Aluminum dross (AD) is a waste product produced during aluminum processing and can be used to prepare mullite ceramic materials. However, the research on the preparation of mullite porous ceramics entirely from solid waste is still in the development stage. In this paper, porous mullite ceramics were successfully fabricated using a solid-phase sintering process with AD and different silicon sources (fly ash, silica dust, and gangue) as raw materials.
View Article and Find Full Text PDFIn this study, the hydrolysis behavior and kinetics of AlN in aluminum dross (AD) were investigated in order to better identify the steps controlling the AlN hydrolysis reaction and the factors influencing the hydrolysis rate to enhance the removal efficiency of AlN. The hydrolysis behavior of AlN, including AlN content, phase composition, chemical composition, microstructure, and element distribution, was determined by a leaching test, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and energy dispersive spectroscopy, respectively. The results showed that increasing the leaching liquid-solid ratio as well as the temperature was helpful for the removal efficiency of AlN.
View Article and Find Full Text PDFAiming at these problems of image colorization algorithms based on deep learning, such as color bleeding and insufficient color, this paper converts the study of image colorization to the optimization of image semantic segmentation, and proposes a fully automatic image colorization model based on semantic segmentation technology. Firstly, we use the encoder as the local feature extraction network and use VGG-16 as the global feature extraction network. These two parts do not interfere with each other, but they share the low-level feature.
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