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For the investigation on some hydrate dissociation behaviors at different ambient conditions, methane hydrates formed inside porous media with different saturations were dissociated by depressurizations. Plots of the instantaneous flow rate of gas as dissociation versus production pressure as well as deformation of experimental sample versus accumulative amount of released gas were drawn. These two lines slopes are, respectively, characterized as gas discharge resistance and reciprocal of the latter one as damage degree of experimental samples. The results show that these formed hydrates at higher ambient conditions, that is, temperature and pressure, and possess a higher saturation, which is beneficial to discharge gas and to keep experimental samples undamaged. And the nonuniformity of dissociation processes at different layer positions induced by depressurization is inhibited significantly, especially while combining extra heating. Hydrate saturation dominates the total volume loss of these samples under loadings. These conclusions can provide reference for the prediction in gas discharge capability and media damage degree as hydrate dissociation at different experimental and natural ambient conditions.

Abstract Cu2BaSn(S,Se)4 (CBTSSe) solar cells are emerging photovoltaic devices due to their high theoretical efficiencies of ~31%, environment-friendly and earth-abundant composition, low density of non-recombination defects, and so on. However, the record efficiency of CBTSSe solar cell is only 5.2%, showing the importance of studying their performance via numerical analysis to further enhance their practical efficiencies. In this paper, the effect of absorber and buffer layers on performances of Cu2BaSnS4 (CBTS) solar cells are firstly systematically studied via the SCAPS-1D software to provide a platform for the study of the effect of MoS2 interlayer on the performances of CBTS solar cells. The highest PCE of CBTS solar cell with a 30 nm CdS buffer layer is 11.87%. The PCE of CBTS solar cell with a 0.8 μm CBTS absorb layer is 12.51%, indicating that the CBTS solar cell is a potential low-cost solar cell due to its large optical absorption coefficient (α > 104 cm−1). The efficiency of CBTS solar cell is improved to 16.47% when the carrier concentration of CBTS is 1016 cm−3. The relationship between the performance of solar cell and the band gap, thickness, donor concentration, acceptor concentration of MoS2 interlayer is systematically investigated on the basis of the optimized efficiency. It is found that MoS2 interlayer plays an important role in the performance of CBTS solar cell. The p-type MoS2 has a beneficial effect on the efficiency improvement while the n-type MoS2 has a negative effect on the efficiency enhancement. The highest PCE of CBTS solar cell is as high as 18.28% when the thickness and the acceptor concentration of MoS2 are 4 nm and 1019 cm−3, respectively. Our simulation result provides a promising research direction to further improve the actual efficiency of the CBTS solar cell.

The Geza arc is an important part of the Sanjiang tectono-magmatic belt and is a newly discovered copper polymetallic ore concentration area in northwest Yunnan province, Southwest China. The area comprises numerous metal ore deposits, including one super-large deposit, three large deposits, etc. The formation of these deposits was closely related to intermediate–acidic magmatic intrusions. Based on previous studies, the “big data” analysis technique was used for a comparative study of large geochemical datasets of granite related to ore-formation in the Geza porphyry copper deposit and global adakites. As a result, 1313 element combinations and 127,765 overlap ratios were obtained. The results show that the Geza porphyry has similar geochemical characteristics to global adakites (the ratios of REE and Ga to major elements are in the range of global adakites). However, the Cu, Mo, and Zn contents of the porphyry are significantly higher than those of global adakites, and the porphyry may, therefore, represent an end-member of the global range of adakite composition. In addition, the geochemistry of adakites associated with the porphyry copper deposits overlaps in part with that of global adakites, although most of the data lie outside of the range of global adakites (i.e. low Mn/Cu, Sr/Cu, Na/Cu, and Zr/Cu values, and high Th/Cu, Ba/Cu, Na/Mo, Rb/Mo, Th/Mo, Ta/Mo, Ba/Mo, Mn/Zn, and Ba/Zn values). The samples with characteristics that deviate significantly from the geochemistry of global adakites show more advanced mineralization and alteration, and a stronger relationship with Cu and Mo mineralization. The results of geochemical data mining can be used as a prospecting indicator, and provide a new scientific basis for geological prospecting of the deep levels and periphery of the Geza Cu polymetallic ore belt.

