Search Results (1,083)

The increasing demand for plant-based foods has led to significant growth in the availability, at a retail level, of plant-based cheese analogue products. This study presents the first comprehensive benchmarking of commercially available plant-based cheese analogue (PBCA) products in the Irish market, comparing them against conventional cheddar and processed dairy cheeses. A total of 16 cheese products were selected from Irish retail outlets, comprising five block-style plant-based analogues, seven slice-style analogues, two cheddar samples, and two processed cheese samples. Results showed that plant-based cheese analogues had significantly lower protein content (0.1–1.7 g/100 g) than cheddar (25 g/100 g) and processed cheese (12.9–18.2 g/100 g) and lacked a continuous protein matrix, being instead stabilized largely by solid fats, starch, and hydrocolloids. While cheddar showed the highest hardness, some plant-based cheeses achieved comparable hardness using texturizing agents but still demonstrated lower tan δ_max values, indicating inferior melting behaviour. Thermograms of differential scanning calorimetry presented a consistent single peak at ~20 °C across most vegan-based variants, unlike the dual-phase melting transitions observed in dairy cheeses. Sensory analysis further highlighted strong negative associations between PBCAs and consumer-relevant attributes such as flavour, texture, and overall acceptability. By integrating structural, functional, and sensory findings, this study identifies key formulation and performance deficits across cheese formats and provides direction for targeted improvements in next-generation PBCA product development. Full article

This study presents a breakthrough in sustainable injection molding by uniquely combining a backpropagation neural network (BPNN) with particle swarm optimization (PSO) to overcome traditional optimization challenges. The BPNN’s exceptional ability to learn complex nonlinear relationships between six key process parameters (including melt temperature and holding pressure) and product quality is amplified by PSO’s intelligent search capability, which efficiently navigates the high-dimensional parameter space. Together, this hybrid approach achieves what neither method could accomplish alone: the BPNN accurately models the intricate process-quality relationships, while PSO rapidly converges on optimal parameter sets that simultaneously meet strict quality targets (66–70 g weight, 3–5 mm thickness) and minimize energy consumption. The significance of this integration is demonstrated through three key outcomes: First, the BPNN-PSO combination reduced optimization time by 40% compared to traditional trial-and-error methods. Second, it achieved remarkable prediction accuracy (RMSE 0.8229 for thickness, 1.5123 for weight) that surpassed standalone BPNN implementations. Third, the method’s efficiency enabled SMEs to achieve CAE-level precision without expensive software, reducing setup costs by approximately 25%. Experimental validation confirmed that the optimized parameters decreased energy use by 28% and material waste by 35% while consistently producing parts within specifications. This research provides manufacturers with a practical, scalable solution that transforms injection molding from an experience-dependent craft to a data-driven science. The BPNN-PSO framework not only delivers superior technical results but does so in a way that is accessible to resource-constrained manufacturers, marking a significant step toward sustainable, intelligent production systems. For SMEs, this framework offers a practical pathway to achieve both economic and environmental sustainability, reducing reliance on resource-intensive CAE tools while cutting production costs by an estimated 22% through waste and energy savings. The study provides a replicable blueprint for implementing data-driven sustainability in injection molding operations without compromising product quality or operational efficiency. Full article

The stabilization of heavy metal elements, such as zinc, in the form of ions within the glass-ceramics represents a valuable approach to addressing environmental pollution caused by heavy metals. This study investigates the feasibility and physicochemical properties of diopside-based glass-ceramics synthesized from zinc-containing smelting slag. The zinc-rich smelting slag is abundant in SiO₂, Al₂O₃, CaO, and other constituents, thereby providing cost-effective and efficient raw materials for glass-ceramic production. The conversion of zinc-containing smelting slag into glass-ceramics was achieved through a melting process. We analyzed the effects of varying doping levels on the properties of the resulting glass-ceramics. The results indicated that as the doping level of smelting slag increases, the crystallization temperature of the glass-ceramics decreases while the crystal phases of diopside and anorthite progressively increase, significantly enhancing both mechanical strength and chemical stability. Notably, when the doping level reaches 60%, these glass-ceramics exhibit remarkable physical properties, including high density (3.12 g/cm³), Vickers hardness (16.60 GPa), and excellent flexural strength (150.75 MPa). Furthermore, with increasing amounts of doped smelting slag, there are substantial improvements in acid resistance, alkali resistance, and corrosion resistance in these materials. Raman spectroscopy and EDS analysis further verified a uniform distribution of the crystal phase and effective immobilization of heavy metal zinc. Full article

