Single-crystal silver nanowires: Preparation and Surface-enhanced Raman Scattering (SERS) property

Ordered Ag nanowire arrays with high aspect ratio and high density self-supporting Ag nanowire patterns were successfully prepared using potentiostatic electrodeposition within the confined nanochannels of a commercial porous anodic aluminium oxide (AAO) template. X-ray diffraction and selected area electron diffraction analysis show that the as-synthesized samples have preferred (220) orientation. Transmission electron microscopy and scanning electron microscopy investigation reveal that large-area and ordered Ag nanowire arrays with smooth surface and uniform diameter were synthesized. Surface-enhanced Raman Scattering (SERS) spectra show that the Ag nanowire arrays as substrates have high SERS activity.Comment: 5 pages, 4 figure

Unveiling the Mechanism of Plasma-Catalytic Low-Temperature Water–Gas Shift Reaction over Cu/γ-Al₂O₃ Catalysts

The water-gas shift (WGS) reaction is a crucial process for hydrogen production. Unfortunately, achieving high reaction rates and yields for the WGS reaction at low temperatures remains a challenge due to kinetic limitations. Here, nonthermal plasma coupled to Cu/γ-Al2O3 catalysts was employed to enable the WGS reaction at considerably lower temperatures (up to 140 °C). For comparison, thermal-catalytic WGS reactions using the same catalysts were conducted at 140-300 °C. The best performance (72.1% CO conversion and 67.4% H2 yield) was achieved using an 8 wt % Cu/γ-Al2O3 catalyst in plasma catalysis at ∼140 °C, with 8.74 MJ mol-1 energy consumption and 8.5% H2 fuel production efficiency. Notably, conventional thermal catalysis proved to be ineffective at such low temperatures. Density functional theory calculations, coupled with in situ diffuse reflectance infrared Fourier transform spectroscopy, revealed that the plasma-generated OH radicals significantly enhanced the WGS reaction by influencing both the redox and carboxyl reaction pathways

An Effective Synthesis Method for Tilorone Dihydrochloride with Obvious IFN-α Inducing Activity

Tilorone dihydrochloride (1) has great potential for inducing interferon against pathogenic infection. In this paper, we describe a convenient preparation method for 2,7-dihydroxyfluoren-9-one (2), which is a usual pharmaceutical intermediate for preparing tilorone dihydrochloride (1). In the novel method, methyl esterification of 4,4′-dihydroxy-[1,1′-biphenyl]-2-carboxylic acid (4) was carried out under milder conditions with higher yield and played an important role in the preparation of compound 2. The structures of the relative intermediates and target compound were characterized by melting point, IR, MS, and 1H-NMR. Furthermore, the synthesized tilorone dihydrochloride exhibited an obvious effect on induction of interferon-α (IFN-α) in mice within 12 h, and the peak level was observed until 24 h. This fruitful work has resulted in tilorone dihydrochloride becoming available in large-scale and wide application in clinics, which has a good pharmaceutical development prospects

Optimization of Numerical Methods for Transforming UTM Plane Coordinates to Lambert Plane Coordinates

The rapid transformation from UTM (Universal Transverse Mecator) projection to Lambert projection helps to realize timely merging, inversion, and analysis of high-frequency partitioned remote sensing images. In this study, the transformation error and the efficiency of the linear rule approximation method, the improved linear rule approximation method, the hyperbolic transformation method, and the conformal transformation method were compared in transforming the coordinates of sample points on WGS84 (The World Geodetic System 1984)-UTM zonal projections to WGS84-Lambert projection coordinates. The effect of the grid aspect ratio on the coordinate transformation error of the conformal transformation method was examined. In addition, the conformal transformation method-based error spatial pattern of the sample points was analyzed. The results show that the conformal transformation method can better balance error and efficiency than other numerical methods. The error of the conformal transformation method is less affected by grid size. The maximum x-error is less than 0.36 m and the maximum y-error is less than 1.22 m when the grid size reaches 300 km × 300 km. The x- and y-error values decrease when square grids are used; namely, setting the grid aspect ratio close to 1 helps to weaken the effect of increasing grid area on the error. The dispersion of the error distribution and the maximum error of sample points both decrease relative to their minimum distance to the grid edge and stabilize at a minimum distance equal to 70 km. This study can support the rapid integration of massive remote sensing data over large areas

