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关键词： Diesel engine   Boron doped filter   Exhaust emission   Catalyst   Environmental effect   Activated carbon  

摘要： One of the main causes of environmental pollution is the exhaust emissions emitted from internal combustion engines. Currently, the use of rare elements such as platinum, palladium and rhodium in metal catalysts, which form part of exhaust purification systems, causes production difficulties and increased costs. Furthermore, these elements do not possess particle retention properties. This study aimed to determine whether geopolymer materials could be used as an innovative exhaust purification system in the automotive industry, given that porous geopolymer structures contain catalyst materials, are resistant to pressure and temperature, are easy and inexpensive to apply, and can be made from waste raw materials. In this study, newly developed aluminum-carbon-boron (5% Al₂O₃ and 1% activated carbon) doped emission treatment filter (also named as “AlCBDoF”) and zirconium-boron (5% ZrO₂ and 5% Zr(SO₄)₂) doped emission treatment filter (also named as “ZrBDoF”) are developed and their effects on the diesel engine performance and emissions were investigated. The developed novel emission treatment filters and a standard catalytic converter of the diesel engine were separately installed in the exhaust after treatment line of a 4-cylinder diesel engine under different speeds and loads. When standard catalytic converter is used, HC emissions are improved by up to 48%, while HC emissions are reduced by 60% when AlCBDoF is used and 70% when ZrBDoF is utilized. The fact that the filter output values of the CO₂ are higher than the filter input values shows that the filters are effective in CO₂ conversion of CO emissions by acting as a catalyst. It has also been observed to demonstrate over 99% improvement in particulate matter. Therefore, the newly developed Boron Doped Filters can be used as a single device instead of both Diesel Oxidation Catalyst and Diesel Particulate Filter. In addition to improving

关键词： Magneto-ionics   Exchange bias   MnCoN  

摘要： To address growing computational demands, energy-efficient hardware technologies such as spintronics and neuromorphic computing have attracted significant interest. In particular, magneto-ionics offers a low-power, non-volatile approach to control magnetic properties, making it particularly suitable for manipulating antiferromagnetic (AFM) materials. In this work, we report magneto-ionic control of exchange bias (EB) in Mn_1−xCo_xN/Co with a compositionally tunable Néel temperature, T_N. The high T_N in MnN (> 650 K) typically necessitates high-temperature annealing, which triggers uncontrolled thermally induced ion-motion effects. Addition of Co to MnN reduces T_N, enabling robust EB to be established after field cooling from 400 K, while preserving structural integrity. Importantly, EB can be subsequently tuned by voltage, up to a 30% enhancement observed at 100 K alongside an increase in saturation magnetization (up to ≈ 250 emu cm⁻³). Unlike previous works on similar single-layer nitrides, incorporating an additional ferromagnetic Co layer to form an AFM/ferromagnetic bilayer amplifies the voltage-induced effects. This work highlights the dual role of Co addition to MnN: (i) reducing the thermal requirements for setting EB by lowering T_N, and (ii) enhancing electrical control of EB. These results represent a step forward towards the development of low-power voltage-controlled spintronic devices.

关键词： Coalbedgas   Separation   1,3-Diox   Hydrate particles   Methane recovery  

摘要： Recovering CH₄ from low-concentration coalbed gas (LCBG) is of critical importance for addressing energy shortages and reducing greenhouse gas emissions. However, the formation of hydrates in solution is frequently limited by mass transfer constraints, resulting in reduced separation efficiency. This study proposes an advanced LCBG separation method that employs loose 1,3-dioxlane (1,3-Diox) hydrate particles as the medium. It comprehensively examines the effects of various kinetic hydrate promoters, operating temperature, initial pressure, and 1,3-Diox hydrate particle size on separation performance. The results show that hydrate particles formed from a solution containing 5.56 mol% 1,3-Diox and 5000 ppm L-tryptophan (L-Trp) achieve optimal separation performance for LCBG. Under conditions of 3.0 MPa and 269.65 K, the CH₄ concentration in the residual gas phase decreased from 30.09 mol% to 15.20 mol%, achieving a CH₄ recovery rate of 78.70% and a separation factor of 3.84. Raman spectroscopy analysis confirms that CH₄ molecules effectively occupy the unsaturated small cages within 1,3-Diox primary hydrate particles after separation, while N₂ molecules compete with CH₄ for occupancy in the small cages. Moreover, the findings indicate that the CH₄ recovery rate initially increases and then decreases with decreasing temperature. While increasing the initial pressure accelerates the reaction rate, it slightly diminishes the CH₄ recovery rate. Additionally, smaller 1,3-Diox hydrate particle sizes enhance both the reaction rate and the CH₄ recovery rate. This study offers significant theoretical insights and practical guidance for the application of hydrate separation technology in recovering CH₄ from coalbed gas.

