enhancing interfacial affinity. Systematic comparison reveals that cellulose configuration decisively influences separator performance: unlike the dense fiber entanglement networks formed by CNF and BC, the unique rigid granular packing structure of MCC maintains hydrophilicity while establishing more permeable ion transport pathways. Among these, MCC@PP exhibited optimal electrochemical performance, with the lithium-ion migration number increasing to 0.41 and a capacity retention rate of 88.04% after 100 cycles at 0.5 A/g. This study elucidates the relationship between cellulose configuration and the modification of separator performance, demonstrating that MCC represents a more efficient, robust, and cost-effective option for separator modification compared to complex fiber networks. Full article

Adsorption is a promising solution to the presence of contaminants in water resources that involves the use of adsorbent materials, such as granular activated carbon (GAC) and nanoparticles like silver (Ag) and copper (Cu). However, the practical challenge of using pure GAC lies in its susceptibility to biofouling. This study aimed to develop a multifunctional GAC/AgCu nanocomposite to address the dual challenge of pharmaceutical contamination and bacterial activity of Escherichia coli. Characterization by SEM, XRF, XRD and FTIR confirmed the successful impregnation of nanoparticles. Kinetic studies showed that the pseudo-first-order model was more suitable for both caffeine and paracetamol contaminants. The Langmuir model provided the best fit for isotherms, achieving maximum adsorption capacities of 138.35 $\mathrm{m}\mathrm{g} {\mathrm{g}}^{-1}$ for caffeine and 92.21 $\mathrm{m}\mathrm{g} {\mathrm{g}}^{-1}$ for paracetamol. In antibacterial tests, GAC/AgCu achieved a bacterial reduction of over 97%, whereas pure GAC showed no inhibitory effect, confirming that the antimicrobial properties are derived from the Ag and Cu nanoparticles. These results highlight GAC/AgCu as a promising multifunctional material for the simultaneous removal of emerging pharmaceutical pollutants and biological contaminants, offering a solution to mitigate biofouling and enhance water treatment efficiency. Full article

This study situates Environmental Product Declarations (EPDs) within the broader challenge of decarbonising the built environment, arguing that efficiency-oriented approaches remain insufficient unless complemented by a sufficiency paradigm that already questions “how much is necessary” in the meta-design phase. Building on an interdisciplinary reading of standards and the scientific literature, the paper analyses the regulatory architecture of Type III environmental declarations and discusses the operational implications of the two main reference frameworks for construction EPDs—ISO 21930 (global) and EN 15804 (European)—with attention paid to methodological rigidity, system boundaries, and the granularity of climate-related indicators. The paper highlights that the declared aim of comparability is frequently undermined in practice by heterogeneous Product Category Rules, background databases, modelling assumptions, and verification practices, producing an “illusion of comparability” and limiting the reliability of product-to-product comparisons. Emphasis is placed on the epistemic role of the functional unit and reference service life, showing how narrowly product-based units can conceal system-level effects and bias decision-making. The paper concludes that EPDs are most effective when interpreted as boundary objects linking policy, industry, and design, and when embedded in a sufficiency-oriented “critical ecology of materials” that integrates embodied and operational carbon within contextualised project decisions. Full article

Calculation of heat transfer in granular materials is an important task for many applications, from thermal management in electronics to exploring celestial soils. Usually, an effective thermal-conductivity model is employed to predict heat flux in unstructured granular media, such as a packed bed. However, a more advanced approach, the discrete element method (DEM), can capture the complex effects of mechanical loading and material mixtures on thermal transport coefficients, which traditional models struggle with. Pivotal for this approach is knowing the heat transfer coefficient between two adjacent particles. Currently, in most DEM-capable software, only particles in direct surface contact are considered to have non-zero heat conduction. We propose considering particles that are close to each other but don’t have a contact area with a non-zero surface area. We perform numerical modeling of the conductive heat transfer coefficient between equal spherical particles separated by media, assuming the fluid’s thermal conductivity is at least an order of magnitude lower. We use numerical solutions of differential equations to account for both thermal resistance within particles and through the gap between them. We found a simple generalized correlation for the heat transfer coefficient between particles and a general formula for the angular distribution of heat flux density across the particle surface. By employing a non-dimensional approach, the obtained formulas are constructed using non-dimensional parameters: the ratio of the particle’s thermal conductivity to that of the medium, and the ratio of the gap width between particles to their radius. The resulting formula is simple and convenient for DEM heat transfer calculations in packed and fluidized beds. Full article

