Search Results (1,312)

The objective of this study was to establish the kinetic of gasification reactions involved in chemical looping gasification (CLG) using pelletized biomass as solid fuel. However, significant limitations have been found in obtaining such kinetics using a traditional methodology from a large number of tests in a thermogravimetric analyzer (TGA) for pelleted biomass. A novel methodology is presented in this article, namely: (i) the determination of the intrinsic gasification rate for several biomasses; (ii) the determination of the gasification rate of pelletized biomass under selected operating conditions; (iii) the development and validation of a reaction model for pelletized biomass considering the determined intrinsic kinetics and gas diffusion in the biomass particles; and (iv) obtaining an apparent kinetics from data calculated with the developed model, which will be easy to implement in the modeling of gasifiers. To evaluate the applicability of this methodology, it was demonstrated with three different types of biomasses: pine forest residue (PFR), industrial wood pellets (IWP), and wheat straw pellets (WSP). The intrinsic kinetics was derived from tests with powdered char under several operating conditions: reacting temperature (1073–1223 K), concentration of gasifying agent (10–40 vol.% H₂O or CO₂), and concentration of gasification product (0–40 vol.% H₂ or CO). The evolution of the char conversion with the reacting time was predicted using a model involving three different regimes: (I) deactivation at the beginning; (II) uniform progress in the main middle part following a n-order model; and (III) catalytic activation as complete conversion is approached. The second regime was included for all biomasses, being 1, 0.4, and zero-order for WSP, IWP, and PFR, respectively. However, the third regime was observed for PFR and IWP, and the first regime only for IWP. The intrinsic kinetics was successfully used in a theoretical model to properly predict the gasification rate of pelletized biomass, and, eventually, to determine an apparent gasification kinetics as simple as possible in order to be easily implemented in future gasifier modeling works. Full article

Since the early development of Fluorescence Correlation Spectroscopy (FCS), it has been recognized that background intensity can lead to artifacts in the amplitude of the autocorrelation function (ACF) and, consequently, to inaccurate estimates of particle numbers. Here, we present a protocol for quantitative background evaluation and amplitude correction in FCS experiments, applicable to different sources of background such as detector noise, autofluorescence, and light scattering. We demonstrate the performance of our approach through three representative case studies: (i) FCS measurements of a bright fluorophore at low concentration, (ii) FCS of dim nanoparticles affected by solvent Raman scattering, and (iii) FCS performed using a confocal setup equipped with a SPAD array, where background originates from detector hot pixels. These examples represent typical experimental conditions in which background signals compromise quantitative interpretation, illustrating how our protocol restores accuracy and reproducibility in FCS analysis. By systematically identifying and correcting these effects, the proposed protocol addresses a long-standing limitation of FCS and provides a robust framework for improving the accuracy and reproducibility of quantitative fluorescence measurements. Full article

Palladium, a non-toxic platinum-group metal, is widely used in catalysis, electronics, hydrogen storage, and chemical industries because of its excellent physical and chemical properties. However, given that the number of palladium-producing countries is limited, recycling is considered essential for ensuring a stable and sustainable global supply. Here, I describe a simple and efficient method for palladium recovery from electronic waste (e-waste) using Enterobacter oligotrophicus CCA6^T. To clarify biomineralization capacity, the role of electron donors in modulating biomineralization capacity was examined. Findings showed that formic acid was the most effective donor, enhancing the relative recovery rate to 44% compared to 23% without electron donors. Transmission electron microscopy analysis revealed palladium particles (1–10 nm) distributed across the cell wall, periplasmic space and cytoplasm, confirming active biomineralization rather than passive biosorption. Moreover, based on a comparison with the biomineralization mechanism of Escherichia coli, the biomineralization mechanism of E. oligotrophicus CCA6^T was estimated . Reaction parameters were then optimized by testing the effects of formic acid concentration, reaction temperature, and reaction pH. Under optimized conditions, the relative recovery rate exceeded 99% within 6 h using 40 mg/L palladium. When this method was applied to a metal dissolution solution prepared from e-waste , a recovery rate of 94% was achieved from trace concentrations (36 µg/L), and palladium loss from bacteria after the palladium recovery test was negligible (<0.01%). Taken together, these results demonstrate that biomineralization using E. oligotrophicus CCA6^T could potentially be applied to the recovery of palladium from e-waste, particularly for trace-level concentrations where conventional methods are ineffective. Full article

