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Modeling of real-world fuels and fuel mixtures in combustion engines, using computational fluid dynamics (CFD), calls for the development of compact and computationally efficient chemical kinetic mechanisms. To improve the modeling capabilities of multicomponent fuels it is necessary to transition from the single-component descriptions of fuels and move toward more complex, accurate multicomponent ones, where different functionality groups are included. In this work a newly developed multicomponent reaction mechanism, capable of modeling the four different functionality groups n-, iso-, cyclo-alkanes and aromatics, is presented. The mechanism consists of seven fuel components with different molecular sizes and the mechanism offers the possibility to create surrogate fuels for real-world fossil and alternative fuels and fuel mixtures. The presented mechanism accurately models key combustion parameters at a wide range of conditions, considering the intrinsic characteristics of the four functional groups. The presented mechanism offers a unique combination of fuel flexibility, modeling performance and a low computational cost, and it opens up the possibilities to cost-efficient CFD simulations of multicomponent surrogate aviation fuels.

Two-dimensional (2D) materials have emerged as a significant focus in materials research due to their tunable properties on thermoelectricity, spin-splitting, and nontrivial topology. Specifically, Janus-type 2D materials are interesting due to their additional breaking of inversion or mirror symmetry in the atomic structure. Based on the recently synthesized monolayer MoSi₂N₄ and previously studied BaIn₂Te₄ with the chemical formula of MA₂Z₄, we derive a family of 2D Janus compounds, namely BaABTe₄. Using first-principles calculations, a total of six Janus BaABTe₄ monolayers (BaAlGaTe₄, BaAlInTe₄, BaAlTlTe₄, BaGaInTe₄, BaGaTlTe₄, and BaInTlTe₄) were investigated for their dynamical stability, electronic, and topological properties. Notably, the Z₂ topological invariant calculated using HSE06 hybrid functional reveals that three out of the six monolayers (BaAlGaTe₄, BaAlTlTe₄, and BaInTlTe₄) have nontrivial topological phases, with BaInTlTe₄ exhibiting the largest positive system band gap of 17 meV. These three topological monolayers were further confirmed to be dynamically stable based on phonon dispersion and formation energy calculations. Subsequent orbital analysis of BaInTlTe₄ showed that the spin–orbit coupling effect drives the topological phase transition, resulting in the band inversion between the s-orbital of In + Tl and p_x + p_y-orbitals of Te around Γ. Also, the presence of the gapless edge states confirmed the nontrivial topological property. The Janus monolayers were found to exhibit significant Rashba spin-splitting except BaAlInTe₄. The topologically nontrivial BaAlTlTe₄ has the strongest Rashba strength of α^K-Γ= α^Γ-M = 1.03 eVÅ. Our results show that the coexisting nature of the nontrivial phase and Rashba-type splitting within the BaABTe₄ Janus monolayers might apply to spintronics.

Amid the growing demand for sustainable energy storage, biomass-derived porous carbons have emerged as eco-friendly alternatives to conventional electrode materials. This study shows that activated carbon prepared by one-step activation exhibits an enhanced specific surface area and pore volume. The optimum parameter for ameliorating the structural and electrochemical properties is 60 min of microwave heating. The specific surface area, pore volume, and mesopore volume of the resulting activated carbon (EUAC1–60) achieve 1589.0 m²/g, 0.82 cm³/g, and 0.28 cm³/g, respectively. EUAC1–60 exhibits an exceptional defect degree with an I_D/I_G value of 0.92 and can provide ample active sites for ion storage. The electrochemical investigation shows that the EUAC1–60 electrode has the highest specific capacitance of 232.92 F/g at a current density of 0.2 A/g. In addition, continuous cycling performance at a current density of 1 A/g validates its exceptional stability with capacitance retention of 89.90% and Coulombic efficiency of 117.21% after 10,000 cycles. The zinc ion hybrid supercapacitor with the EUAC1–60 cathode and Zn foil anode displayed an excellent energy density performance of 95.58 W h/kg at a power density of 64,800 W/kg. This research presents an innovative approach to the fabrication of high-performance activated carbon electrode materials from Eucommia Ulmoides Oliver, demonstrating its promising potential in supercapacitor applications.

