Search Results (314)

Aluminum matrix composites provide an ideal solution for lightweight brake disks, but conventional casting processes are prone to crack initiation due to inhomogeneous reinforcement dispersion, gas porosity, and inadequate toughness. To break the conventional trade-off between high wear resistance and low toughness of brake disks, this study fabricated a bimetallic structure of SiC_p/Al–Fe–V–Si aluminum matrix composite and cast ZL101 alloy using friction stir lap welding (FSLW). Then, the microstructural evolution, mechanical properties, and tribological behavior of the FSLW joints were studied by XRD, SEM, TEM, tensile testing, and tribological tests. The results showed that the FSLW process homogenized the distribution of SiC particle reinforcements in the SiC_p/Al–Fe–V–Si composites. The Al₁₂(Fe,V)₃Si heat-resistant phase was not decomposed or coarsened, and the mechanical properties were maintained. The FSLW process refined the grains of the ZL101 aluminum alloy through recrystallization and fragmented eutectic silicon, improving elongation to 22%. A metallurgical bond formed at the joint interface. Tensile fracture occurred within the ZL101 matrix, demonstrating that the interfacial bond strength exceeded the alloy’s load-bearing capacity. In addition, the composites exhibited significantly enhanced wear resistance after FSLW, with their wear rate reduced by approximately 40% compared to the as-received materials, which was attributed to the homogenized SiC particle distribution and the activation of an oxidative wear mechanism. Full article

Predicting the blow-off (BO) is critical for characterising the operability limits of gas turbine engines. In this study, the applicability of a low-order extinction prediction modelling, which is based on a stochastic variant of the Imperfectly Stirred Reactor (ISR) approach, to predict the lean blow-off (LBO) curve and the extinction conditions in a hydrogen Rich-Quench-Lean (RQL)-like swirl combustor is investigated. The model predicts the blow-off scalar dissipation rate (SDR), which is then extrapolated using Reynolds-Averaged Navier–Stokes (RANS) cold-flow simulations and simple scaling laws, to determine the critical blow-off conditions. It has been found that the sISR modelling framework can predict the BO flow split ratio at different global equivalence ratios, showing a reasonable agreement with the experimental data. This further validates sISR as an efficient low-order modelling flame extinction tool, which can significantly contribute to the development of robust hydrogen RQL combustors by enabling the rapid exploration of combustor operability during the preliminary design phases. Full article

Nickel is used in aerospace, military, energy, and chemical sectors. Commercially pure (CP) Ni, and its alloys, including solid-solution strengthened (SSS), precipitation strengthened (PS), and specialty alloys (SA), are widely utilized, typically at elevated temperatures, in corrosive settings and in cryogenic milieu. Ni or Ni-based alloys frequently require welding realized, inter alia, via methods using electric arc and beam power. Tungsten inert gas (TIG) and Electron-beam welding (EBW) have been utilized most often. Friction stir welding (FSW) is the most promising solid-state welding technique for connecting Ni and its alloys. The primary weldability issues related to Ni and its alloys are porosity, as well as hot and warm cracking. CP Ni exhibits superior weldability. It is vulnerable to porosity and cracking during the solidification of the weld metal. Typically, SSS alloys demonstrate superior weldability when compared to PS Ni alloys; however, both types may experience weld metal solidification cracking, liquation cracking in the partially melted and heat-affected zones, as well as ductility-dip cracking (DDC). Furthermore, PS alloys are prone to strain-age cracking (SAC). The weldability of specialty Ni alloys is limited, and brazing might provide a solution. Employing appropriate filler metal, welding settings, and minimal restraint can reduce or avert cracking. Full article

Micro-nano bubbles (MNBs) are tiny bubbles with diameters ranging from 200 nm to 30 µm. They possess unique physicochemical properties such as a large specific surface area, slow rising velocity, high gas dissolution rate, high mass transfer efficiency, and strong interfacial zeta potential. These properties endow MNBs with great potential in various fields, including water treatment, enhanced oil recovery, medical and health care, and agriculture. This paper systematically reviews the physicochemical properties, generation methods, and applications of micro-nano bubbles. The main production methods include the mechanical stirring, pressurized dissolved gas release, ultrasonic cavitation, venturi injection, electrolysis, etc. The principles, advantages and disadvantages, and optimization strategies of these methods are comprehensively analyzed. In terms of applications, the mechanisms and typical cases of MNBs in enhanced oil recovery, water treatment, mineral flotation, medical drug delivery, and crop yield enhancement are thoroughly discussed. Extensive research has shown that MNB technology is highly efficient, energy-saving, and environmentally friendly. However, improving bubble stability, generation efficiency, and large-scale application remain key directions for future research. Full article