The use of focal plane array micro-Fourier transform infrared spectroscopy (FPA-μFTIR) enables high-resolution characterization of microplastics (MPs) in a wide variety of matrices, including both biotic and abiotic samples. However, this technique has not yet been applied to study MP ingestion in organisms in areas with low MP pollution (e.g., national parks or protected areas). In this study, FPA-μFTIR was used to quantify MPs in the bodies of aquatic insects collected from a high-altitude stream (~2000 m) in Taiwan. Results showed that MP ingestion occurred in nearly all examined taxa, except for caddisfly (Trichoptera: Stenopsychidae) and dragonfly (Odonata: Gomphidae). The majority of MPs were smaller than 500 μm, and the dominant MP polymers identified were polyethylene (65%) and polypropylene (30%), which occurred mainly as fragments (83%) and, to a lesser extent, as fibers (17%). The highest number of MP particles was in the scraper functional-feeding group (FFG), while MPs were not detectable in collector–filterer FFG. The highest MP concentration (particles/individuals) was found in the waterpenny beetle Ectopria sp., followed by the mayflies Paraleptophlebia sp. and Epeorus erratus, and Chironomidae in the subfamily Tanypodinae. We suggest that using high-resolution FPA-μFTIR can be effectively applied to study and monitor MP ingestion in remote, pristine ecosystems. Full article

Airborne magnetic particles (AMPs) are associated with potentially toxic elements, and their size, mineralogy, and concentration can significantly impact both the environment and human health. However, their spatial analysis is often limited by small datasets, non-normality, and pronounced local variability. In this work, two sites with distinct demographic and geographic characteristics, the city of Mar del Plata (Argentina) and the Aburrá Valley region (Colombia), were analyzed using the fuzzy Magnetic Pollution Index (IMC) as an indicator of the concentration of AMPs. Moreover, an original methodological framework that explicitly incorporates measurement uncertainty through fuzzy numbers, combined with an approach modeling fuzzy semivariances via α-cuts, performs spatial prediction via ordinary kriging. This study produces maps that simultaneously reflect the magnitude of IMC and its associated uncertainty. Unlike classical geostatistics, the fuzzy-based model captures the inherent imprecision of magnetic measurements and reveals spatial patterns where uncertainty becomes informative about the type and origin of pollution. In particular, this approach demonstrates that areas with higher IMC levels are associated with high anthropic activity (near industrial zones, main avenues, slow traffic). In contrast, lower values were found in residential areas. Overall, the fuzzy-driven approach provides an additional layer of information not accessible through traditional methods, improving spatial interpretation and supporting the identification of priority areas for environmental monitoring. Full article

Extracellular vesicles (EVs) secreted by Fusarium oxysporum play an important role in the process of its infestation of the host, but the in vitro research system for EVs of F. oxysporum (Fo-EVs) has not yet been improved, and the mechanism of its action remains unclear. In this study, particle size distribution, particle concentration, number of particles per unit of protein, number of particles per unit of mycelial biomass, and concentration of contaminated proteins were used as indicators to evaluate the yield and purity of Fo-EVs. The optimal method for Fo-EV preparation and extraction was screened by comparing liquid culture, solid culture, and solid culture with enzymatic cell wall hydrolysis. The optimal system for Fo-EVs separation and purification was screened by a pairwise combination of three primary methods (Ultracentrifugation (UC), Ultrafiltration (UF), and Polyethylene glycol precipitation method (PEG)) and two secondary methods (Size-exclusion chromatography (SEC) and Aqueous two-phase system (ATPS)), respectively. The protein composition was identified via mass spectrometry technology, followed by GO annotation and GO enrichment analysis using whole-genome proteins as the background. Based on these steps, a Fo-EV protein library was constructed to reveal Fo-EV’s most active biological functions. The results showed that solid culture combined with the UC-SEC method could effectively enrich Fo-EVs with a typical cup-shaped membrane structure. The obtained Fo-EVs had an average particle size of 253.50 nm, a main peak value of 200.60 nm, a particle concentration of 2.04 × 10¹⁰ particles/mL, and a particle number per unit protein of 1.09 × 10⁸ particles/μg, which were significantly superior to those of other combined methods. Through proteomic analysis, 1931 proteins enriched in Fo-EVs were identified, among which 350 contained signal peptides and 375 had transmembrane domains. GO enrichment analysis revealed that these proteins were mainly involved in cell wall synthesis, vesicle transport, and pathogenicity-related metabolic pathways. Additionally, 9 potential fungal EV markers, including Hsp70, Rho GTPase family, and SNARE proteins, were screened. This study constructed an isolation system and a marker database for Fo-EVs, providing a methodological and theoretical basis for in-depth analysis of the biological functions of Fo-EVs. Full article