Optimization of Numerical Methods for Transforming UTM Plane Coordinates to Lambert Plane Coordinates

The rapid transformation from UTM (Universal Transverse Mecator) projection to Lambert projection helps to realize timely merging, inversion, and analysis of high-frequency partitioned remote sensing images. In this study, the transformation error and the efficiency of the linear rule approximation method, the improved linear rule approximation method, the hyperbolic transformation method, and the conformal transformation method were compared in transforming the coordinates of sample points on WGS84 (The World Geodetic System 1984)-UTM zonal projections to WGS84-Lambert projection coordinates. The effect of the grid aspect ratio on the coordinate transformation error of the conformal transformation method was examined. In addition, the conformal transformation method-based error spatial pattern of the sample points was analyzed. The results show that the conformal transformation method can better balance error and efficiency than other numerical methods. The error of the conformal transformation method is less affected by grid size. The maximum x-error is less than 0.36 m and the maximum y-error is less than 1.22 m when the grid size reaches 300 km × 300 km. The x- and y-error values decrease when square grids are used; namely, setting the grid aspect ratio close to 1 helps to weaken the effect of increasing grid area on the error. The dispersion of the error distribution and the maximum error of sample points both decrease relative to their minimum distance to the grid edge and stabilize at a minimum distance equal to 70 km. This study can support the rapid integration of massive remote sensing data over large areas

Naphthalene decomposition by dielectric barrier discharges at atmospheric pressure

Naphthalene decomposition in O 2 /N 2 gas mixture with different O 2 concentrations has been studied in a dielectric barrier discharge reactor at atmospheric pressure. O 2 played an important role in the decomposition of naphthalene, especially in the selectivities of CO and CO 2 . There was an optimal naphthalene decomposition rate at an O 2 concentration of about 3%. The CO x selectivity increased up to 83.3% gradually with the O 2 concentration increasing from 1% to 20%. Nanoparticles were found in the gas samples, concentrations of which can be reduced greatly through raising the O 2 concentration. The decomposition byproducts of naphthalene were obviously different under different O 2 concentrations. Some nitrogenous compounds reduced but some oxygenous compounds increased with increasing O 2 concentration. The mechanism of naphthalene decomposition was proposed as that naphthalene was first initiated by dehydrogenation and oxidation, and then followed by deep oxidation to CO and CO 2

Highly effective mineralization of acetic acid wastewater via catalytic ozonation over the promising MnO2/γ-Al2O3 catalyst

The complete mineralization of acetic acid in wastewater through a biodegradation process is difficult due to the α-position methyl coordinated with the carboxyl group, and this work explored the oxidation performance of acetic acid by catalytic ozonation with metal oxides supported on γ-Al2O3. It was found that MnO2/γ-Al2O3 catalyst achieved superior mineralization performance to Co/Fe/CeOx supported on γ-Al2O3 for acetic acid wastewater treatment. The effects of MnO2 loading, catalyst dosage, acetic acid concentration, O3 concentration, ozonation temperature, and initial pH value of the acetic acid solution were investigated. Typically, the mineralization of acetic acid over 1.0 wt.% MnO2/γ-Al2O3 catalyst was as high as 88.4% after 300 min ozonation of 1.0 g·L‒1 acetic acid at 25 °C with the highest energy efficiency around 15 g·kWh‒1. By contrast, the mineralization of acetic acid could only reach 43.2% in the absence of the catalyst, with an energy efficiency of 5.1 g·kWh−1. Radical quenchers and indicated that ·OH radical, O2− species originated from ozone played an important role in the catalytic ozonation of acetic acid into CO2 and H2O. Besides, the catalytic ozonation mechanism of acetic acid over MnO2/γ-Al2O3 was carefully proposed based on the in situ DRIFTS results

