Modified g-C_(3)N_(4) derived from ionic liquid and urea for promoting visible-light photodegradation of organic pollutants

In this work,modified g-C_(3)N_(4) was fabricated successfully by calcination of ionic liquid(IL) and urea.The addition of IL changed the polymerization mode of urea,induced the self-assembly of urea molecules,modified the morphological structure of the tightly packed g-C_(3)N_(4),and extended the electron conjugation system.When using 1-butyl-3-methylimidazolium chloride([Bmim]Cl) as a modifier,the heteroatom Cl could be inserted into the g-C_(3)N_(4) to optimize the electronic structure.The results of characterizations indicate that the unique structure of modified g-C_(3)N_(4) has an expanded electron delocalization range,introduces an interlayer charge transmission channel,promotes the charge transmission,reduces the band gap,enhances the absorption of visible light,and inhibits electron-hole recombination.Modified g-C_(3)N_(4) showed excellent photocatalytic performance for the degradation of rhodamine B and tetracycline.Furthermore,the effect of different anions in 1-butyl-3-methylimidazolium salts([Bmim]Cl,[Bmim]Br,[Bmim][BF_(4)],and [Bmim][PF_6]) on the structure and function of g-C_(3) N_(4) are discussed.

Removal of Stripes in Remote Sensing Images Based on Statistics Combined with Image Enhancement

A method to remove stripes from remote sensing images is proposed based on statistics and a new image enhancement method.The overall processing steps for improving the quality of remote sensing images are introduced to provide a general baseline.Due to the differences in satellite sensors when producing images,subtle but inherent stripes can appear at the stitching positions between the sensors.These stitchingstripes cannot be eliminated by conventional relative radiometric calibration.The inherent stitching stripes cause difficulties in downstream tasks such as the segmentation,classification and interpretation of remote sensing images.Therefore,a method to remove the stripes based on statistics and a new image enhancement approach are proposed in this paper.First,the inconsistency in grayscales around stripes is eliminated with the statistical method.Second,the pixels within stripes are weighted and averaged based on updated pixel values to enhance the uniformity of the overall image radiation quality.Finally,the details of the images are highlighted by a new image enhancement method,which makes the whole image clearer.Comprehensive experiments are performed,and the results indicate that the proposed method outperforms the baseline approach in terms of visual quality and radiation correction accuracy.

Template-free synthesis of hollow TiO2 nanospheres supported Pt for selective photocatalytic oxidation of benzyl alcohol to benzaldehyde

Heterogeneous photocatalytic system are widely applied to degrade organic pollutants or converse into high value-added chemicals. Both environmental and energy aspects should be considered to improve these chemical processes, favoring reaction conditions that involve room temperature and ambient O2 pressure. In the present work, hollow titanium dioxide nanospheres were fabricated via template-free method. The prepared samples were characterized by X-ray diffraction, N2 adsorption–desorption isotherms, transmission electron microscopy, and X-ray photoelectron spectroscopy. The photocatalytic activity was evaluated by photocatalytic oxidation of benzyl alcohol to benzaldehyde with visible light under atmospheric pressure at room temperature. The designed hollow structure(2%Pt–TiO2–5) not only exhibited a very high surface area,but also promoted photonic behavior and multiple light scattering, which as an efficient photocatalyst performed moderate conversion(about 20%) and high selectivity(> 99%) for oxidation of benzyl alcohol to benzaldehyde at room temperature with visible light in solvent of toluene.This work suggests that both hollow structure and Pt nanoparticles have great potential for execution of oxidative transformations under visible light.