Change in sea level (SL) is an important indicator of global warming, since it reflects alterations in several components of the climate system at once. The main factors behind this phenomenon are the melting of glaciers and thermal expansion of ocean water, with the latter contributing about 40% to the overall rise in SL. Rising SL indirectly indicates an increase in ocean heat content and, consequently, its surface temperature. Previous studies have found that tropical sea surface temperature (SST) is critical to regulating the Earth’s climate and weather patterns in high and mid-latitudes. For this reason, SST and SL in the tropics can be considered as precursors of both global climate change and the emergence of climate anomalies in extratropical latitudes. Although SST has been used in this capacity in a number of studies, similar research regarding SL had not been conducted until recently. In this paper, we examine the links between SL in the tropical North Atlantic and North Pacific Oceans and surface air temperature (SAT) at mid- and high latitudes, with the aim of assessing the potential of SL as a predictor in forecasting SAT anomalies. To identify similarities between the variability of tropical SL and SST and that of SAT in high- and mid-latitude regions, as well as to estimate possible time lags, we applied factor analysis, clustering, cross-correlation and cross-spectral analyses. The results reveal a structural similarity in the internal variability of tropical SL and extratropical SAT, along with a significant lagged relationship between them, with a time lag of several years. Full article

Aiming at the problems of complex process flow, high energy consumption, and difficult emulsification in the preparation of traditional SBS-modified emulsified asphalt, a preparation method of fast-melting SBS (referred to as SBS-T) modified emulsified asphalt based on the integration of modification and emulsification is proposed. Based on surface free energy theory, the contact angles between three rapid-melting SBS-modified emulsified asphalts with different dosages and three probe liquids (deionized water, glycerol, and formamide) were measured using the sessile drop method. The adhesion performance of the asphalt–aggregate system was studied by means of micromechanical methods. The evaluation indicators such as the cohesion work of the emulsified asphalt, the adhesion work of asphalt–aggregate, the spalling work, and the energy ratio were analyzed. The results show that the SBS-T modifier can significantly improve the thermodynamic properties of emulsified asphalt. With increasing modifier content, the SBS-T-modified emulsified asphalt demonstrated enhanced cohesive work, improved asphalt–aggregate adhesive work, and increased energy ratio, while showing reduced stripping work. At equivalent dosage levels, the SBS-T-modified emulsified asphalt demonstrates a slight improvement in adhesion performance to aggregates compared to conventional SBS-modified emulsified asphalt. The SBS-T emulsified modified asphalt provides an effective technical solution for the preventive maintenance of asphalt pavements. Full article

A series of Er³⁺–Tm³⁺–Yb³⁺ tri-doped fluorophosphate glasses with different molar compositions were synthesized using the conventional melt-quenching technique, and their optical properties were measured and analyzed. Under laser excitation at 980 nm, blue, green and red upconverted emissions were observed at around 475, 545 and 660 nm, respectively. Based on the results and the energy level diagrams, energy transfer processes were proposed to explain the population mechanisms of the emitting levels. A final characterization was developed within the framework of the CIE 1931 chromaticity coordinate diagram. Varying the doping concentrations of the optically active rare-earth ions, as well as the laser pumping power, enabled modulation of the three primary colors, resulting in blue, green and relatively close to white light emissions. This tunability of the upconverted emissions highlights the potential of these fluorophosphate glasses as tunable optical devices, laser systems and visual show effects. Full article

