Influence of deposition parameters on surface morphology and application of CuInS2 thin films in solar cell and photocatalysis

Copper indium disulfide (CuInS₂) thin films as an absorption layer for solar cell and photocatalytic degradation of organic pollutants, were successfully electrodeposited on the FTO coated glass substrate using the simple and inexpensive electrodeposition method and a sulfurization process. The effects of the Cu/In molar ratio, annealing temperature and kind of Cu²⁺ precursor (Cu(salen) and Cu(acac)₂ as novel Cu²⁺ precursors) on the structural and morphological properties of samples were examined. The XRD diffraction patterns and energy dispersive spectroscopy measurements exhibit that high-quality film with superior crystalline structure was formed in the presence of Cu(salen) as Cu²⁺ precursor. Also, we found that a suitable heat treatment temperature could suppress the CuS phases and form well-crystallized CIS. As we know, this is the first reported efficiency for any CuInS₂ superstrate solar cell to date that fabricated using Cu(salen) as Cu²⁺ precursor. In addition, the photocatalytic degradation of organic dye in the presence of as-synthesized CuInS₂ thin films was studied. The as-prepared semiconductor photocatalysts have a good reusability; it can be successfully reused for 5 times recycling photoactivity tests.     

Optimization of post-classification processing of high-resolution satellite image: A case study

The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 m resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5 satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of China.     

Decolorization of reactive brilliant red X-3B by heterogeneous photo-Fenton reaction using an Fe–Ce bimetal catalyst

Decolorization of reactive brilliant red X-3B was studied by using an Fe–Ce oxide hydrate as the heterogeneous catalyst in the presence of H₂O₂ and UV. The decolorization rate was in the order of UV–Fe–Ce–H₂O₂ > UV–Fe³⁺–H₂O₂ > UV–H₂O₂ > UV–Fe–Ce ≥ Fe–Ce–H₂O₂ > Fe–Ce. Under the conditions of 34 mg l⁻¹ H₂O₂, 0.500 g l⁻¹ Fe–Ce, 36 W UV and pH 3.0, 100 mg l⁻¹ X-3B could be decolorized at efficiency of more than 99% within 30 min. The maximum dissolved Fe during the reaction was 1 mg l⁻¹. From the fact that the decolorization rate of the UV–Fe–Ce–H₂O₂ system was significantly higher than that of the UV–Fe³⁺–H₂O₂ system at Fe³⁺ = 1 mg l⁻¹, it is clear that the Fe–Ce functioned mainly as an efficient heterogeneous catalyst. UV–vis, its second derivative spectra, and ion chromatography (IC) were employed to investigate the degradation pathway. Fast degradation after adsorption of X-3B is the dominant mechanism in the heterogeneous catalytic oxidation system. The first degradation step is the breaking down of azo and CN bonds, resulting in the formation of the aniline- and phenol-like compounds. Then, the breaking down of the triazine structure occurred together with the transformation of naphthalene rings to multi-substituted benzene, and the cutting off of sulphonic groups from the naphthalene rings. The last step includes further decomposition of the aniline structure and partial mineralization of X-3B.     

Competitive Reaction During Decomposition of Hexachlorobenzene Over Ultrafine Ca–Fe Composite Oxide Catalyst

The decomposition of hexachlorobenzene (HCB) has been investigated over ultrafine Ca–Fe composite oxide catalyst (Ca/Fe atomic ratio was 3.4), CaO and α-Fe₂O₃ by using in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Adsorption experiments on the surface of oxides monitored by in situ DRIFTS showed that partial oxidation products, i.e., phenolate and acetate species were formed on the surface of Ca–Fe composite oxide. The further studies indicated that Ca–Fe composite oxide catalyst was easier to induce the rupture of C–Cl bond and C–C bond of aromatic rings. The best catalytic activity of Ca–Fe composite oxide may be related to the acidity, which was determined by NH₃–TPD. The products after reaction have been analyzed by XRD and chloride selective electrode. Ca–Fe composite oxide exhibited the highest extent of mineralization for organic chlorine among the different oxides tested. The combined results of current and previous experiments demonstrated that two competitive reactions took place during the decomposition process of HCB: (1) hydrodechlorination resulting in the formation of lower chlorinated benzenes and (2) oxidation of aromatic rings leading to the rupture of aromaticity and the formation of oxidation products. The latter is the major process in the coexisted competitive reaction. A possible decomposition pathway was discussed.     