In the field of data-driven material development, an imbalance in data sets where data points are concentrated in certain regions often causes difficulties in building regression models when machine learning methods are applied. One example of inorganic functional materials facing such difficulties is photocatalysts. Therefore, advanced data-driven approaches are expected to help efficiently develop novel photocatalytic materials even if an imbalance exists in data sets. We propose a two-stage machine learning model aimed at handling imbalanced data sets without data thinning. In this study, we used two types of data sets that exhibit the imbalance: the Materials Project data set (openly shared due to its public domain data) and the in-house metal-sulfide photocatalyst data set (not openly shared due to the confidentiality of experimental data). This two-stage machine learning model consists of the following two parts: the first regression model, which predicts the target quantitatively, and the second classification model, which determines the reliability of the values predicted by the first regression model. We also propose a search scheme for variables related to the experimental conditions based on the proposed two-stage machine learning model. This scheme is designed for photocatalyst exploration, taking experimental conditions into account as the optimal set of variables for these conditions is unknown. The proposed two-stage machine learning model improves the prediction accuracy of the target compared with that of the one-stage model.

The glycocalyx of endothelial cells is a dynamic, gel-like layer of glycoproteins, proteoglycans, and glycolipids that lines the luminal surface of blood vessels, playing a critical role in vascular permeability, mechanotransduction, and protection against shear stress. In this study, we investigated the in vitro adhesion of giant unilamellar vesicles (GUVs) composed of 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). Specifically, we examined mildly positively charged DOTAP-DMPC (20:80) GUVs, based on positively charged DOTAP and neutral DMPC but exhibiting an overall mild positive charge in physiological buffer, and neutral DMPC GUVs, which show a negative charge in physiological buffer. Adhesion to human umbilical vein endothelial cells (HUVEC) was studied under three culture conditions: dynamic (intact glycocalyx), static (underdeveloped glycocalyx), and glycocalyx-shed (degraded glycocalyx). Vesicles were produced via electroformation, stained with Texas Red dye, and perfused over endothelial cells at a controlled velocity to simulate slow blood flow. Adhesion was tracked using fluorescence microscopy combined with cell segmentation techniques. Adhesion of DOTAP-DMPC vesicles was significantly enhanced─by approximately 3.5-fold─on glycocalyx-shed cells compared to cells with an intact glycocalyx. In contrast, DMPC vesicles showed no adhesion under any condition. Analysis of vesicle size distributions revealed no significant differences between adherent and nonadherent vesicles or between DOTAP-DMPC and DMPC vesicles. These findings provide insights into the role of the endothelial glycocalyx in regulating adhesion, with potential implications for tumor cell interactions with the endothelium and mechanisms underlying DOTAP-based transfection.

Prolonged exposure to drugs prohibited in cosmetics may cause irritation and allergic reactions in humans. In this study, a method using ultrahigh performance liquid chromatography-tandem mass spectrometry was established for the simultaneous determination of 64 prohibited drugs spanning 11 categories, including 39 antibiotics, 8 antiallergics, 7 anesthetics, and 10 hormones. Typical cosmetic samples containing toner, cream, and oil matrices were extracted using a 70% acetonitrile solvent system with 1% formic acid and purified using a pass-through cleanup solid-phase extraction approach with a PRiME hydrophobic–lipophilic balanced column. Analytes covering a wide range of polarities showed excellent recoveries between 70 and 120%, with relative standard deviations of <11%. Excellent sensitivities ranging from 0.1 to 1 μg/kg were achieved with the limits of quantification. This method provides a rapid and comprehensive targeted strategy for the analysis of multiclass prohibited drugs in various cosmetic matrices. Finally, analysis of 20 cosmetic products using the optimized method identified prohibited substances in 6 samples at concentrations spanning 7 orders of magnitude.

Microplastics originate from the fragmentation of large plastic litter or environmental emissions. These new emerging pollutants not only cause physical harm but also serve as a substrate for other contaminants that adhere to and/or are adsorbed in microplastics. Consumption of these fine particles by organisms may lead to bioaccumulation and bioamplification. Conventional wastewater treatment using inorganic and organic polymeric flocculants is nonbiodegradable and toxic to ecosystem. Plant-derived polysaccharides can provide a highly efficient, nontoxic, and ecofriendly substitute to synthetic flocculants. The microplastic removal efficiency of polysaccharides derived from fenugreek, okra, and the combination of okra and fenugreek in the ratio of 1:1 was studied in simulated and water samples collected from various sources under bench-scale laboratory conditions. Water samples used for the study were collected from surface, ocean, and groundwater sources. A combination of optical microscopy and scanning electron microscopy with energy-dispersive X-ray spectroscopy (EDS) and Fourier transform infrared spectroscopy was used to study the microplastic removal efficiency of the plant-derived polysaccharides. ζ-Potential measurements and scanning electron microscopy were used to confirm the mechanism and capture of microplastic from water samples. The effect of varying polymer concentrations and contact time was also studied. The best concentration was found to be 1 g/L, with fenugreek showing the best microplastic removal in 30–60 min as the optimum contact time. It was found that fenugreek was the most efficient with an ∼89% microplastic removal from groundwater samples. A combination of okra and fenugreek was the most efficient for freshwater samples with an ∼77% microplastic removal. For the ocean water, okra showed the best removal efficiency of ∼80%. The mechanism of microplastic removal using plant-based polysaccharides as flocculant was found to be bridging. Both experimental and statistical analyses demonstrated that plant-based polysaccharides showed better microplastic removal efficiency than polyacrylamide, which is commercially used for water treatment.