TiVCr-based alloys are well-explored body-centered cubic (BCC) materials for hydrogen storage applications that can potentially store higher amounts of hydrogen at moderate temperatures. The challenge remains in optimizing the alloy-hydrogen stability, and several transition elements have been found to support the reduction in the hydride stability. In this study, Ni and Nb transition elements were incorporated into the TiVCr alloy system to thoroughly understand their influence on the (de)hydrogenation kinetics and thermodynamic properties. Three different compositions, (TiVCr)₉₅Ni₅, (TiVCr)₉₀ Ni₁₀, and (TiVCr)₉₅Ni₅Nb₅, were prepared via arc melting. The as-prepared samples showed the formation of a dual-phase BCC solid solution and secondary phase precipitates. The samples were characterized using hydrogen sorption studies. Among the studied compositions, (TiVCr)₉₀Ni₁₀ exhibited the highest hydrogen absorption capacity of 3 wt%, whereas both (TiVCr)₉₅Ni₅ and (TiVCr)₉₀Ni₅Nb₅ absorbed up to 2.5 wt% hydrogen. The kinetics of (de)hydrogenation were modeled using the JMAK and 3D Jander diffusion models. The kinetics results showed that the presence of Ni improved hydrogen adsorption at the interface level, whereas Nb substitution enhanced diffusion and hydrogen release at room temperature. Thus, the addition of Ni and Nb to Ti-V-Cr-based high-entropy alloys significantly improved the hydrogen absorption and desorption properties at room temperature for gas-phase hydrogen storage. Full article

The manufacture of lightweight components is one of the most important requirements in the automotive and aerospace industries. Gears, on the other hand, are among the heaviest parts in terms of their total weight. Accordingly, a spur gear was considered, the body of which was configured as a lattice structure to make it lightweight. In addition, the structure was optimized by topology optimization using ProTOP software. Subsequently, the gear was manufactured by a selective laser melting process by using a strong and lightweight material, namely Ti-6Al-4V. This study defeated the problems of manufacturing orientation, surface roughness, support structure, and bending due to the high thermal gradient in the selective laser melting process. To experimentally investigate the benefits of such a lightweight gear body structure, a new test rig with a closed loop was developed. This rig enabled measurements of strains in the gear ring, hub, and tooth root. The experimental results confirmed that a specifically designed and selectively laser-melted, lightweight cellular lattice structure in the gear body can significantly influence strain. This is especially significant with respect to strain levels and their time-dependent variations in the hub section of the gear body. Full article

This study investigates the linkage between the radar reflectivity slope and raindrop size distribution (DSD) in precipitation with bright bands through coordinated C-band/Ka-band radar and disdrometer observations in southern China. Precipitation is classified into three types based on the reflectivity slope (K-value) below the freezing level, revealing distinct microphysical regimes: Type 1 (K = 0 to −0.9) shows coalescence-dominated growth; Type 2 (|K| > 0.9) shows the balance between coalescence and evaporation/size sorting; and Type 3 (K = 0.9 to 0) demonstrates evaporation/size-sorting effects. Surface DSD analysis demonstrates distinct precipitation characteristics across classification types. Type 3 has the highest frequency of occurrence. A gradual decrease in the mean rain rates is observed from Type 1 to Type 3, with Type 3 exhibiting significantly lower rainfall intensities compared to Type 1. At equivalent rainfall rates, Type 2 exhibits unique microphysical signatures with larger mass-weighted mean diameters (D_m) compared to other types. These differences are due to Type 2 maintaining a high relative humidity above the freezing level (influencing initial D_m at bottom of melting layer) but experiencing limited D_m growth due to a dry warm rain layer and downdrafts. Type 1 shows opposite characteristics—a low initial D_m from the dry upper layers but maximum growth through the moist warm rain layer and updrafts. Type 3 features intermediate humidity throughout the column with updrafts and downdrafts coexisting in the warm rain layer, producing moderate growth. Full article

