Search Results (3,228)

Road transport in the European Union is responsible for approximately 60% of PM10 emissions and 45% of PM2.5 emissions. Acoustic agglomeration is researched to be the most effective after-treatment method to control particle pollution. Recent experimental research suggests that at a frequency of around 20 kHz and a sound pressure level of 140 dB, particles can be agglomerated. The kinetic energy of the particles is influenced by the presence of acoustics, and this enhances the collision efficiency between the particles. These collided fine particles increase in size and can be easily filtered through conventional filters. Additionally, clean burning biofuels produce comparatively fewer particles; hence RME is used for experiments along with its two blends of isopropanol (RME95I5 and RME90I10). The results are then compared to those of standard diesel fuel. With an increase in load, an average reduction of 20% in fine particles is observed along with an increase in large-sized particles. The aggregation of smaller particles is observed in a range of 0–50% in almost all tested conditions. With the increase in isopropanol from 5 to 10%, oxygen content in the fuel increased by 7%, a 1% reduction in carbon and a 2% reduction in C/H ratio is observed which led to a 6 and 9% reduction in particle emissions at 60 Nm and 90 Nm, respectively. At higher loads, D100, RME95I5 and RME90I10 recorded an agglomeration of 10%, 111% and 189%, respectively. Similar results are observed for the tendency for agglomeration at lower loads. Full article

Sediment plumes threatening benthic ecosystems are one of the environmental hazards associated with seafloor interventions such as bottom trawling, cabling, dredging, and marine mining operations. This study focuses on sediment plume release from hypothetical future deep-sea mining activities, emphasizing its interaction with turbulent ocean currents in regions characterized by complex seafloor topography. In such environments, turbulent lee waves may significantly enhance the scattering of released sediments, pointing to the clear need for appropriate impact assessment frameworks. Global-scale models are limited in their ability to resolve sufficiently high Reynolds numbers to accurately represent turbulence generated by seafloor topography. To overcome these limitations and effectively assess lee wave dynamics, models must incorporate the full physics of turbulence without simplifying the Navier–Stokes equations and must operate with significantly finer spatial discretization while maintaining a domain large enough to capture the full topographic signal. Considering a seamount in the Lofoten Basin of the Norwegian Sea as an example, we present a novel numerical analysis that explores the interplay between lee wave turbulence and sediment plume dispersion using a high-resolution Large Eddy Simulation (LES) framework. We show that the turbulence occurs within semi-horizontal channels that emerge beyond the topographic highs and extend into sheet-like tails close to the seafloor. In scenarios simulating sediment release from various sites on the seamount, our model predicts distinct behavior patterns for different particle sizes. Particles with larger settling velocities tend to deposit onto the seafloor within 50–200 m of release sites. Conversely, particles with lower settling velocities are more susceptible to turbulent transport, potentially traveling greater distances while experiencing faster dilution. Based on our scenarios, we estimate that the plume concentration may dilute below 1 ppm at about 2 km distance from the release site. Although our analysis shows that mixing with ambient seawater results in rapid dilution to low concentrations, it appears crucial to account for the effects of topographic lee wave turbulence in impact assessments related to man-made sediment plumes. Our high-resolution numerical simulations enable the identification of sediment particle size groups that are most likely affected by turbulence, providing valuable insights for developing targeted mitigation strategies. Full article

The integration of electric railways with renewable energy sources is crucial for advancing sustainable transportation and building clean, low-carbon, and efficient energy systems in alignment with global sustainable development goals. However, the application of photovoltaic (PV) integration into railway traction power supply systems may exacerbate resonance phenomena between electric locomotives and the traction network. It is therefore necessary to study the impedance frequency characteristics (IFCs) of traction networks to minimize harmonic resonance overvoltage. In this paper, a harmonic impedance model of the sustainable traction power supply system (STPSS) is established, and an impedance analysis method is adopted to reveal the influence law of grid-connected PV inverters on the IFCs of STPSSs. Additionally, to improve the stability of STPSSs, a multi-parameter co-tuning method based on an improved particle swarm optimization algorithm is proposed. This method constructs a multi-objective function that includes resonance frequency, impedance magnitude, and filtering cost, thereby realizing the automatic optimization of the control parameters and filtering parameters of PV inverters. The results demonstrate a 56% reduction in the maximum impedance magnitude within the 0–5 kHz frequency range and a 10.8% cost reduction in the LCL filter implementation, confirming the effectiveness of the proposed optimization model. Results show that the maximum impedance magnitude of the optimized system in the frequency range of 0–5 kHz can be reduced by 56%. Moreover, the cost of LCL filters can be reduced by 10.8% through component value optimization. These findings validate the effectiveness of the proposed method. Full article

