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In this paper, a new phononic crystal structure with periodic units consisting of four tungsten vibrators wrapped by silicone rubber coating is designed. The dispersion curve, vibration mode and transmission loss spectrum of the structure were calculated by finite-element method(FEM). The results show that the bandgap range of this structure is 18. 85 ~225. 28 Hz, which is consistent with the frequency attenuation range of transmission loss spectrum, and can effectively suppress the propagation of elastic waves of 20 ~200 Hz in phononic crystals. By analyzing the vibration mode corresponding to the point on the dispersion curve, the formation mechanism of the bandgap is explained. The influence of the notch angle of the phononic crystal plate and the longitudinal and transverse spacing between the phonons on the bandgap was discussed in this paper. The results show that as the notch angle decreases, the lower boundary of the bandgap remains almost unchanged, and the upper boundary of the bandgap rises, thus increasing the width of the bandgap. As the transverse or longitudinal spacing between the vibrators increases, the lower and upper boundaries of the bandgap rise, and the width of the bandgap increases, thus the bandgap of the phononic crystal model is optimized. At the same time, the notch design of the phononic crystal plate save the material and reduce the weight of the structure. [ABSTRACT FROM AUTHOR]

In the process of preparing silicon single crystal, the Czochralski method has problems such as multiple mechanism assumptions, unclear boundary conditions under multiple field couplings, interlaced and mutual influence of physical and chemical changes, which makes it impossible to establish an accurate mechanism model for silicon single crystal growth process control. To solve this problem, based on a large amount of crystal growth data in the single crystal furnace pulling workshop, this paper analyzes the characteristic parameters related to crystal diameter based on the maximum information coefficient (MIC) algorithm proposed by the mutual information theory. Then, based on the nonlinear autoregressive with exogeneous inputs (NARX) dynamic neural network, a multi-input, and single-output equal-diameter phase crystal diameter prediction model was established, the diameter prediction was also performed for the three single crystal furnace pulling data, and the average mean square error value of the prediction is 0.000774. Finally, the prediction model of crystal diameter in the equal diameter stage established based on the NARX dynamic neural network is compared with the prediction model of crystal diameter in the equal diameter stage established based on the back propagation (BP) neural network. The results of the comparative analysis verified the superiority of the NARX dynamic neural network model for predicting the crystal diameter in the isodiametric stage. The results show the NARX dynamic neural network provides a more accurate identification model for the control of crystal diameter. [ABSTRACT FROM AUTHOR]

In view of the difficulty of observing chip formation in flying cutting of single crystal germanium, a meshless simulation method（SPH method） is adopted in this study. The influence of cutting depth and cutting speed on cutting force and chip formation during plastic removal is studied by establishing a micro-cutting simulation model of single crystal germanium（111). The results show that when the cutting speed is 4 μm·μs-1 and the cutting depth is 0.5 μm, 1 μm, 2 μm and 5 μm, the tangential force and normal force gradually increase and then decrease to a gentle fluctuation trend. It is concluded that the larger the cutting depth is, the greater the stable fluctuation value of cutting force is, and the critical cutting depth for chip generation is between 0.5 μm and 1μm. When the cutting depth of single crystal germanium is 1 μm and the cutting speed is 2 μm·μs-1, 4 μm·μs-1, 6 μm·μs-1 and 8 μm·μs-1, it is found that the tangential force and normal force are not affected by the cutting speed, and the critical cutting speed for chip formation is between 2 μm·μs-1 and 4 μm·μs-1. [ABSTRACT FROM AUTHOR]

Ingot crystalline silicon is one of the important sources for solar-grade crystalline silicon materials. For reducing the cost of silicon wafers, it is necessary to develop large-size ingot crystalline silicon while ensuring the crystal quality. The core parameters that affect the quality of cast crystalline silicon include the ratio of crystal growth rate to temperature gradient at the solidification interface V/ G, wall heat flow q, height difference of solidification interface Δh, and temperature difference of silicon melt ΔT. Aiming at the quality control during the growth of ingot crystalline silicon, this study established a process control optimization method based on the artificial neural network (ANN) model for the crystal growth process. A process control data set for the growth process of ingot crystalline silicon was constructed based on the experimental measurement data and numerical simulation results. The opening of the bottom insulation cage and the power ratio of the side and top heaters were used as the main process control parameters, and V/ G, | q |, | Δh |, ΔT are the optimization goals. A neural network model for mapping the relationship between process control parameters and thermal field characteristics was established. The influence of the bottom heat insulation cage opening and the power ratio of the side to top heaters on the thermal field during the crystal growth process were analyzed using the trained neural network model. The process control parameters for the ingot crystalline silicon growth process are optimized using genetic algorithm (GA), improving the quality of grown crystal and reducing energy consumption. Finally based on the experimental test images, the influences of V/ G on the crystal quality were discussed. Research shows that V/ G in the middle stage of crystal growth changes smoothly along the horizontal direction, and the corresponding defects are less and evenly distributed. Therefore, increasing the uniformity of V/ G in the horizontal direction is also an important factor to improve the quality of crystal. [ABSTRACT FROM AUTHOR]

Groundwater in a many regions is an important support or supplement for ecological stability, the critical depth of recharge of surface vegetation by groundwater is critical to groundwater management and ecological security. Taking the West Liaohe Plain as an example, five results were concluded as follows: (1) The moisture movement structure in vadose zone was innovatively demarcated based on recharge of the vegetation by groundwater, and the mechanism and physical process of recharge of the vegetation by groundwater were described, and the critical depth of recharge of the vegetation by groundwater and related physical concepts were defined. (2) According to the physical mechanism of absorbing the phreatic evaporation by the root system of the vegetation, the phreatic water affected layer which is formed by the rise of the capillary water is the key to critical depth. (3) The rational formula of the soil effective pore size was deduced, and the porosity parameter was calculated based on crystal structure model of soil particles, which dissolved the precise calculation of the maximum height of capillary water. (4) The calculation model for critical depth of recharge of the vegetation by groundwater was built by thickness of the root system. (5) The results were confirmed by massive field surveys. The results of the study were timely applied in the Horqin Grassland. [ABSTRACT FROM AUTHOR]