The pilot study is devoted to the assessment of both the accumulation and spatial distribution of microplastics in the snow cover of the Zhetysu region. The height of snow cover in the study area varied from 4.0 to 80.5 cm, with a volume of melt water ranging from 1.5 to 143 L. The analysis of 53 snow samples taken at different altitudes (from 350 to 1500 m above sea level) showed the presence of microplastics in 92.6% of samples in concentrations from 1 to 12 particles per square meter. In total, 170 microplastic particles were identified. The main polymers identified by Raman spectroscopy were polyethylene (PE), polypropylene (PP), and polystyrene (PS). These are typical components of plastic waste. The spatial distribution of microplastics showed elevated concentrations near settlements and roads. Notable contaminations were also recorded in remote mountainous areas, confirming the significant role of long-range atmospheric transport. Particles smaller than 0.5 mm dominated, having high aerodynamic mobility and capable of long-range atmospheric transport. Quantitative and qualitative characteristics of microplastics in snow cover have been realized for the first time both in Kazakhstan and in the Central Asian region, which contributes to the formation of primary ideas and future approaches about microplastic pollution in continental inland regions. The obtained results demonstrate the importance of atmospheric transport in the distribution of microplastics. They indicate the need for further monitoring and microplastic pollution analyses in Central Asia, taking into account its detection even in hard-to-reach and remote areas. Full article

The observations of atmospheric, oceanic, and sea ice data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition were used to analyze the influence of snow redistribution and melt-pond processes on the evolution of sea ice thickness (SIT) in 2019 and 2020. To mitigate the effect of missing atmospheric observations from the time of the expedition, we used ERA5 atmospheric reanalysis along the MOSAiC drift trajectory to force the single-column sea ice model Icepack. SIT simulations from six combinations of two melt-pond schemes and three snow-redistribution configurations of Icepack were compared with observations and analyzed to investigate the sources of model–observation discrepancies. The three snow-redistribution configurations are the bulk scheme, the snwITDrdg scheme, and one simulation conducted without snow redistribution. The bulk scheme describes snow loss from level ice to leads and open water, and snwITDrdg describes wind-driven snow redistribution and compaction. The two melt-pond schemes are the TOPO scheme and the LVL scheme, which differ in the distribution of melt water. The results show that Icepack without snow redistribution simulates excessive snow–ice formation, resulting in an SIT thicker than that observed in spring. Applying snow-redistribution schemes in Icepack reduces snow–ice formation while enhancing the congelation rate. The bulk snow-redistribution scheme improves the SIT simulation for winter and spring, while the bias is large in simulations using the snwITDrdg scheme. During the summer, Icepack underestimates the sea ice surface albedo, resulting in an underestimation of SIT at the end of simulation. The simulations using the TOPO scheme are characterized by a more realistic melt-pond evolution compared to those using the LVL scheme, resulting in a smaller bias in SIT simulation. Full article

Additive manufacturing techniques, such as laser-based powder bed fusion of metals (PBF-LB/M), have now gained high industrial and academic interest. Despite its design flexibility and the ability to fabricate intricate components, LPBF has not yet reached its full potential, partly due to the challenges associated with microstructure control. The precise manipulation of the microstructure in LPBF is a formidable yet highly rewarding endeavor, offering the capability to engineer components at a local level. This work introduces an innovative parallelized Cellular Automaton (CA) framework for modeling the evolution of the microstructure during the LPBF process. LPBF involves remelting and subsequent nucleation followed by crystal growth during solidification, which complicates and burdens microstructure simulations. In this research, a novel approach to nucleation seeding and crystal growth is implemented, focusing exclusively on the final stages of melting and solidification, enhancing the computational efficiency by 30%. This approach streamlines the simulation process, making it more efficient and effective. The developed model was employed to simulate the microstructure of an austenitic advanced high-strength steel (AHSS). The model was validated by comparing the simulation results qualitatively and quantitatively with the experimental data obtained under the same process parameters. The predicted microstructure closely aligned with the experimental findings. Simulations were also conducted at varying resolutions of CA cells, enabling a comprehensive study of their impact on microstructure evolution. Furthermore, the computational efficiency was critically evaluated. Full article