This study designed a novel coherent tuyere device capable of adjusting the core length of the jet flow. Physical experiments were first conducted to investigate how the number of secondary nozzles in the coherent tuyere affects the gas–solid two-phase flow behavior within the raceway during the blasting process. Subsequently, the Computational Fluid Dynamics (CFD) method was employed to examine the influence of structural parameters on jet morphology in coherent tuyere. Finally, computational fluid dynamics and discrete phase method (CFD-DPM) was adopted, and the velocity, temperature, and composition distribution patterns within the raceway were analyzed following the injection of hydrogen-rich gas through the coherent tuyere. The results of the physics experiment indicate that increasing the number of secondary nozzles in the coherent tuyere can significantly enlarge the raceway size and broaden the particle kinematic zone, thereby enhancing particle fluidization at the periphery of the raceway. CFD numerical simulation results indicate that increasing the number of secondary nozzles of the tuyere can effectively extend the length of the velocity jet core region. Compared with conventional tuyeres, a six-nozzle coherent tuyere can increase the core length of the blast velocity by about 40%. When the diameter of the secondary nozzles in the coherent tuyere is doubled, the core length of the blast velocity increases by 10%. The results of the CFD-DPM coupled simulation show that unburned carbon particles flow and combust along the periphery of the raceway with the hot air, leading to the formation of a high-temperature region in this area. After the injection of hydrogen-rich gas through the coherent tuyere, the temperature in the raceway decreased significantly. A high-concentration region of H₂ appeared at the periphery of the raceway, while the high-concentration CO region increased in concentration and gradually extended toward the upper part of the raceway. This research achievement is of significant importance for optimizing blast furnace blast kinetic energy and hydrogen-rich gas injection. Full article

This study investigates the interaction of humic acid (HA) with magnetite nanoparticles and its impact on the adsorption behavior of the HA-coated magnetite (Fe₃O₄) nanoparticles towards uranium (U-232) in aqueous solutions. The particle surface modification was performed using HA solutions of varying concentrations (0.01, 0.1, and 1.0 g/L). Zeta potential measurements revealed a significant shift in surface charge—from positive values (+13 mV) for unmodified particles to negative values (down to −30 mV) due to the presence of carboxylic moieties on the particle surface. Batch adsorption experiments at pH 5.6 demonstrated that increasing HA coating markedly improves the U-232 adsorption, with K_d values rising by up to an order of magnitude compared to unmodified Fe₃O₄ nanoparticles. The enhanced performance is linked to both the greater number of surface-active sites and the increased negative surface charge introduced by the HA layer. Despite the HA coating, the hydrodynamic diameter of the particles remains largely unaffected, preserving colloidal stability. The latter is also corroborated by SEM-EDX analysis. Overall, this work highlights the role of HA in the adsorption behavior of magnetite particles towards (radio)toxic metal ions, which is of particular interest regarding their mobility in the geosphere and their removal from contaminated waters. Full article

Suspended sediment transport in large rivers is characterized by complex cross-sectional patterns. This study investigates the cross-sectional distribution of the suspended sediment concentration (SSC), based on 15 measurement campaigns at six stations along a 67 km reach of the middle Rhine in Germany. Utilizing a multi-method approach, we conducted turbidity and acoustic backscatter measurements, in situ particle size data, recorded water quality parameters such as electrical conductivity, and took 495 pump-based water samples over a period of 2.5 years. Statistical analysis of this comprehensive dataset shows that lateral differences have greater importance for the cross-sectional SSC distribution than vertical differences, suggesting that incomplete river mixing is of greater importance than vertical stratification for uncertainties in load calculations. We demonstrate that surface measurements are consistently representative for the whole water column and that applying the traditional Rouse equation for vertical extrapolation from surface measurements leads to large errors. We conclude that efficient monitoring programs should prioritize covering the lateral SSC distribution for more accurate load calculations and offer practical recommendations for improved SSC monitoring in similar conditions. Full article