LandQv2: A MapReduce-Based System for Processing Arable Land Quality Big Data

Arable land quality (ALQ) data are a foundational resource for national food security. With the rapid development of spatial information technologies, the annual acquisition and update of ALQ data covering the country have become more accurate and faster. ALQ data are mainly vector-based spatial big data in the ESRI (Environmental Systems Research Institute) shapefile format. Although the shapefile is the most common GIS vector data format, unfortunately, the usage of ALQ data is very constrained due to its massive size and the limited capabilities of traditional applications. To tackle the above issues, this paper introduces LandQv2, which is a MapReduce-based parallel processing system for ALQ big data. The core content of LandQv2 is composed of four key technologies including data preprocessing, the distributed R-tree index, the spatial range query, and the map tile pyramid model-based visualization. According to the functions in LandQv2, firstly, ALQ big data are transformed by a MapReduce-based parallel algorithm from the ESRI Shapefile format to the GeoCSV file format in HDFS (Hadoop Distributed File System), and then, the spatial coding-based partition and R-tree index are executed for the spatial range query operation. In addition, the visualization of ALQ big data with a GIS (Geographic Information System) web API (Application Programming Interface) uses the MapReduce program to generate a single image or pyramid tiles for big data display. Finally, a set of experiments running on a live system deployed on a cluster of machines shows the efficiency and scalability of the proposed system. All of these functions supported by LandQv2 are integrated into SpatialHadoop, and it is also able to efficiently support any other distributed spatial big data systems

LandQ(upsilon 2): A MapReduce-Based System for Processing Arable Land Quality Big Data

Arable land quality (ALQ) data are a foundational resource for national food security. With the rapid development of spatial information technologies, the annual acquisition and update of ALQ data covering the country have become more accurate and faster. ALQ data are mainly vector-based spatial big data in the ESRI (Environmental Systems Research Institute) shapefile format. Although the shapefile is the most common GIS vector data format, unfortunately, the usage of ALQ data is very constrained due to its massive size and the limited capabilities of traditional applications. To tackle the above issues, this paper introduces LandQv2, which is a MapReduce-based parallel processing system for ALQ big data. The core content of LandQv2 is composed of four key technologies including data preprocessing, the distributed R-tree index, the spatial range query, and the map tile pyramid model-based visualization. According to the functions in LandQv2, firstly, ALQ big data are transformed by a MapReduce-based parallel algorithm from the ESRI Shapefile format to the GeoCSV file format in HDFS (Hadoop Distributed File System), and then, the spatial coding-based partition and R-tree index are executed for the spatial range query operation. In addition, the visualization of ALQ big data with a GIS (Geographic Information System) web API (Application Programming Interface) uses the MapReduce program to generate a single image or pyramid tiles for big data display. Finally, a set of experiments running on a live system deployed on a cluster of machines shows the efficiency and scalability of the proposed system. All of these functions supported by LandQv2 are integrated into SpatialHadoop, and it is also able to efficiently support any other distributed spatial big data systems

Effect of Zr Addition on the Low-Temperature SCR Activity and SO₂ Tolerance of Fe–Mn/Ti Catalysts

Zr is added to the Fe–Mn/Ti catalyst to increase NO conversion and improve SO₂ tolerance. It is found that 0.03 is the optimal ratio for Zr/(Ti + Zr). With this ratio, the NO conversion below 150 °C increases, and the SO₂ poisoning is alleviated, while the further increase of Zr does not have a positive effect on NO conversion and SO₂ tolerance. With Zr additive, more manganese oxides are reduced in the form of MnO₂ and Mn₂O₃ at lower temperature in H₂-TPR, and the total amount of H₂ consumption rises, indicating better redox properties. It leads to the increase of NO complexes on the catalysts. Despite the small decrease of NH₃ adsorption, the reaction via the L–H way is promoted and NO conversion increases. Furthermore, more nitrates and NO₂ are formed in the reaction with SO₂ on Fe–Mn/Ti–Zr(0.03) compared to Fe–Mn/Ti, so the L–H reaction way is less inhibited by SO₂ with Zr additive, and the SO₂ tolerance of this catalyst is also improved