Superparamagnetic magnetite nanoparticles (Fe₃O₄) have garnered considerable interest due to their unique magnetic properties and potential for integration into multifunctional biomaterials. In particular, their incorporation into bacterial cellulose (BC) matrices offers a promising route for developing sustainable and high-performance magnetic composites. Numerous studies have explored BC-magnetite systems; however, innovations combining ex situ coprecipitation synthesis within BC matrices, tailored reagent molar ratios, stirring protocols, and purification processes remain limited. This study aimed to optimize the ex situ coprecipitation method for synthesizing superparamagnetic magnetite nanoparticles embedded in BC membranes, focusing on enhancing particle stability and crystallinity. BC membranes containing varying concentrations of magnetite (40%, 50%, 60%, and 70%) were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and vibrating sample magnetometry (VSM). The resulting magnetic BC membranes demonstrated homogenous dispersion of nanoparticles, improved crystallite size (6.96 nm), and enhanced magnetic saturation (Ms) (50.4 emu/g), compared to previously reported methods. The adoption and synergistic optimization of synthesis parameters—unique to this study—conferred greater control over the physicochemical and magnetic properties of the composites. These findings position the optimized BC-magnetite nanocomposites as highly promising candidates for advanced applications, including electromagnetic interference (EMI) shielding, electronic devices, gas sensors, MRI contrast agents, and targeted drug delivery systems. Full article

Sparkling wine is a complex alcoholic beverage with high economic value, produced through a secondary fermentation of a still wine, followed by a prolonged aging period that may last from nine months to several years. With the growing global demand for high-quality sparkling wines, understanding the biochemical mechanisms related to aroma development has become increasingly relevant. This review provides a comprehensive overview of the secondary fermentation process, with particular emphasis on yeast selection, types of closure, and the impact of aging on the volatile composition. Special attention is also given to the analytical strategies employed for the identification and quantification of target compounds in sparkling wine matrices. Due to the presence of volatile compounds at trace levels, effective extraction and pre-concentration techniques are essential. Extraction methods such as solid-phase microextraction (SPME), stir-bar sorptive extraction (SBSE), and thin-film SPME (TF-SPME) are discussed, as well as chromatographic techniques, such as gas chromatography (GC) and liquid chromatography (LC). Full article

In this study, weekly grab samples extracted by solid-phase extraction (SPE) and stir bar sorptive extraction (SBSE) were compared for the analysis of 230 pesticides in surface waters. Samples were collected from three different locations around Melbourne, Australia. Analysis was performed using Gas Chromatography Quadrupole Time of Flight High Resolution Mass Spectrometry (GC-QToF-HRMS). The two extraction techniques were compared, among others, for their limits of detection, recovery, extraction, and quantification efficiency of pesticides, as well as spatial and temporal differences in detected compounds. The target compounds screened were pesticides belonging mainly to the categories of fungicides, insecticides, and herbicides. Although SBSE extracted more pesticides at two out of three sites, SPE extracted total concentrations up to four times higher than SBSE over all sampling sites. The log K_OW of detected pesticides only partially explained the differences in detection, with SBSE performing better in the absorption of hydrophobic compounds. In addition, matrix effects, in particular turbidity, appeared to hinder extraction of contaminants, especially for SBSE. Spatially, SBSE detected 10 pesticides more than SPE at two locations, while the opposite was true at the third location, where turbidity was higher. The types of pesticides detected varied slightly between techniques and locations. The study highlights the complementarity of SBSE and SPE for monitoring pesticides in natural environments. SBSE is an easy-to-use technique and allows for extraction of a higher number of pesticides at trace level, but it might not be the preferred option for highly turbid waters. SPE requires more tedious and complex sample processing but allows for a more accurate quantification of a broader range of pesticides. Full article