This paper reports a facile method to prepare a textured surface with combined micron- and nano-scale surface features, which is used as master for nano-imprinting process to obtain transparent front electrodes in thin-film silicon tandem cells. The micron- and nano-scale surface features of the master are formed by combination of SiO2 sphere pre-deposition and ZnO textured growth. The master exhibits an averaged total transmittance value of 89.7% and an averaged haze value of 54.1% for the wavelength from 380 to 1100 urn. Comparing to the flat reference cell, the thin-film Si tandem cell deposited on the superstrate prepared using this master shows substantial decrease in reflectance at long wavelengths and drastic gain in the photocurrent of the bottom cell, the maximum summed current is enhanced by 35.5%, and the convert efficiency is improved from 8% to 10.0 +/- 0.3%. (C) 2015 Elsevier Ltd. All rights reserved.

Wind power, as one of the primary clean energies, is an important way to achieve the goals of carbon peak and carbon neutrality. Therefore, high-resolution measurement and accurate forecasting of wind speed are very important in the organization and dispatching of the wind farm. In this study, several methodologies, including the mesoscale WRF (Weather Research and Forecasting(WRF) model, mathematical statistics algorithms, and machine learning algorithms, were adopted to systematically explore the predictability and optimization of wind speed of a Gobi grassland wind farm located in western Inner Mongolia. Results show that the rear-row turbines were significantly affected by upwind turbine wakes. The output power of upwind-group turbines was 591 KW with an average wind speed of 7.66 m/s, followed by 532 KW and 7.02 m/s in the middle group and 519 KW and 6.92 m/s in the downwind group. The higher the wind speed was, the more significantly the wake effect was presented. Intercomparison between observations and WRF simulations showed an average deviation of 3.73 m/s. Two postprocessing methods of bilinear interpolation and nearest replacement could effectively reduce the errors by 34.85% and 36.19%, respectively, with average deviations of 2.43 m/s and 2.38 m/s. A cycle correction algorithm named Average Variance–Trend (AVT) can further optimize the errors to 2.14 m/s and 2.13 m/s. In another aspect, the categorical boosting (CatBoost) artificial intelligence algorithm also showed a great performance in improving the accuracy of WRF outputs, and the four-day average deviation of 26–29 September decreased from 3.21 m/s to around 2.50 m/s. However, because of the influence of large-scale circulations, there still exist large errors in the results of various correction algorithms. It is therefore suggested through the investigation that data assimilation of the northwest and Mongolian plateau, boundary layer parameterization scheme optimization, and embedding of high-resolution topographic data could have great potential for obtaining more accurate forecasting products.

Unsteady flow structures unrelated to rotating frequency in the turbine wheel space cavity has been observed and reported in a number of recent rim sealing investigations. These flow structures are relatively large in scale and have a significant influence on the sealing effectiveness prediction. As a result, it is important to capture these flow structures in numerical simulation. Small computation sectors, due to the circumferential symmetry assumption, have been proved to fail to capture these flow structures. This paper aims to find a minimum computation sector size that can capture these flow structures, at the same time save computation resources and shorten the convergence process for a simple axial rim seal. Four different sector model (10, 20, 30, 180-degree) are set into simulation using RANS and URANS method. The steady and unsteady simulation results are compared. By comparison, the 20-degree sector model is considered appropriate to conduct successive investigations. Then the 20-degree model is set into unsteady simulation under four different sealing flow rates cw=0(non-sealing flow case), cw=2500, cw=5000, cw=10000). It was found that due to the large-scale flow structure, a staggering pressure distribution is found in the cavity. Increasing the sealing flow rate diminishes these structures and stabilizes the flow in the wheel space cavity. The staggering pressure distribution causes the sealing effectiveness to show an abnormal variation trend. Unsteady pressure oscillation waves at two different circumferential positions are subjected to cross-correlation analysis, by which the rotating speed and number of the flow structure could be calculated.

An object-oriented white box design procedure of thermoelectric power generators is proposed based on a system level analysis.