Laser-based powder bed fusion of metals (PBF-LB/M) is one of the most promising additive manufacturing technologies to fabricate complex-structured metal parts. However, its corresponding applications have been limited by technical bottlenecks and increasingly strict industrial requirements. Process optimization, a scientific issue, urgently needs to be solved. In this paper, a three-phase transient model based on the level-set method is established to examine the heat transfer and melt pool behavior in PBF-LB/M. Surface tension, the Marangoni effect, and recoil pressure are implemented in the model, and evaporation-induced mass and thermal loss are fully considered in the computing element. The results show that the surface roughness and density of metal parts induced by heat transfer and melt pool behavior are closely related to process parameters such as laser power, layer thickness, scanning speed, etc. When the volumetric energy density is low, the insufficient fusion of metal particles leads to pore defects. When the line energy density is high, the melt track is smooth with low porosity, resulting in the high density of the products. Additionally, the partial melting of powder particles at the beginning and end of the melting track usually contributes to pore formation. These findings provide valuable insights for improving the quality and reliability of metal additive manufacturing. Full article

This work provides a comprehensive investigation into the synergistic effects of zirconium and oxygen on the microstructural evolution, high-temperature oxidation resistance, and mechanical properties of γ-phase Ti52AlxZr alloys (x = 0, 0.5, 1, and 2 at.%) under systematically controlled oxygen concentrations. Unlike prior studies that have examined these alloying elements in isolation, this study uniquely decouples the contributions of interstitial (oxygen) and substitutional (zirconium) solutes by employing low (LOx) and high (HOx) oxygen levels. Alloys were synthesized via vacuum arc melting and subsequently subjected to homogenization annealing at 1250 °C for 100 h to ensure phase and microstructural stability. Characterization techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electron backscatter diffraction (EBSD) were employed to elucidate phase constitution and grain morphology. Zirconium addition was found to stabilize the γ-TiAl matrix, suppress α₂-phase formation, and promote grain coarsening in LOx specimens. Conversely, elevated oxygen concentrations led to α₂-phase precipitation along grain boundaries. Mechanical testing, comprising Vickers hardness and uniaxial compression at ambient and elevated temperatures (800 °C), revealed that both zirconium and oxygen significantly enhanced strength and hardness, with Ti52Al2Zr delivering optimal mechanical performance. Moreover, zirconium substantially improved oxidation resistance by promoting the formation of a thinner, adherent Al₂O₃ scale while simultaneously inhibiting TiO₂ growth. Collectively, the findings demonstrate the critical role of zirconium in engineering advanced γ-TiAl-based intermetallics with superior high-temperature structural integrity and oxidation resistance. Full article

Laser powder-bed fusion (L-PBF) additive manufacturing has been widely explored for fabricating intricate metallic parts such as lattice structures with thin struts. However, L-PBF-fabricated small parts (e.g., thin struts) exhibit different morphological and mechanical characteristics compared to bulk-sized parts due to distinct scan lengths, affecting the melt pool behavior between transient and quasi-steady states. This study investigates the keyhole porosity in Ti6Al4V thin struts fabricated by L-PBF, incorporating a range of strut sizes, along with various levels of linear energy densities. Micro-scaled computed tomography and image analysis were employed for porosity measurements and evaluations. Generally, keyhole porosity lessens with decreasing energy density, though with varying patterns across a higher energy density range. Keyhole porosity in struts predictably becomes severe at high laser powers and/or low scan speeds. However, a major finding reveals that the porosity is reduced with decreasing strut size (if less than 1.25 mm diameter), plausibly because the keyhole formed has not reached a stable state to produce pores in a permanent way. This implies that a higher linear energy density, greater than commonly formulated in making bulk components, could be utilized in making small-scale features to ensure not only full melting but also minimum keyhole porosity. Full article