Mixing time, as a key parameter for evaluating ladle refining efficiency, has long attracted extensive attention from researchers. In typical experimental studies, salt solution tracers are introduced into ladle water models to assess the degree of mixing within the ladle. Previous studies have demonstrated that the volume of tracer can significantly influence the measured mixing time. However, the gas flow rates employed in these studies are generally relatively high, whereas, in industrial operations, especially during final composition adjustments, lower gas flow rates are often applied. To systematically investigate the effect of the salt solution tracer volume on the mixing efficiency in a ladle water model under asymmetrical gas stirring with a low gas flow rate, a 1:3-scaled water model was developed based on a 130-ton industrial ladle. The mixing behaviors corresponding to different tracer volumes were comprehensively analyzed. The results indicate that the relationship between tracer volume and mixing time is non-monotonic. As the tracer volume increases, the mixing time first decreases and then increases, reaching a minimum at 185 mL. When the tracer volume was small, the dimensionless concentration curves at Monitoring Point 4 exhibited two distinct patterns: A parabolic profile, which was when the tracer initially moved through the left and central regions and then slowly crossed the gas plume to reach the monitoring point. A sinusoidal profile, which was when the tracer predominantly circulated along the right side of the ladle. When the tracer volume exceeded 277 mL, the concentration curves at Monitoring Point 4 consistently exhibited a sinusoidal pattern. Compared with moderate gas flow conditions (8.3 L/min), the peak concentration at Monitoring Point 3 was significantly lower under a low gas flow (2.3 L/min), and the overall mixing time was longer, indicating reduced mixing efficiency. Based on the findings, a recommended tracer volume range of 185–277 mL is proposed for low gas flow conditions (2.3 L/min) to achieve accurate and efficient mixing time measurements with minimal disturbance to the flow field. It was also observed that when the tracer concentration was relatively low, the mixing behavior throughout the ladle became more uniform. Full article

In this study, through RH water model simulation experiments, the effects of precipitation bubbles on the two-phase flow pattern, liquid steel flow behavior, and flow characteristics in an RH reactor during the whole decarburization process were comparatively investigated and analyzed by using quasi-counts that reflected the similarity of the precipitation bubble phenomenon. The experimental results show that an increase in precipitation bubbles is positively related to an increase in circulating flow rate, a reduction in mixing time, and an increase in gas content and negatively related to the residence time of liquid steel in the vacuum chamber. The two-phase flow pattern of the rising tube under the influence of precipitation bubbles includes bubble flow, slug flow, mixing flow, and churn flow. Under the influence of precipitation bubbles, the liquid surface spattering inside the vacuum chamber is reduced, the fluctuation amplitude is reduced, the efficiency of liquid steel processing is improved, it is not easy for cold steel to form, and the fluctuation frequency is increased, which is conducive to increasing the surface area of the vacuum chamber; the bubbles’ rising, aggregating, and crushing behavior increases the stirring effect inside the vacuum chamber, which is conducive to improving the decarburization and mass transfer rate. Under the influence of the precipitated bubbles, the concentration gradient between the ladle and the vacuum chamber is increased, which accelerates the mixing speed of the liquid steel in the ladle, and the volume of the dead zone is reduced by 50%. The lifting gas flow rate can be appropriately reduced in the plant. Full article

Background: There is a continuous demand to create new, superior sensory food experiences. In the food industry, yeast-derived flavor products (YPs) are often used as ingredients in foods to create new aromas and taste qualities that are appreciated by consumers. Methods: Chicken bouillon samples containing diverse YPs were chemically and sensorially characterized using statistical multivariate analyses. The sensory evaluation was performed using quantitative descriptive analysis (QDA) by trained panelists. Thirty-four sensory attributes were scored, including odor, flavor, mouthfeel, aftertaste and afterfeel. Untargeted metabolomic profiles were obtained using stir bar sorptive extraction (SBSE) coupled to GC-MS, RPLC-MS and targeted HILIC-MS. Results: In total, 261 volatiles were detected using GC-MS, from chemical groups of predominantly aldehydes, esters, pyrazines and ketones. Random Forest (RF) modeling revealed volatiles associated with roast odor (2-ethyl-5-methyl pyrazine, 2,3,5-trimethyl-6-isopentyl pyrazine) and chicken odor (2,4-nonadienal, 2,4-decadienal, 2-acetyl furan), which could be predicted by our combined model with R² > 0.5. In total, 2305 non-volatiles were detected for RPLC-MS and 34 for targeted HILIC-MS, where fructose-isoleucine and cyclo-leucine-proline were found to correlate with roast flavor and odor. Furthermore, a list of metabolites (glutamate, monophosphates, methionyl-leucine) was linked to umami-related flavor. This study describes a straightforward data-driven approach for studying foods with added YPs to identify flavor-impacting correlations between molecular composition and sensory perception. It also highlights limitations and preconditions for good prediction models. Overall, this study emphasizes a matrix-based approach for the prediction of food taste, which can be used to analyze foods for targeted flavor design or quality control. Full article

