Water-dispersible silicon nanoparticles (Si-NPs) are desirable for applications in biological techniques. A simplified method to synthesize such particles is reported here. The resulting Si-NPs are water-dispersible and luminescent. Under the excitation of UV light, the Si-NPs emit strong red light with a peak maximum at 606 nm and a quantum yield of 6%. They are highly stable, and remain so over several weeks. Fourier Transform Infrared (FTIR) spectroscopy shows a visible Si–CH2 scissoring vibration mode. Furthermore, the surface chemical bondings were confirmed by X-ray photoelectron spectroscopy (XPS). In the Si2p and C1s core levels, Si–C components are observed. The diameters of the synthesized Si-NPS as measured by atomic force microscope (AFM) are approximately 5 nm. Furthermore, the nanoparticles can be taken up by cultured cells. Fluorescence images of Si-NPs within MCF-7 human breast cancer cells show they are distributed throughout the cell tissue
The steel strip is an essential raw material in the machinery industry. Besides, the surface defects of the steel strip directly determine its performance. To achieve rapid and effective detection of the defects, a CP-YOLOv3-dense (classification priority YOLOv3 DenseNet) neural network was proposed in the present study. The model used YOLOv3 as basic network, implemented priority classification on the images, and then replaced the two residual network modules with two dense network modules. Therefore, the network can receive the multi-layer convolution features output by the dense connection block before making predictions, consequently enhancing the reuse and fusion of features. Finally, the six kinds of surface defects were detected by the improved network. According to the results, the detection precision of the CP-YOLOv3-dense network is 85.7%, the recall rate is 82.3%, the mean average precision is 82.73%, and the detection time of each image is 9.68 ms.
In view of the existing problems of complexity of process parameters and the difficulty in determining the optimal process in the field of 3D printing, polylactic acid (PLA) samples were prepared by fused deposition modeling (FDM). Orthogonal experiments were designed with 3D printing parameters (layer height, filling density and printing speed) as factors. The effects of layer height, filling density and printing speed on the tensile and compressive properties of PLA were studied. When layer height is 0.15 mm, the filling density is 100%, and the printing speed is 30 mm/s, the sample has the best comprehensive mechanical properties.
The inclusions in molten aluminum were removed using the deep filtration of ceramic foam filters and ceramic particles with active coatings. The results of tensile tests showed that the elongation of the filtered tensile specimen S 6 increases by 17.93 pct, but the tensile strength does not. The scanning electron microscope (SEM) examination showed that the secondary cracks and dimples in the filtered tensile specimen S 6 were finer and more homogeneous than those in the unfiltered tensile specimen S 0 . In addition, metallographic examination showed that there were only a few inclusions of approximately 6 mm in diameter in the filtered specimen S 6 , but more inclusions of approximately 40 mm in diameter were found in the unfiltered specimen S 0 . The filtration efficiency of the coated ceramic particles was higher than that of the coated ceramic foam filters. The active coating could effectively capture the inclusions and dissolve Al 2 O 3 in them during filtration.
The variation of substrate concentration in anode chamber directly affects the power generation efficiency and decontamination performance of microbial fuel cell (MFC). In this study, three concentrations of swine wastewater with 800 mg/L, 1600 mg/L and 2500 mg/L were selected as substrates, and the performance of MFC and response characteristics of anode microbial community were investigated. The results show that the concentration of a selected substrate is positively correlated with the output voltage of MFC and chemical oxygen demand (COD) removal rate. The microbial community diversity in the anode chamber and the performance of battery can be significantly affected when concentration changes in different ways, which helps to selectively cultivate the adaptable dominant bacteria to enhance the stability and decontamination performance of MFC. The community structure of anodic biofilm is mainly composed of Proteobacteria, Bacteroidetes, Firmicutes, Chloroflexi and Spirochaetae. These findings are meaningful to improve the treatment effects of swine wastewater and can help to find out the mechanism of varying concentration that influences the production of microorganisms in MFC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.