The crude oil reserves of fractured-vuggy reservoirs are large, but most of them are heavy oil and ultraheavy oil reservoirs. They have the characteristics of high heavy metal ion concentration, high asphaltene content, high viscosity and density, and deep burial. They are difficult to exploit. Therefore, it is necessary to reduce the viscosity of the heavy oil to improve crude oil recovery. In this paper, the use of a viscosity-reducing foamer is investigated. First, the optimal concentration screening, temperature resistance, salt resistance, aging resistance, viscosity-reducing ability, ability to reduce oil–water interfacial tension, and ability to reduce gas–liquid surface tension were evaluated for DXY-03 viscosity-reducing foamer and DXY-08 viscosity-reducing foamer. Then, an oil displacement experiment on the viscosity-reducing foam was carried out under different placement conditions by using a visual fractured-vuggy model. The experimental results showed that the DXY-08 viscosity-reducing foamer has better temperature resistance, salt resistance, viscosity-reducing ability, and ability to reduce gas–liquid interfacial tension than the DXY-03 viscosity-reducing foamer. Therefore, the DXY-08 viscosity-reducing foam was selected for visual oil displacement experiments. The results of the visual oil displacement experiments showed that the DXY-08 viscosity-reducing foamer has good flooding ability, can effectively use the remaining oil in the fractures and holes in the middle of a reservoir, can also block large-opening fractures, and can effectively use the remaining oil in small- and medium-sized fractures. In addition, a liquid phase and a gas phase are produced after the disproportionation of the viscosity-reducing foamer. The liquid phase can emulsify and reduce the viscosity of crude oil, and the gas phase replaces the oil remaining in the fracture hole at the top of the reservoir under the action of gravity, which greatly improves oil recovery.

Due to the low bioactivity of titanium implants, the extended bone integration process after implantation substantially heightens the risk of inflammation, a primary cause of implant failure. To mitigate inflammatory responses and enhance bone integration between the implant and bone tissue, based on prior research that applied calcium phosphate (CaP) on titanium surfaces, we employed electrospraying technology to develop a drug-loaded polycaprolactone/silk fibroin/polydopamine (PCL/SF/PDA) composite coating as the second layer on top of the calcium phosphate deposition. The surface morphologies of the CaP deposits and composite coatings were characterized by SEM. The SF/PDA gel significantly increased the adhesion of the coating, thereby enhancing its clinical application potential. All materials exhibited excellent biodegradability, and their superior biocompatibility was confirmed through cell assays. Following in vitro experiments, in vivo studies were conducted using a rat cranial defect model. Micro-CT results and staining demonstrated that CaP deposition significantly accelerated bone integration between the titanium substrate and bone, while the drug-loaded polymer coating notably improved the inflammatory environment at the defect site. These findings offer new insights into the development of titanium implants.

This study investigates potassium–lithium metaphosphate glasses using Differential Scanning Calorimetry, Complex Impedance Spectroscopy, Nuclear Magnetic Resonance, and Raman Spectroscopy to elucidate the structural mechanisms underlying the Mixed Ion Effect. Thermal analyses reveal a systematic decrease in the glass transition temperature with increasing potassium content, which is dictated not solely by ionic size mismatch but also by structural reorganization within the glass network. The redistribution of nonbridging oxygens and the reduction of phosphate cross-links contribute to this behavior. Impedance spectroscopy shows a pronounced nonlinear reduction in ionic conductivity, decreasing by over 6 orders of magnitude at room temperature for the intermediate composition. NMR analysis indicates a nearly linear evolution of ³¹P and ⁷Li chemical shifts and full width at half-maximum, confirming the absence of phase segregation. Raman spectroscopy reveals a consistent PO₂ symmetric mode shift, indicative of solid solution behavior and random cation mixing. These findings validate two key hypotheses of the Random Ion Distribution Model: the structural specificity of each cation site and their random distribution within the glass network, while also demonstrating that structural reorganization plays a critical role in modulating T_g.