The modification of road bitumen using micro-sized carbonaceous materials offers a promising route to enhance pavement performance; however, the influence of microdispersed coke derived from coal and petroleum sources has not been sufficiently clarified. In this study, coal and petroleum coke from Pavlodar Petrochemical Plant LLC (Pavlodar, Kazakhstan) were mechanochemically activated and used as the modifiers for BND 100/130 bitumen, produced by Asphaltbeton 1 LLC (Almaty, Kazakhstan). X-ray diffraction and scanning electron microscopy were used to determine the structure and morphology of the resulting coke powders. Standard tests and the Superpave Multiple Stress Creep and Recovery (MSCR) methodology were used to determine the physico-mechanical and rheological properties of the modified binders. Microdispersed granular coke powders produced after mechanochemical activation had a minimum average particle diameter of 8.28 µm (petroleum coke) and 16.64 µm (coal coke), and were mainly an amorphous carbon phase with traces of graphite. Addition of 1 wt.% microdispersed coke resulted in better performance of binder and an enhancement in grades of BND 100/130 to BND 70/100, in line with ST RK 1373-2013. MSCR testing showed that Jnr_3.2 is between 2.0–3.0 kPa⁻¹, which is in the S category of AASHTO M 332-20. This study showed how micro-sized coal and petroleum coke can be effectively used as a high-carbon modifier in bitumen, which reflects the possibility of their practical use in asphalt pavements that are subjected to normal traffic conditions. Full article

The physical structure formed during the packing of granular grain constitutes a fundamental ecological factor within the grain bulk ecosystem. Accurate simulations of grain-packing behavior help to deepen our understanding of this ecosystem. In this study, a white hard wheat was selected as the test material, and a high-fidelity multi-sphere discrete element model of wheat kernels was constructed using three-dimensional laser scanning. Physical experiments were conducted to determine the basic physical properties of the kernels, including true density and bulk density. Using the angle of repose as the calibration parameter, the wheat-packing process was investigated with the discrete element method (DEM). The results indicated that the coefficients of static and rolling friction between particles were highly significant factors governing the angle of repose. The optimal parameter combination consisted of a particle–particle coefficient of restitution of 0.500, a coefficient of static friction of 0.388, and a coefficient of rolling friction of 0.054. The mean angle of repose obtained from the DEM packing simulation was 28.46°, corresponding to a relative error of 3.16% compared with the physical experiment. This calibrated parameter set is therefore considered accurate and reliable, and it provides baseline data for DEM simulations of wheat grain bulks. Full article

Granular materials exhibit complex mechanical behaviors during unloading, yet the underlying micro- and meso-scale mechanisms remain unclear. This study employs a discrete element method to simulate a series of triaxial tests on sand and pebble specimens with varying initial densities under different unloading stress paths. While dense specimens demonstrate strain softening and dilatancy, loose samples exhibit shear contraction. To quantify the underlying fabric evolution, persistent homology (PH) theory is adopted to analyze the particle contact force networks. The results reveal that the average strength of this network correlates strongly with the macroscopic stress–strain response. For dense samples, network strength rapidly increases to a peak coinciding with the deviatoric stress maximum, then gradually decreases with further shear. Crucially, this evolution is path-dependent: the average contact force network strength increases approximately 20% more during unloading in the minor principal stress direction compared to unloading in the major principal stress direction. This quantitative analysis of force chain degradation provides a mechanistic explanation for the observed strain softening, highlighting the dominant role of the unloading stress path. In contrast, loose specimens, which initially lack an obvious force chain network, show negligible microstructural evolution during unloading. Full article

Lost circulation remains a persistent and costly challenge in drilling operations for oil, gas, and geothermal energy systems, particularly when wide fractures and cavernous formations are encountered. Although a wide range of lost circulation materials (LCMs) is commercially available, multiple laboratory studies report that many conventional products are unable to effectively seal fractures of approximately 5 mm width under controlled conditions. In contrast, recent investigations of shape memory polymer (SMP)-based LCMs have demonstrated successful sealing of fractures up to approximately 12 mm in width. This review examines recent advances in SMP-based LCMs as an emerging class of smart materials capable of overcoming geometric and operational constraints associated with drilling equipment, particularly bottom-hole assembly (BHA) components. Through thermomechanical programming, these materials are transformed into compact temporary shapes suitable for seamless circulation and are subsequently triggered by reservoir temperatures to recover permanent geometries up to an order of magnitude larger. Upon activation, these discrete elements function collectively as a hierarchical, jammed system. The resulting multiscale networks—comprising ladder-shaped elements, interwoven fibers, and granular particles—bridge large apertures, enhance mechanical interlocking, and achieve superior hydraulic isolation. Full article