Granular materials usually require the design of specialised equipment for their processing and transport. Nowadays, equipment design increasingly relies on modelling techniques to support decision-making during the design process. The Discrete Element Method (DEM) is a numerical technique that enables the prediction of forces and displacements acting on individual particles. The design of ship loaders, dumpers, screw conveyors, conveyor belts, moving floors, bucket elevators, truck feeders, hoppers, and silos can all benefit from DEM-based predictions of particle behaviour. To develop DEM models able to accurately predict the particle behaviour, it is essential to characterise the material by determining its physical and mechanical properties. Key parameters include particle density, elastic modulus, Poisson’s ratio, particle-to-wall friction, and particle-to-particle friction. In this research, a methodology is proposed for determining the particle-to-particle friction coefficient. For this purpose, a test apparatus was designed and constructed to perform direct measurements of sliding angles. The proposed method yielded an average particle-to-particle friction coefficient of μ = 0.62, based on twelve independent sliding-angle tests. The measurements showed an overall relative standard deviation of 3.4%, indicating good repeatability and demonstrating that the developed apparatus provides reliable and consistent friction values for granular particles. The primary aim of the study was to validate the test method. Hand-made clay samples were produced, arranging the particles in different configurations and placing them in various orientations on the apparatus. The results confirm that the proposed method is suitable for determining representative particle-scale friction parameters, offering a simple and repeatable approach that can support DEM calibration and enhance the predictive capability of granular flow simulations. Full article

The disposal of coal mine solid waste has always been a challenge in the coal mining production process, and the research and development of low-cost and high-performance filling materials is a prerequisite for achieving large-scale disposal of coal mine solid waste. The effects of water–cement ratio, foaming agent dilution ratio, foam agent content, foam stabilizer content, and gypsum content on the mechanical properties, transportation characteristics, and microstructure of cement foam filling materials were studied by laboratory test methods. The optimal ratio of cement foam filling material for comprehensive performance was determined. On this basis, the mechanism of influence of fly ash content, gangue content, and gangue particle size on the mechanics, transportation characteristics, and microstructure of foam filling materials was further studied. The experimental results show that at fly ash contents below 30%, gangue content is less than 30%. The particle size of gangue is less than 0.6 mm, and the expansion ratio of coal mine solid waste foam filling material is about three times, which has good mechanical properties and transportation performance. The on-site test results show that the control effect of the surrounding rock in the goaf is good, achieving safe and efficient mining of the working face. Full article

To optimize the corrosion mitigation process in the annular space of oil and gas well pipelines, this study introduces a secondary acceleration pneumatic conveying device for particles within the confined spaces of offshore oil and gas wells. This approach addresses the limitations of traditional offshore hydraulic transportation, which can lead to corrosion failure of drug particles. The study investigates the motion mechanisms of drug particles within the pipeline and identifies the critical structural parameters that influence the smooth transport of these particles. A DEM-CFD coupled simulation methodology was employed to conduct single-factor experiments on the minimum air pressure and particle injection quantity required for stable transportation. The results demonstrate that at an air pressure of 0.25 MPa, no particle retention or accumulation occurs within the pipeline, thereby satisfying the engineering requirements. A Box–Behnken three-factor, three-level experimental design was used to perform response surface analysis on the pneumatic device. The findings reveal that the particle outlet velocity initially increases and then decreases with the air injection angle, while the outlet velocity progressively increases with the diameter of the conveying hole and the number of small holes. The maximum outlet velocity achieved is 8 m/s, with the optimal structural parameters identified as an air injection hole diameter of 2.96 mm, an air injection angle of 47°, and 24 small holes. The simulation model was calibrated and validated through fluidized bed experiments, and the simulation optimization was further confirmed via bench-scale particle transportation tests. This research provides a theoretical framework and engineering guidance for optimizing pneumatic particle transport in the confined spaces of offshore oil and gas wells. Full article