The present study investigates a two-stage process aimed at producing biogas from food waste leachates (FWL) through an experimental approach. The first stage involves biohydrogen production via dark fermentation (DF), while the second focuses on biomethane production through anaerobic digestion (AD). The substrate consists of leachates derived from fruit and vegetable waste, which are introduced into two continuous stirred-tank reactors (CSTR1) with two different inoculum-to-substrate ratios (ISR). Dark fermentation occurs in these reactors. The effluent from the CSTRs is then fed into two additional reactors for methanogenesis. All reactors operated under mesophilic conditions. During the DF stage, hydrogen yields were relatively low, with a maximum of 8.2 NmL H₂/g VS added (ISR = 0.3) and 6.1 NmL H₂/g VS added (ISR = 0.5). These results were attributed to limited biodegradation of volatile solids (VS), which reached only 21.9% and 23.6% in each respective assay. Similarly, the removal of organic matter was modest. In contrast, the AD stage demonstrated more robust methane production, achieving yields of 275.2 NmL CH₄/g VS added (ISR = 0.3) and 277.5 NmL CH₄/g VS added (ISR = 0.5). The system exhibited significant organic matter degradation, with VS biodegradability reaching 66%, and COD removal efficiencies of 50.8% (ISR = 0.3) and 60.1% (ISR = 0.5). The primary focus of the study was to monitor and quantify the production of the two biofuels, biohydrogen and biomethane. In conclusion, this study provides an assessment of the two biochemical conversion pathways, detailing the generation of two valuable and utilizable gaseous products. This research examines the process-specific operational conditions governing gas production, with a focus on optimizing process parameters to enhance yield and overall efficiency. Full article

To address the issues of low solid–liquid mixing and mass transfer efficiency and difficult real-time regulation in the resource utilization of non-ferrous metal smelting slag, this study constructs a research framework integrating Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) coupling models and machine learning. The framework systematically investigates particle motion characteristics and mass transfer laws in stirred tanks and enables an intelligent prediction of key parameters. Through a CFD-DEM two-way coupling simulation, the study quantifies particle dispersion characteristics using relative standard deviation (RSD) and calculates the mass transfer coefficient (k) based on the Hughmark model, revealing the effects of particle size and impeller speed on mixing and mass transfer efficiency. For parameter prediction, particle motion and mass transfer data are used to train a multi-model prediction library, with model performance evaluated through comparative experiments. The results show that increasing the rotational speed shortens the particle mixing time, reduces RSD values by 25–40%, increases the coupling force, and decreases stability during the circulation phase. Different machine learning (ML) algorithms exhibit varying performances in the time-series prediction of particle motion characteristics and real-time prediction of mass transfer coefficients. Notably, GA-BP achieves a fitting degree R of 0.99 in both predictions, meeting the requirements for the structural optimization and intelligent regulation of stirred tanks. This research provides theoretical support and technical pathways for the structural optimization and intelligent control of stirred tanks, offering engineering application value in fields such as hydrometallurgy and solid waste resource utilization. Full article

