Bairui Tao

Photoluminescence properties of ordered Bi4−xNdxTi3O12 matrix supported by 3-dimensional silicon microchannel plate

Ordered ferroelectric neodymium (Nd)-substituted bismuth titanate (Bi4−xNdxTi3O12) is fabricated on silicon microchannel plates (Si-MCPs). A significantly enhanced photoluminescence peak at about 890 nm (~1.4 eV) corresponding to the 4 f3 − 4 f3 forced electric dipole transition from the 4I9/2 ground state to different excited states of Nd3+ is observed. Moreover, the near-infrared emission intensity can be tuned by adjusting the Nd composition. The effects can be ascribed to the difference in the host lattice between the Nd-doped titanate with a simple perovskite structure and the result rendered by the regular cubic array of the Si-MCPs.

Nickel-Palladium Nanoparticles for Nonenzymatic Methanol Detection

Silicon microchannel plates (MCP) modified by nickel-palladium nanoparticles (Ni-Pd/Si-MCP) have highly ordered microchannels with uniform diameters and lengths isolated and parallel to one another and are excellent sensors for the determination of methanol in alkaline solutions. The 3D ordered Si MCP is fabricated by electrochemical etching used as the backbone, and the Ni-Pd nanoparticles are sensitive materials for detecting methanol that was obtained by an electroless plating method. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and electrochemical methods were employed to characterize the Ni-Pd/Si-MCP structure. An electrochemical workstation was used to monitor the sensing characteristics of the Ni-Pd/Si-MCP electrode. As a result of the synergetic effects rendered by the MCP and Ni-Pd nanoparticles, these sensors present a high sensitivity of 0.168 mA mM−1, and the detection limits was 12 μM. In particular, since the fabrication process is compatible with conventional silicon technology, the structure has immense potential as an efficient, nonenzymatic, and integrated methanol sensors.

Design of BP Speaker Recognition System Based on KPCA-MFCC Parameter Optimization

The recognition of the speaker through machine learning algorithm has become a hot spot of research. On the basis of speaker recognition based on BP and traditional MFCC characteristic parameters, the feature parameters of MFCC are reduced by KPCA algorithm, and the BP neural network algorithm is used as the back-end recognition model to classify the speaker. The improved algorithm is simulated on the MATLAB platform and compared with the traditional PCA algorithm. The experimental results show that the improved algorithm has a great improvement in recognition efficiency and recognition accuracy and has a good research value.

Nonenzymatic Alkaline Direct Glucose Fuel Cell With a Silicon Microchannel Plate Supported Electrocatalytic Electrode

Highly active Pd-Ni/Si microchannel plate (MCP) electrocatalytic electrode has been synthesized by combining conventional microelectronics technology with electrochemical techniques. The obtained Pd-Ni/Si-MCP electrocatalytic electrode was characterized by SEM, energy dispersive spectrometer (EDS), XRD, and electrochemical measurements. The results show that Pd-Ni/Si-MCP electrocatalytic electrode possesses better stability and higher activity in comparison with Pd-Ni/Si prepared by the same procedure. The high performance of the fuel cell is mainly attributed to the increased kinetics of both the glucose oxidation reaction and oxygen reduction reaction, rendered by a better electrocatalytic activity of Pd-Ni nanoparticles, ordered microchannels, and high surface-to-volume ratio of backbone Si-MCP. Especially, the compatibility of silicon microelectronics processing could achieve monolithic integration of Si-based microfabricated fuel cells. [DOI: 10.1115/1.4024605]