In this study, molybdenum disulfide (MoS₂)-based water nanofluids were prepared and stabilized using two surfactants with opposite charges: the cationic cetyltrimethylammonium bromide (CTAB) and the anionic sodium lauryl sulfate (SLS). Different MoS₂:surfactant ratios (1:1, 1:2, and 1:3) were examined to identify the optimal formulation ensuring stable dispersion. Stability was evaluated through dynamic light scattering (DLS), zeta potential, and UV–Vis spectroscopy analyses. The results showed that the MoS₂:SLS (1:3) nanofluid achieved the highest stability, characterized by a zeta potential of −38 mV and a mean particle size of approximately 290 nm. Thermophysical properties were then investigated for nanoparticle concentrations of 0.05, 0.1, and 0.2 wt%. The 0.1 wt% nanofluid exhibited the best performance, showing a thermal conductivity enhancement of about 49% and an increased specific heat capacity compared with pure water. This improvement is attributed to uniform nanoparticle dispersion and enhanced phonon transport. Overall, the results demonstrate that the anionic SLS surfactant at a 1:3 ratio effectively enhances the stability as well as the thermal performance of MoS₂–water nanofluids, making them promising candidates for thermal management and energy systems applications. Full article

Gold (Au) and silver (Ag) nanoparticles (NPs) are used for drug transport and plant protection due to their insoluble nature and unique properties. To produce health-friendly NPs, toxic solvents should be replaced with plant-based synthesis. Plants, such as alfalfa (Medicago sativa L.), release biomolecules that reduce metal ions and form nanoclusters without free radicals, showing anti-inflammatory and antioxidant properties. In this study, callus cultures of two M. sativa genotypes, ‘Kometa’ and ‘La Bella Campagnola’, were exposed to two precursors (AgNO₃ and HAuCl₄) for 24 and 48 h to assess the feasibility of biological NP synthesis. Spectrophotometry showed significant (p ≤ 0.05) changes in light absorbance compared with the control. Dynamic light scattering and zeta potential measurements indicated a change in the composition of the liquid compared with the control. To improve image quality and obtain more accurate data, transmission electron microscopy (TEM) analysis was repeated, confirming the presence of quasi-spherical nanoparticles with diameters in the range of 5–25 nm for both AuNPs and AgNPs in the callus culture extracts of both genotypes. Nanoparticle Tracking Analysis demonstrated that the AgNPs and AuNPs from both genotypes displayed polydisperse size distributions, with a mean particle size ranging from 220 to 243 nm. Elemental analysis provided clear evidence that Ag and Au were present only in treated samples, confirming effective NP biosynthesis and excluding contamination. X-ray diffraction (XRD) analysis was performed to characterise the crystalline structure; however, due to the very small particle size (5–25 nm), no clear diffraction patterns could be obtained, as nanocrystals below ~20–30 nm typically produce signals below the detection limit of standard XRD instrumentation. The novelty of this research is the cost-effective, rapid biosynthesis of quasi-spherical AuNPs and AgNPs with diverse sizes and enhanced properties, making them more eco-friendly, less toxic, and suitable for antibacterial and anticancer studies. Full article