Adsorption of benzoic acid by CTAB exchanged montmorillonite

This paper reports the adsorption of benzoic acid from water on cetyl trimethylammonium exchanged montmorillonite (CTAB-montmorillonite). Important factors are the adsorbent concentration, ionic strength, equilibrium time and pH. The largest adsorption is at pH 9. The adsorption kinetics data fitted the pseudo-second-order equation. The adsorption isotherms at different pH were linear indicating a partition mechanism. Up to about 61% of the dissolved benzoic acid was adsorbed by CTAB-montmorillonite. These results indicate that CTAB-montmorillonite is a potential adsorbent for benzoic acid.     

Investigation of isosynthesis via CO hydrogenation over ZrO2 and CeO2 catalysts: Effects of crystallite size,phase composition and acid–base sites

This paper investigates the isosynthesis via CO hydrogenation over zirconia and ceria catalysts. Various techniques including XRD, NH₃-TPD, CO₂-TPD and BET surface area were employed for the catalyst characterization. The results showed that not only acid–base properties, but also crystallite size and crystal phase essentially influenced the catalytic performance. It was found that the activity and the selectivity of isobutene in hydrocarbons on nanoscale catalysts were higher than those on the micronscale ones. Moreover, the acid–base properties were dependent on the fraction of tetragonal phase for zirconia, but independent on crystal phase for ceria. The synthesized nanoscale zirconias were more active than the commercial one but less than the nanoscale ceria. From the results, it was indicated that zirconia with 29% tetragonal phase exhibited the highest activity. Furthermore, the presence of tetragonal phase in zirconia played an important role on the selectivity of isobutene in hydrocarbons.     

基于溶胶凝胶法的TiO2溶胶的制备

用N-N二甲基乙酰胺(DMAC)作溶剂,钛酸丁酯作前驱物,冰乙酸为稳定剂,通过溶胶凝胶法制得了二氧化钛(TiO2)溶胶,并且对加水方式、加水量、溶剂量、pH值、温度等影响因素进行了考察.结果表明,当采用分散加水方式,温度在25℃～35℃以下,DMAC与钛酸丁酯的体积比为3.5:1,V(H2O)/V(Ti(OC4H9)4...     

Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration

Calibrating watershed-scale hydrologic models remains a critical but challenging step in the modeling process. The Soil and Water Assessment Tool (SWAT) is one example of a widely used watershed-scale hydrologic model that requires calibration. The calibration algorithms currently available to SWAT modelers through freely available and open source software, however, are limited and do not include many multi-objective genetic algorithms (MOGAs). The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient MOGA calibration algorithm for a wide variety of applications including for SWAT model calibration. Therefore, the objective of this study was to create an open source software library for multi-objective calibration of SWAT models using NSGA-II. The design and implementation of the library are presented, followed by a demonstration of the library through a test case for the Upper Neuse Watershed in North Carolina, USA using six objective functions in the model calibration.     

Prediction of urban stormwater quality using artificial neural networks

There are a vast number of complex, interrelated processes influencing urban stormwater quality. However, the lack of measured fundamental variables prevents the construction of process-based models. Furthermore, hybrid models such as the buildup-washoff models are generally crude simplifications of reality. This has created the need for statistical models, capable of making use of the readily accessible data. In this paper, artificial neural networks (ANN) were used to predict stormwater quality at urbanized catchments located throughout the United States. Five constituents were analysed: chemical oxygen demand (COD), lead (Pb), suspended solids (SS), total Kjeldhal nitrogen (TKN) and total phosphorus (TP). Multiple linear regression equations were initially constructed upon logarithmically transformed data. Input variables were primarily selected using a stepwise regression approach, combined with process knowledge. Variables found significant in the regression models were then used to construct ANN models. Other important network parameters such as learning rate, momentum and the number of hidden nodes were optimized using a trial and error approach. The final ANN models were then compared with the multiple linear regression models. In summary, ANN models were generally less accurate than the regression models and more time consuming to construct. This infers that ANN models are not more applicable than regression models when predicting urban stormwater quality.     

水资源缺乏地区地表水环境承载现状研究——以京津冀和西北五省(自治区)为例

本研究以主体功能区划作为控制单元进行划分,以水功能区纳污能力作为环境容量基础数据,结合国家环境保护部污染物排放统计数据,分析京津冀和西北五省(自治区)的不同主体功能区的地表水环境容量超载情况。结果显示,在水资源缺乏的京津冀和西北五省(自治区)地区,其重点开发区的氨氮排放入河量均已超出水环境容量,城镇生活污水排放是水环境氨氮容量超载的主要贡献因子。对于农产品主产区和重点生态功能区,京津冀地区水环境的化学需氧量(COD)和氨氮排放量普遍超载,而西北五省(自治区)还有19%~73%的水环境容量剩余。不同主体功能区的环境和产业政策取决于主体功能区的类型和水环境容量的超载情况。