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We investigate magnetron-sputtered In2(OxS1−x)3 compounds acting as an alternative buffer system to the solution-grown CdS or Zn(O,S) buffer layers in Cu(In,Ga)Se2 (CIGS) thin-film solar cells. The influence of the oxygen content on the solar cell performance, microstructure of the mixed systems, bandgap, and band offsets to CIGS is investigated experimentally and also characterized by calculations based on density functional theory. Samples in a series with different chemical compositions ranging from In2S3 to In2O3 are either directly deposited from ceramic targets or from a pure In2S3 target by reactive sputtering by adding O2 in the Ar sputtering gas. The binary compounds In2S3 and In2O3 sputtered at 220 °C substrate temperature from ceramic targets exhibit a crystalline structure, whereas the ternary In2(O,S)3 compounds are either nanocrystalline in the case of In2(O0.25S0.75)3 or amorphous for In2(O0.5S0.5)3 and In2(O0.75S0.25)3. For [O]/([O] + [S]) ratios above 0.25, the cell efficiencies decrease drastically, mainly due to lower open-circuit voltages (VOC). This behavior can be explained by an increase of the negative conduction band offset between the CIGS absorber and the oxygen-rich In2(OxS1−x)3 or In2O3 buffer, resulting in pronounced VOC losses. Adding oxygen to In2S3 with optical bandgap energies of around 2 eV results in a bowing of the values to below 2 eV and finally reaching values of around 2.7 eV for In2O3 if an indirect band transition is assumed. In summary, our results reveal that pronounced oxygen incorporation in In2S3 is not beneficial in terms of CIGS device efficiency because oxygen is electronically inactive and poorly miscible. [ABSTRACT FROM AUTHOR]

A good water ecological environment is crucial for the sustainable development and ecological civilization of China. However, various problems remain for China’s water ecological environment, including eutrophication, pollution of drinking water sources, contamination of groundwater and coastal waters, emerging pollutants, and shortage of ecological water. In this study, we analyzed the overall situation of the water ecological environment in China, pinpointed the major challenges, and proposed the strategic thinking and several basic principles. These principles focus on improving the water ecological environment and comprehensively consider water quality improvement, water ecological protection, and water environmental risk prevention and control. Three major scientific and technological projects were proposed pertaining to (1) coordinated governance and overall restoration of mountains, rivers, forests, fields, lakes, grasses, and sand in key basins, (2) overall improvement of water environment and water ecology in the Beijing-Tianjin-Hebei Collaborative Development Area, and (3) assurance of drinking water safety in the new era. Furthermore, we proposed the following four countermeasures: (1) revising the Environmental Quality Standards for Surface Water to strengthen its leading role in the construction of water ecological civilization in China; (2) evaluating the spatial and temporal differences of nitrogen and phosphorus nutrients in China’s lakes and implementing differentiated nutrients standards; (3) assessing the current status of water ecology in China and promoting water ecology monitoring and assessment; and (4) establishing an intelligent supervision platform for drinking water safety based on big data fusion.

Soft magnetic materials are a core element of power electronics and electrical machines. However, none of the soft magnetic materials is able to exploit the full potential of wide bandgap semiconductors, which operate above MHz frequency for efficient energy conversion in power electronic systems. Here, a high‐performance Fe–Si soft magnetic composites with a 2D ordered domain structure are reported, enabling efficient energy conversion at MHz frequencies. By transforming spherical particles into flakes and arranging them in layers, 2D magnetic domains are created within the composite. This leads to a 90% increase in permeability and a tenfold decrease in loss at 3 MHz compared to composite made with spherical particles. The significantly increased cut‐off frequency indicates that the ordered flaky particles are suitable for MHz applications, unlike the disordered spherical particles. These findings provide an effective approach for fabricating high performance soft magnetic composites from traditional spherical particles and miniaturizing magnetic devices for efficient power electronics operation. [ABSTRACT FROM AUTHOR]

We propose a spatiotemporal coupling deep neural network approach for time-resolved reconstruction of the velocity field around a circular cylinder. The neural network leverages two distinct data types: (1) non-time-resolved velocity field around the cylinder, consisting of fixed frequency sampling and variable frequency sampling velocity field, and (2) the time-resolved surface pressure sequence around the cylinder. The deep neural network comprises two sub-networks: a convolutional autoencoder (CAE) for nonlinear mode extraction and a Transformer for sequence-to-sequence learning. We refer to this architecture as CTNet (CAE-Transformer Network). The encoder in the CAE maps non-time-resolved velocity field to a latent vector, enabling the extraction of nonlinear modal coefficients. An appropriate time window length for the surface pressure sequence is then selected to establish a Transformer sequence learning model, using the chosen sequence as input to predict the corresponding nonlinear modal coefficients. Once the Transformer is well trained, the time-resolved nonlinear modal coefficients of velocity field can be achieved. Along with the well-trained decoder in the CAE, the time-resolved velocity field can be reconstructed from the output of the Transformer. We verify the performance of CTNet by a simulated dataset at a representative Reynolds number of 3900. The results show a relative reconstruction error of just 6.3% for the time-resolved velocity field, demonstrating high reliability in the reconstruction. We further compare the reconstructed velocity field obtained with and without the utilization of variable frequency sampling velocity field. Notably, the inclusion of variable frequency sampling velocity field significantly improves the reconstruction quality. [ABSTRACT FROM AUTHOR]