The widespread and excessive use of plastic in our daily life has led to serious microplastic pollution in the atmosphere, water, and soil. These microplastics can enter freshwater systems and pose significant risks to the ecosystem and human health via the food chain. This environmental problem deserves proper investigation and mitigation strategies. In this study, the abundance, morphology, color, size and polymer composition of microplastics in surface water of Feiyun River Basin were systematically studied by means of field sampling, microscopy and laser micro-Raman spectroscopy. The result showed that microplastic abundance ranged from 3.7 to 36.4 items/L, with an average of 11.0 ± 2.39 items/L. These microplastics were mainly particles, followed by fragments and fibers, with white, black, and blue being the most common colors. Most of the particles were smaller than 0.1 mm (57%), and a laser micro-Raman spectrometer was used to identify the polymer types of the microplastics. The results showed that the main polymer types identified were PET, PP, and PS. Risk assessment based on PLI, PHI, and PERI indices indicated a low ecological risk of microplastics in the study area. These findings provide further insight into the sources and distribution of microplastics in local watersheds and support future assessments of riverine transport of microplastics to estuarine and marine environments. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer mortality, with therapeutic resistance posing the primary barrier to durable outcomes. Beyond genetic and epigenetic alterations, amino acid transporter-driven metabolic reprogramming—mediated by LAT1 (SLC7A5), ASCT2 (SLC1A5), and xCT (SLC7A11)—supports tumor proliferation, redox homeostasis, and immune escape. Their preferential expression in NSCLC highlights their potential as therapeutic targets and predictive biomarkers. In parallel, α-particle therapy has gained attention for its capacity to eradicate resistant clones through densely clustered, irreparable DNA double-strand breaks. Astatine-211 (²¹¹At) combines a clinically relevant half-life, high linear energy transfer, and predictable decay scheme, positioning it as a unique candidate among α-emitters. Preclinical studies of ²¹¹At-labeled transporter ligands, particularly LAT1-targeted conjugates, demonstrate potent tumor suppression and synergy with targeted therapy, chemotherapy, radiotherapy, immunotherapy, and ferroptosis inducers. Advances in radiochemistry, delivery systems (antibodies, peptides, and nanocarriers), and PET tracers such as [¹⁸F]FAMT and [¹⁸F]FSPG collectively support a theranostic framework for patient stratification and adaptive dosing. By linking transporter biology with α-particle delivery, ²¹¹At-based theranostics offer a mechanistically orthogonal strategy to overcome resistance and heterogeneity in NSCLC. Successful translation will depend on precise dosimetry, scaffold stabilization, and biomarker-guided trial design, enabling progression toward first-in-human studies and future integration into multimodal NSCLC therapy. Full article

Transportation constitutes a major source of global greenhouse gas emissions. As a low-carbon fuel alternative, the design efficiency and performance of Liquefied Natural Gas (LNG) storage tanks for vehicles are critically important. However, traditional design methods have a low degree of automation and lack standardized assessment, which can easily lead to repetitive design modifications, causing resource waste and restricting the process of green development. Based on the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and three-dimensional modeling technology, this study proposes an intelligent design and automated modeling method for vehicle LNG storage tanks oriented towards sustainable design. The results demonstrate that this method completes both tank parameter design and model generation within 30 min. Compared to traditional designs, the proposed method achieves an 8.992% reduction in heat dissipation, a 26.015% reduction in inner vessel compressive deformation, with a trade-off of a 14.452% increase in total weight. This design approach significantly enhances material utilization efficiency and environmental benefits by optimizing resource allocation and performance balance, providing effective technical support for strengthening the sustainability of LNG storage tank design. Full article

Dredged sludge is characterized by a high water content, low permeability, and poor load-bearing capacity, which hinder its sustainable utilization as an engineering filler. During the stabilization process using vacuum preloading (VP), fine-grained sludge readily clogs drainage channels, thereby prolonging consolidation duration and compromising drainage efficiency. To address these persistent challenges, this study proposes an improved method that combines electroosmosis, VP, and polyacrylamide (PAM) to enhance the consolidation performance of dredged sludge. Column settling experiments demonstrated that the optimal application dosages of anionic polyacrylamide (APAM) and calcium chloride (CaCl₂) were 0.25% and 4.0% of dry sludge mass, respectively. Excessive dosage of either APAM or CaCl₂ disturbed the agglomeration and sedimentation of fine-grained particles due to surface charge inversion. Electroosmotic VP (EVP) facilitated the directional movement of pore water, which increased the cumulative water discharge mass by 37.3%. The combination of APAM and CaCl₂ enhanced particle flocculation via adsorption and bridging effects, significantly improving soil permeability and dewatering performance. Driven by an electric field, Ca²⁺ ions transported water molecules toward the cathode. Subsequently, these Ca²⁺ ions participated in reactions to generate cementitious agents. Compared with VP, this integrated method increased the sludge shear strength by 108.1% and produced a much denser microstructure. Full article