关键词： Three-way catalysts   LaNi1-xCoxO3 perovskite   Automotive exhaust gas   CO oxidation   C3H6 oxidation  

摘要： LaNi_1-xCo_xO₃ (x = 0, 0.3, 0.5) perovskite-type oxides were synthesized and evaluated as three-way catalysts (TWCs) for the simultaneous removal of CO, C₃H₆, and NO from automotive exhaust. TPR results revealed a progressive decrease in reduction temperatures upon cobalt incorporation, attributed to enhanced hydrogen spillover and improved oxygen mobility. FESEM and BET analyses showed pseudo-spherical morphologies with increased macroporosity but reduced surface areas and particle aggregation upon cobalt doping. XPS demonstrated enrichment of chemisorbed oxygen (O_ad) and higher Ni³⁺/Ni²⁺ ratios with increasing cobalt content, correlating with enhanced redox properties. Optical characterization revealed band-gap narrowing from 2.40 eV (LaNiO₃) to 2.31 eV (LaNi_0.5Co_0.5O₃), favoring electron transfer. Catalytic activity tests demonstrated significant improvements in CO and C₃H₆ oxidation after cobalt substitution, with T₅₀ for CO oxidation decreasing from 185 °C (LaNiO₃) to 164.6 °C (LaNi_0.5Co_0.5O₃), and T₉₀ from 228.1 °C (LaNiO₃) to 207.5 °C (LaNi_0.5Co_0.5O₃). Similarly, T₅₀ for C₃H₆ conversion reached 266.8 °C and T₉₀ at 312.1 °C for LaNi_0.5Co_0.5O₃, compared to 307.1 °C and 335.0 °C for pristine LaNiO₃. Although NO conversion peaked at ∼90% around 275 °C for LaNiO₃, it decreased upon Co substitution due to equilibrium constraints. These findings demonstrate that cobalt incorporation enhances reducibility, lattice oxygen mobility, and surface oxygen reactivity, thereby promoting CO and hydrocarbon oxidation under TWC conditions.

关键词： Glycerol   1,3-propanediol   Pt-WOx interaction   Oxygen vacancy   TetrahedralW5  

摘要： Pt/WO_x/Al₂O₃ catalysts with tunable oxygen-vacancy concentrations were prepared by sequential impregnation using Al₂O₃ supports calcined at different temperatures. Glycerol hydrogenolysis to 1,3-propanediol showed a volcano-type dependence on support calcination temperature, and Pt/WO_x/Al₂O₃-600 gave the highest 1,3-PDO yield, nearly twice that of the untreated catalyst. The superior performance of Pt/WO_x/Al₂O₃-600 is primarily attributed to the formation of abundant oxygen vacancies on the Al₂O₃ support at the optimal calcination temperature. Quantitative correlation analysis indicates that oxygen vacancies are far more closely associated with tungsten dispersion, serving as the primary anchoring sites, whereas Al³⁺_penta likely plays a secondary of stabilizing role. At excessively high calcination temperatures, sintering decreases the vacancy concentration and damages the interfacial structure, leading to lower activity. These results demonstrate that support defect engineering is an effective strategy for regulating metal-support interactions and constructing efficient bifunctional catalysts for selective C-O bond cleavage.

摘要： This work presents, for the first time, both experimental and numerical investigations of the thermal and chemical structure of laminar premixed flames of aviation kerosene TS-1 and its four-component surrogate fuel, SU4 (n-decane, isocetane, methylcyclohexane, and tetralin). Experiments were conducted for lean (φ = 0.8) and stoichiometric (φ = 1.0) mixtures at atmospheric pressure. Species mole fraction profiles for more than 20 compounds, including key intermediates and radicals, were measured using soft-ionization molecular-beam mass spectrometry. The flame structures of TS-1 and SU4 show good agreement for most species, confirming the suitability of the surrogate for modeling high-temperature combustion behavior of the real fuel, with the exception of soot formation processes. Based on the experimental data, the detailed kinetic mechanism CRECK_2003_TOT_HT was validated. The main discrepancies were associated with the tetralin sub-mechanism. A reduced skeletal mechanism, KCPsur, consisting of 85 species and 183 reactions, was developed using the Directed Relation Graph (DRG) and Computational Singular Perturbation (CSP) methods. The KCPsur mechanism demonstrates predictive performance comparable to the detailed CRECK mechanism, while reducing computational cost by more than a factor of 32. This makes it suitable for CFD simulations of gas turbine combustion systems, particularly in cases where soot formation is not the primary focus.