Constituent phases and their corresponding phase transformations are important in developing alloys. This study investigates the phase transformations of a Cr₃₉Co₁₈Fe₁₈Ni₁₈Al₇ HEA after annealing at and quenching from 1100 °C, 1200 °C and 1300 °C. The as-quenched alloy exhibits major body-centered cubic (BCC) and minor face-centered cubic (FCC) structures. The volume fraction of the BCC phase progressively increases as the annealing temperature is elevated. Upon cooling, the occurrence of spinodal decomposition in the high-temperature BCC phase leads to the formation of two distinct disordered BCC phases, BCC1 and BCC2, at a high temperature regime. The BCC1 phase acts as the matrix and is lean in Ni and Al concentrations, while the BCC2 phase presents as fine particles and is enriched in Ni and Al. As the temperature decreases, sequential spinodal decompositions occur in both BCC phases, giving rise to other product BCC phases. Upon further cooling, the Ni–Al-enriched BCC phases undergo ordering reactions, transforming into B2 phases. Consequently, the major phases in the matrix and fine particles are BCC and B2, respectively. In addition, the BCC matrix and B2 fine particles also contain B2 and BCC nanoparticles, respectively. The co-clustering and ordering effects of Ni and Al participate in the phase transformations of the as-quenched HEA. Correspondingly, the hardness increases with annealing temperature, which is attributed to the higher BCC phase fraction and the increasing number density of ordered B2 precipitates that collectively strengthen the matrix by impeding dislocation motion. Full article

High-resolution air quality data are critical for exposure assessment, regulatory compliance, and urban planning. In this study, we present modelled annual mean concentrations of NO₂, PM_2.5, PM₁₀, Black Carbon (BC), and particle number concentration (PNC) for all ~2.5 million Danish addresses in 2019 using the Air Quality at Your Street 2.0 system. The modelling framework combines coupled chemistry–transport models (DEHM/UBM/OSPM) with input from the Green Mobility Model and GPS-based vehicle speed data. Model outputs were evaluated against observations from the Danish Air Quality Monitoring Programme, showing strong agreement for NO₂, PM_2.5, PM₁₀, and BC, but notable overestimation of PNC background levels and underestimation of street contributions. Indicative exceedances of NO₂ EU limit values decreased markedly from 2012 to 2019, while exceedances of updated EU and WHO guidelines persist, especially for particulate matter. This work identifies key sources of model uncertainty and supports high-resolution national-scale assessment and citizen access via an interactive map. Full article

This study investigates the relationship between exhaust gas composition, particle number (PN) emissions, and soot microstructure of a 1.9 L compression-ignition engine operated under six controlled steady-state load regimes at 2000 min⁻¹. Unlike standardized transient procedures (e.g., WLTP), the steady-state approach enables isolation and quantification of fundamental thermochemical processes governing soot formation and NO_x production, providing engine-out data highly relevant for understanding Euro 7 emission behavior at the source. The novel contributions of this study include (i) a combined macroscopic–microscopic analysis linking PN emissions with SEM/EDS-based soot morphology; (ii) distribution-based estimation of soot mass concentration using experimentally derived primary particle sizes; and (iii) an experimental demonstration of the NO_x–soot trade-off across increasing load, supported by microstructural evidence of soot oxidation and agglomeration. The results show a clear decrease in PN concentrations with increasing load (from 1.31 × 10⁷ to 6.4 × 10⁶ cm⁻³), accompanied by a marked rise in NO_x emissions and exhaust temperature. SEM analysis confirms a transition from fine, weakly agglomerated soot structures at low load to more compact, oxidized aggregates at high load. Distribution-based particle sizing (20–80 nm, average ~45 nm) yields soot mass estimates that are consistent with theoretical trends and more accurate than fixed-radius approaches. These findings provide experimentally supported insights into engine-out particulate behavior that complements regulatory PN metrics in Euro 7, offering a mechanistic basis for improved emission control strategies and for interpreting PN-focused regulatory thresholds under real-world operating conditions. Full article