In situ stope leaching is an economically and environmentally friendly metal recovery method suitable for low-grade copper ores, with the internal temperature of the deposit typically ranging from 30 to 45 °C. The fragmented ore with a specific particle size distribution formed after blasting constitutes a complex pore structure, which provides channels for acid solution infiltration and chemical reactions, directly affecting leaching efficiency. To reveal the spatiotemporal heterogeneity of pore structure evolution during leaching at the microscopic level and its fundamental impact on macroscopic permeability and leaching rate, leaching experiments were conducted using acid leaching methods based on ore particle models with different size distributions. Computed Tomography (CT) scanning technology and Avizo 2023 software were employed to scan and reconstruct three-dimensional physical models, enabling quantitative calculation and analysis of the evolutionary patterns of pore structure parameters. These results were then correlated with the measured leaching rate evolution. The findings indicate that both the connectivity and overall volumetric porosity of the stope models for Sample 1 (2–20 mm, uniformly graded) and Sample 2 (0–20 mm, high fine particle content) continuously decreased during leaching, with a more pronounced decline in the lower regions, particularly for Sample 2. The pore-throat sizes of both models increased with leaching time, and after 45 days of leaching, the average pore radius of the two granular ore samples increased by 16.75% and 9.21%, respectively. The leaching rate showed a high correlation with the effective reaction area (R² = 0.93). During the 0–15-day period, a sharp decline in the effective reaction area led to a rapid decrease in leaching efficiency. Sample 1 exhibited a longer effective leaching duration, achieving a leaching rate of 61%, significantly higher than that of Sample 2. Full article

The implementation of Australia’s 2024 waste export ban has increased pressure on domestic recycling systems, resulting in an additional 650,000 tonnes of waste annually. This emphasises the urgent need for high volume landfill waste material recovery, especially in sustainable construction materials such as geopolymer concrete (GPC). Geopolymer concrete is recognised as a sustainable construction material; however, the scientific understanding of the compatibility between landfill waste and the geopolymer matrix, particularly under harsh environments, remains unknown. This paper presents an experimental investigation on five types of geopolymer concrete (GPC) mixes. The study included a control mix with natural stone chips and four additional mixes in which stone chips were 100% replaced with waste materials including shredded plastic, cardboard, crushed glass, and granular crumb rubber as fine aggregates. The mechanical performance, durability behaviour and stress-strain characteristics of these mixes were evaluated. Concrete samples were exposed to normal air, a saline environment with 10% salinity, and a hygrothermal environment at 60 °C and 98% humidity for four months to assess durability performance. The results demonstrate that GPC is compatible with landfill waste aggregates and enables the production of a workable mixture. As a result of saline environments, waste aggregate-based geopolymer concrete reduces compressive strength by 15%, while natural stone chips-based geopolymer concrete decreases strength by 45% during the same period, indicating that waste aggregates are more appropriate than natural aggregates in marine environments. Although the inclusion of waste aggregates reduces the strength and stiffness of the GPC, the materials continue to meet the mechanical property requirements for non-structural applications. A theoretical model considering the elastic modulus, ultimate strength and corresponding strain has been developed to predict compressive stress–strain behaviour of waste-based GPC. High modulus aggregates, typically ranging from approximately 10.0 GPa to 85.0 GPa such as stone chips and glass sand demonstrate parabolic stress–strain behaviour. In contrast low modulus aggregates, generally ranging from 1.0 GPa to 5.0 GPa including plastic, cardboard, and crumb rubber, exhibit a bilinear stress–strain response. Full article

Soft robotics has become a dynamic field that emphasizes adaptability and safe interaction with complex environments. These structures utilize deformable materials and continuum mechanics to adapt their shape, absorb shocks, and perform tasks in unstructured environments. However, the design and optimization of these systems is challenging, primarily due to the nonlinear and discontinuous behavior of granular materials. In this paper, we address the role of simulation frames as an important tool for understanding, designing, and extending the functionality of software robotic devices utilizing granular jamming. The analysis suggests that DEM is essential for capturing particle-level mechanisms, while FEM is more effective for system-level optimization but tends to smooth out the transition of jamming. Hybrid FEM–DEM approaches provide the highest physical accuracy, albeit at an increased computational cost. Overall, the findings emphasize that the choice of framework must be application-oriented and that multiphysics coupling represents the future development. The review gives an up-do-date review of the simulation tools and approaches for granular-jamming-based systems with a specific focus on continuum arms with a granular-jamming-based central backbone. Such methods can be used for the optimization the back-bone geometry and its filling material (shape, porosity, granule size) with possible use in the real-time control of such arms. Full article