关键词： IVX-121   respiratory syncytial virus   RSV   vaccine   virus-like particle  

摘要： Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract disease in all age groups, with substantial burden in older adults. Here, we report the safety and immunogenicity of IVX-121, an investigational virus-like particle vaccine against RSV. This Phase 1/1b trial (EudraCT number: 2020-003633-38) randomized 90 healthy young (18-45 y of age;Phase 1) and 130 older adults (60-75 y of age;Phase 1b) to receive a single intramuscular injection of IVX-121 at low (25 & micro;g), medium (75 & micro;g), or high (250 & micro;g) dose, with/without the adjuvant aluminum hydroxide (Al[OH]3), or placebo. Outcomes were assessed through Day 180. Older adult participants who had received IVX-121 or placebo could continue into an extension study in which safety was assessed for an additional 6 months before receiving IVX-121 (75 & micro;g, unadjuvanted, open-label) on Day 365;safety and immunogenicity were assessed up to Day 546. Adverse reactions were generally mild, and there were no vaccine-related serious adverse events. All IVX-121 dose levels and formulations boosted preexisting RSV neutralizing antibody (nAb) responses. Although not statistically powered to compare treatment groups, there was no clear dose response and the adjuvant Al(OH)3 did not appear to improve immunogenicity. For both age groups, IVX-121 induced nAbs against RSV A and B, which remained above baseline levels for at least 6 months. A second dose of IVX-121 in older adults elicited a modest increase in nAbs against RSV A but not RSV B. Overall, IVX-121 had a favorable safety profile and induced immune responses against RSV in young and older adults.

关键词： Synthetic Aperture Radar (SAR)   flood mapping   Google Earth Engine (GEE)   Multilayer Perceptron (MLP)   Deep Learning   graphical user interface (GUI)  

摘要： Rapid and accurate flood mapping and monitoring are essential for effective disaster management, response, and recovery, as well as for advancing hydrological sciences. Despite the increasing availability of geospatial data and cloud platforms like Google Earth Engine (GEE), existing GEE-based flood mapping applications largely depend on traditional thresholding techniques requiring manual input or struggle with latency due to loose-coupling of complex models. This study introduces DeepSAR Flood Mapper, a novel, fully automated deep learning-based flood mapping application on the GEE cloud platform as an operational, publicly accessible tool, providing interactive and near-real-time capabilities globally. DeepSAR Flood Mapper utilizes a pre-trained Multilayer Perceptron (MLP) deep learning model, selected for its computational efficiency and ability to model highly nonlinear functions, facilitating seamless integration with GEE. The model integrates two crucial input datasets: Sentinel-1 Synthetic Aperture Radar imagery (VV and VH polarization) for all-weather surface water detection, and Height Above the Nearest Drainage topographic data to mitigate commission errors in elevated areas and enhance reliability. Trained on a combination of global benchmark datasets and historical flood maps, the MLP model is deployed using an Offline Training and Online Prediction coupling strategy, which eliminates data transfer bottlenecks and allows for seamless, on-demand prediction within GEE. The application features an intuitive user interface that allows users to define an Area of Interest and target date, requiring no specialized knowledge. Performance evaluation demonstrates that DeepSAR Flood Mapper significantly improves flood mapping accuracy compared to traditional approaches, including Otsu's thresholding and classical machine learning models, Support Vector Machines and Random Forests. Its near-real-time capability supports timely and scalable flood monitoring across d

关键词： Land surface phenology   MODIS-like NDVI   spatiotemporal data fusion   global vegetation dynamics   remote sensing  

摘要： As climate change continues to reshape global ecosystems, accurately monitoring and understanding shifts in land surface phenology (LSP) has become increasingly critical for detecting vegetation responses, assessing ecosystem resilience, and improving predictions of climate-biosphere interactions. While several moderate-to-fine spatial resolution global LSP datasets exist, most are constrained to post-2000 records due to the availability of MODIS era observations, leaving a significant gap in long-term phenological information and limiting our ability to investigate multi decadal trends. To address this, we developed the first global 1 km resolution LSP dataset spanning 1982-2018. By integrating MODIS and AVHRR NDVI data through the enhanced Flexible Spatiotemporal Data Fusion (cuFSDAF) model, we reconstructed pre-2000 MODIS-like NDVI time series with improved temporal consistency and reduced cross sensor bias. Using logistic functions and third-order derivatives, we extracted four key phenological metrics, including the start of the growing season (SOS), maturity, senescence, and the end of the growing season (EOS), enabling detailed characterization of vegetation development stages across diverse biomes. In the Northern Hemisphere (NH), SOS, maturity, and EOS advanced significantly from 1982 to 2018, while senescence was delayed, indicating a widespread lengthening of the growing season. In contrast, the Southern Hemisphere (SH) experienced delayed SOS, maturity, and senescence, with EOS occurring earlier, suggesting a shortening of the growing season and revealing contrasting hemispheric sensitivities to climate forcing. These metrics were validated against ground-based observations from multiple networks, demonstrating strong consistency, high accuracy, and reliable reconstruction of long term phenological signals. As the first dataset of its kind at 1 km resolution over such an extended period, it provides an invaluable resource for studying global vegetation d