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Clean energy is a major trend. The importance of photovoltaic power generation is also growing. Photovoltaic power generation is mainly affected by the weather. It is full of uncertainties. Previous work has relied chiefly on historical photovoltaics data for time series forecasts. However, unforeseen weather conditions can sometimes skew. Consequently, a spatial‐temporal‐meteorological‐long short‐term memory prediction model (STM‐LSTM) is proposed to compensate for the shortage of photovoltaic prediction models for uncertainties. This model can simultaneously process satellite image data, historical meteorological data, and historical power generation data. In this way, historical patterns and meteorological change information are extracted to improve the accuracy of photovoltaic prediction. STM‐LSTM processes raw satellite data to obtain cloud image data. It can extract cloud motion information using the dense optical flow method. First, the cloud images are processed to extract cloud position information. By adaptive attentive learning of images in different bands, a better representation for subsequent tasks can be obtained. Second, it is important to process historical meteorological data to learn meteorological change patterns. Last but not least, the historical photovoltaic power generation sequences are combined to obtain the final photovoltaic prediction results. After a series of experimental validation, the performance of the proposed STM‐LSTM model has a good improvement compared with the baseline model. [ABSTRACT FROM AUTHOR]

Si OCN ceramics are formed by the thermal decomposition of a polyvinylsilazane precursor in the presence of a dicumyl peroxide ( DP) thermal initiator with different concentrations. The Si OCN ceramics pyrolyzed at 1000°C with different concentrations of DP are characterized with X-ray diffraction, transmission electron microscope, electron paramagnetic resonance, and UV-visible spectroscopy. We find that the structure and optical band gap of the Si OCN ceramics can be changed by altering the concentration of DP. There is a critical concentration, at which the structural and optical behavior varied in different ways as a function of the concentration of DP. The detailed mechanism is discussed. [ABSTRACT FROM AUTHOR]

We report a facile route to synthesize Si CO nanospheres using Pluronic F127/polyvinylsilazane ( PVSZ) mixed micelles as a template, in which PVSZ selectively swells with the PEO core of the F127 micelles. The thermal degradation of the F127/ PVSZ mixed micelles leads to the formation of Si CO nanospheres. The size of the resultant Si CO nanospheres can be tuned in the range from 25 nm to 75 nm by controlling annealing time at 70°C. [ABSTRACT FROM AUTHOR]