The rapid digitalization of power systems and the growing penetration of variable renewable energy sources have intensified the need for flexible and resilient smart-grid architectures capable of coordinating cross-sector energy flows. This review aims to provide a system-level synthesis of the artificial-intelligence-enabled integration of smart grids and green hydrogen, explicitly addressing coordination across physical infrastructure, digital control layers, market mechanisms, and environmental constraints. Following the PRISMA 2020 framework, 142 high-relevance studies published between 2010 and 2025 were systematically screened and classified into five interdependent thematic pillars: demand-side flexibility, ICT and IoT infrastructures, cybersecurity and resilience, communication and control performance, and AI-based optimization and decision-making. The synthesis reveals three principal findings. First, while core technologies such as photovoltaics, battery storage, and proton exchange membrane electrolyzers exhibit high component-level maturity, system-integration readiness remains limited by interoperability, communication latency, cybersecurity compliance, and market eligibility constraints. Second, electrolyzers can technically provide fast-response and multi-timescale flexibility services, yet their economic viability depends strongly on market product granularity, settlement intervals, and regulatory frameworks. Third, environmental and resource constraints, including water availability and material criticality, are emerging as binding factors that must be embedded directly into planning and optimization models. Overall, the review positions artificial intelligence as a cross-layer coordination mechanism that links operational control, digital observability, market participation, and sustainability boundaries, providing an integrated architecture to guide scalable and resilient smart grid–hydrogen deployment. Full article

Earth-based materials are increasingly considered as low-carbon alternatives for sustainable building construction. However, the high variability of natural soils and the complex behaviour of their clay fraction remain major barriers to the standardisation of characterisation and formulation methods. This study proposes a methodological and experimental framework based on the fine fraction (<400 µm) of soils to predict the fresh-state and hardened-state performance of earthen construction materials. Two natural soils from southwestern France with contrasted mineralogical compositions were investigated using rheological studies, compaction, linear shrinkage, and unconfined compressive strength (UCS) tests. The results show that the fine fraction plays a dominant role in governing material behaviour: smectite-rich soils reach higher dry densities (up to ≈2.10 g·cm⁻³) and compressive strengths (up to ≈6 MPa) but exhibit greater shrinkage sensitivity, whereas kaolinite–illite-rich soils display reduced shrinkage and improved dimensional stability. By demonstrating the predictive capacity of fine-fraction-based indicators for mechanical performance and dimensional stability, this work contributes to the development of simplified, reproducible, and environmentally relevant methodologies for the design of low-carbon earthen building materials using locally sourced soils. Full article

Soil–steel interface shear governs load transfer and long-term serviceability in piles, retaining systems, and buried infrastructure; yet the large-displacement interface mechanics of fibre-reinforced sands remain poorly resolved, limiting sustainable design. This study couples large-displacement ring-shear testing with physics-guided hybrid AI to quantify and predict the peak and residual resistance of sand–polypropylene fibre mixtures sliding on smooth and rough steel. Two quartz sands with contrasting particle morphology were tested under 25–200 kPa normal stress and 0–1.0% fibre content, producing a design-oriented database that captures post-peak evolution and residual states. The experiments reveal a strongly nonlinear reinforcement law: an optimum fibre range enhances dilation, stabilises the shear band, suppresses post-peak softening, and increases residual strength, whereas excessive fibres disrupt the granular skeleton and reduce mobilisation efficiency. Roughness and confinement act as amplifiers, intensifying fibre-driven dilation and asperity interlock. To translate mechanisms into prediction, three strategies were benchmarked: a deep neural network (DNN), the Physics-Guided Neural Additive Model (PG-NAM++), and the physics-anchored Residual-DNN that learns only the correction to a mechanical baseline. Residual-DNN achieved the tightest agreement and the highest physical consistency for both peak and residual strength, enabling robust parameter selection with reduced uncertainty and overdesign. The combined experimental–AI framework advances the United Nations Sustainable Development Goals (SDGs) by supporting SDG 9 through resilient, innovation-led infrastructure design and contributing to SDG 12 by enabling optimised (rather than maximal) use and reuse of reinforcement materials within circular ground-improvement practice. Full article