The Discrete Element Method (DEM) has become a cornerstone for analysing granular flow and mixing phenomena in static mixers. This review provides a comprehensive synthesis that distinguishes it from previous studies by: (i) covering a broad range of static mixer geometries, including Kenics, SMX, and Sulzer designs; (ii) integrating experimental validation methods, such as particle tracking, high-speed imaging, Particle Image Velocimetry (PIV), and X-ray tomography, to assess DEM predictions; and (iii) systematically analyzing computational strategies, including advanced contact models, hybrid DEM-CFD/FEM frameworks, machine learning surrogates, and GPU-accelerated simulations. Recent advances in contact mechanics—such as improved cohesion, rolling resistance, and nonspherical particle modelling—have enhanced simulation realism, while adaptive time-stepping and coarse-graining improve computational efficiency. DEM studies have revealed several non-obvious relationships between mixer geometry and particle dynamics. Variations in blade pitch, helix angle, and element arrangement significantly affect local velocity fields, mixing uniformity, and energy dissipation. Alternating left–right element orientations promote cross-sectional particle exchange and reduce stagnant regions, whereas higher pitch angles enhance axial transport but can weaken radial mixing. Particle–wall friction and surface roughness strongly govern shear layer formation and segregation intensity, demonstrating the need for geometry-specific optimization. Comparative analyses elucidate how particle–wall interactions and channel structure influence segregation, residence time, and energy dissipation. The review also identifies current limitations, highlights validation and scale-up challenges, and outlines key directions for developing faster, more physically grounded DEM models, providing practical guidance for industrial mixer design and optimization. Full article

Tire–road friction is a fundamental factor in vehicle safety, energy efficiency, and environmental sustainability. This narrative review synthesizes current knowledge on the tire–road friction coefficient (TRFC), emphasizing its dynamic nature and the interplay of factors such as tire composition, tread design, road surface texture, temperature, load, and inflation pressure. Friction mechanisms, adhesion, and hysteresis are analyzed alongside their dependence on environmental and operational conditions. The study highlights the challenges posed by emerging mobility paradigms, including electric and autonomous vehicles, which demand specialized tires to manage higher loads, torque, and dynamic behaviors. The review identifies persistent research gaps, such as real-time TRFC estimation methods and the modeling of combined environmental effects. It explores tire–road interaction models and finite element approaches, while proposing future directions integrating artificial intelligence and machine learning for enhanced accuracy. The implications of the Euro 7 regulations, which limit tire wear particle emissions, are discussed, highlighting the need for sustainable tire materials and green manufacturing processes. By linking bibliometric trends, experimental findings, and technological innovations, this review underscores the importance of balancing grip, durability, and rolling resistance to meet safety, efficiency, and environmental goals. It concludes that optimizing friction coefficients is essential for advancing intelligent, sustainable, and regulation-compliant mobility systems, paving the way for safer and greener transportation solutions. Full article

Vegetables are crucial to human diet and health. To ensure sustainable vegetable production, regulatory measures are needed to enhance seed germination, plant growth, and resilience to extreme environmental conditions. Nanomaterials (NMs), owing to their high surface area, nanoscale dimensions, and unique photocatalytic properties, exhibit remarkable biological effects, such as promoting germination and growth, as well as improving stress resistance in crops, offering novel solutions to key challenges in vegetable cultivation. This review summarizes the absorption pathways of NMs in plants, specifically through the leaves and roots of vegetables. Their uptake and translocation occur via passive diffusion, active transport, and endocytosis, with key influencing factors including particle size, chemical composition, surface charge, and surface modifications. We further evaluate the advantages of nanofertilizers and nanopesticides, in vegetable production over their traditional counterparts, focusing on improvements in seed germination rates, seedling vigor, biotic and abiotic stress tolerance, and overall yield and quality. Through this review, we aim to offer comprehensive insights into the application of NMs in vegetable crop production. Full article