Unlike on Fe and Co catalysts, the CO conversion effect on Ru catalyst performance is little reported. This study is undertaken to explore the issue using a series of Ru/NaY catalysts under 200–230 °C, 2.0 MPa, H₂/CO = 2, and 10–60% CO conversion in a 1 L continuous stirred tank reactor (CSTR). The results are comparatively studied with those of Fe and Co catalysts reported previously. The NaY support and four 1.0%, 2.5%, 5.0%, and 7.5% Ru/NaY catalysts were characterized by BET, H₂ chemisorption, H₂O-TPD, XRD, HRTEM, and XANES/EXAFS techniques. The BET and XRD results suggest a high surface area (730 m²/g), high degree of crystallinity of the NaY support, and high dispersion of Ru, while an hcp Ru structure and well-reduced Ru were reflected in the HR-TEM FFT and XANES/EXAFS results. The reaction results indicate that the CO conversion effect on CH₄ and C₅₊ selectivities on the Ru is the same as that on the Fe and Co catalysts, with CH₄ selectivity decreasing and C₅₊ selectivity increasing with increasing CO conversion. However, the CO conversion effect on olefin formation for the Ru catalyst was found to be opposite to that of the Fe and Co; increasing CO conversion enhanced olefin formation but suppressed secondary reactions of 1-olefins. The H₂O cofeeding experiments showed that H₂O impacted olefin formation by suppressing hydrogen adsorption and hydrogenation. The H₂O-TPD experiment evidenced a much stronger H₂O adsorption capacity (6.8 mmol/g-cat) on Ru followed by Co (1 mmol/g-cat), and then Fe (0.2 mmol/g-cat)., which showed only a very low H₂O adsorption capacity.This finding may explain the opposite CO conversion effect on olefin formation observed on the Ru catalyst, and may also explain why low CH₄ selectivity (i.e., 3%) occurred on the Ru catalyst and high CH₄ selectivity (i.e., 6–8%) occurred on the Co catalyst, both of which possess low water gas shift (WGS) activity. Full article

Considering the issues of significant ammonia volatilization loss and toxic gas emission associated with the conventional ammonia leaching method used in the resource utilization of cobalt-rich alloy slag, a novel approach involving selective complexation leaching of cobalt in an alkaline histidine solution has been proposed. Under conditions of 35 °C temperature, a molar ratio of histidine to cobalt of 1.5, pH of 8, a leaching period of 12 h, and a stirring speed of 300 rpm, the cobalt leaching rate from cobalt-rich alloy slag exceeds 95%. In contrast, the leaching rates for impurity metals such as iron, lead, and copper remain below 3%, demonstrating outstanding leaching selectivity. Leaching kinetics calculations indicate that the rate-controlling step is chemical reaction control, with an apparent activation energy of 64.32 kJ/mol. Through the use of FTIR and XPS characterization techniques, it has been confirmed that histidine molecules form a stable complex with cobalt ions via the dual coordination of the carboxyl (COO⁻) and amino (-NH₂) groups. This distinctive bifunctional synergistic coordination mechanism markedly enhances leaching selectivity and reaction efficiency. Full article

A Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry (SBSE-GC-MS) method has been optimized and validated for the determination of eight volatile sulphur compounds in wine distillates: diethyl sulphide (DES), dimethyl disulphide (DMDS), diethyl disulphide (DEDS), 2-thiophenecarboxaldehyde (TC), dibutyl sulphide (DBS), dipropyl disulphide (DPDS), dipropyl sulphide (DPS), and dimethyl trisulphide (DMTS). After optimization by 2⁴ factorial design, the SBSE-GC-MS extraction conditions were as follows: a polydimethylsiloxane twister (10 mm × 0.5 mm), 35 °C as the extraction temperature, 10 mL as the sample volume, 7% (v/v) as the alcoholic grade, 47 min as the extraction time, 10% (w/v) of NaCl, and 1% (w/v) of EDTA (ethylenediaminetetraacetic acid). Under optimal conditions, adequate analytical figures of merit were obtained for eight of the ten compounds initially considered, with low quantification and detection limits and relative standard deviations for inter-twister and inter-day repeatability values ranging from 7.5 to 21.8% and from 7.2 to 27.5%, respectively. The methodology was applied to 34 wine distillates (continuous column distillation and distillation in pot still) elaborated for the production of Brandy de Jerez: 15 aged distillates aged for different periods of time in American oak wood and 19 non-aged distillates. The most significant volatile sulphur compounds were DBS, DMDS, and DPS. The Cluster Analysis (CA) on the volatile sulphur compounds grouped the samples according to the use of sulphur dioxide. In general, lower amounts of volatile sulphur compounds were found in the aged samples, although the high standard deviations obtained highlight that their contents depend on multiple factors related to the elaboration process. Full article