Wet stirred media milling (WSMM) is a popular grinding method used to produce important ultrafine-particle materials, such as pigments, pharmaceuticals, and pesticides. Therefore, it is crucial to improve the process capability and quality of WSMM by setting optimal parameters. This study proposes a multi-objective optimization methodology based on an intelligent algorithm to optimize the ultra-fine grinding parameters; this can mitigate the issue whereby grinding parameters are difficult to determine during wet grinding industrial production. A mechanistic model is proposed based on the analysis of energy dissipation mechanisms. The specific energy in the WSMM process is quantified using a stressing model. A shuffled frog leaping algorithm (SFLA)-based stressing model is proposed to maximize the specific stress intensity and specific stress number of the entire system under the constraint of the product particle size and grinding time, which provides the optimal process parameters. The performance of the proposed strategy is validated using two case studies in different industrial optimization scenarios. The result of the first case study illustrates that, in comparison to a quadratic programming-based response surface methodology, the proposed SFLA-based stressing model greatly enhances the wet grinding efficiency (decreasing P₈₀ from 3.28 μm to 2.88 μm). In the second case study, the parameter optimization under different feed particle sizes and different productivities was discussed. The results confirmed that the optimized parameters can achieve the minimum particle size (P₅₀ = 1.78 μm) and maximum solid concentration (C_v = 120 g/L) within the minimum grinding time (t_g = 5 min). The contribution of our work lies in the fact that the proposed SFLA-based stressing model can direct multiple-objective decision-making in a more efficient way without requiring costly experimental procedures to acquire the optimized parameters in WSMM. The proposed approach is systematic and robust and can be integrated into WSMM architectures for parameter optimization in other complex wet grinding systems. Full article

Microplastics (MPs), defined as plastic particles < 5 mm diameter, have become a growing public health concern. First identified in the aquatic environment in 2004 and later in air samples in 2015, airborne MPs display wide variations in shape and size, with fibres being the most common. These physical characteristics, together with others such as median aerodynamic diameter, influence how deeply they penetrate and where they deposit within the respiratory tract. Recent studies have confirmed the presence of MPs in nasal lavage fluid, bronchoalveolar lavage fluid, sputum, pleural fluid and lung tissue samples, with higher concentrations observed in older individuals, smokers and those with occupational exposure. Multiple polymer types have been identified, most frequently polypropylene, polyethylene and polyester. Experimental models demonstrate that MPs can induce inflammation, oxidative stress, mitochondrial dysfunction, microbiota alterations, fibrosis and carcinogenic changes, with toxicity generally increasing as particle size decreases. Despite the growing evidence of plastic toxicity, only a limited number of studies have examined MPs’ influence on the respiratory system, focusing mostly on polyester spheres, rather than fibres, which dominate real-world exposure. Current findings suggest MPs contribute to several pathophysiological processes and may play a role in respiratory disease. However, further research is needed to clarify the underlying mechanisms, long-term consequences and clinical relevance of these emerging pollutants. Full article

Exposure of propulsion gas turbines to inlet flow contaminated with dust, sand, or ash particulates can lead to a myriad of complex and interrelated damage modes that reduce engine operational life, increase maintenance costs, and pose a safety risk to passengers and hardware assets. Experimental and computational research is ongoing to better understand the fundamental physics underlying this phenomenon, but data from full-scale engine tests with particles are needed for anchoring and validation under fully representative conditions. In this study, compressor blade/particle interactions are investigated at field-relevant conditions using Rolls-Royce/Allison M250-C20C turboshaft engines in an instrumented engine test cell. A novel experimental dataset was produced, yielding a qualitative visualization of particle impact regions on blades and vanes of an on-engine full six-stage axial compressor at transonic tip speeds for two particle compositions and two inlet particle delivery configurations. This investigation contributes the first experimental dataset of its kind for a rotating frame at transonic blade tip speeds (nominal Mach 1.0). By comparing the resulting impact patterns produced in this work to those of fielded hardware, it is shown that for field-relevant high-Stokes number particle conditions at the first-stage rotor, particle/engine dynamics simplify significantly due to ballistic inertial particle behavior. In addition, the spatial distribution of particle concentration and particle velocities across the compressor inlet plane was found to have only minor effects on the resulting particle/blade impact patterns for the two dust injection configurations tested. Full article