The polymeric solution-sol-gel (SSG) process has been greatly improved by combination of the high homogeneity of SSG and the high efficiency of combustion synthesis to manufacture BiPbSrCaCuO powder with high homogeneity, ultrafine particles and low carbon content for fabrication of high-J c silver-sheathed bismuth-based 2223 superconducting tape. The improved SSG, termed solution-sol-gel-SHS (SSGS), is realized by ignition of homogeneous wet gel derived from polymeric SSG. X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infared spectroscopy (FTIR) are used to optimize the SSG process and investigate the mechanism of the SSG transition.
When seeds are treated with a high-voltage electric field (HVEF) to improve seed vigor, due to the large differences in the biological electromagnetic effects on different types of seeds, the methods of variance analysis and regression analysis based on data statistics are generally used to construct the optimal electric field dose prediction model; however, the generalization performance of the prediction model tends to be poor. To solve this problem, the electric intensity, frequency and treatment time were taken as the input variables for hybrid support vector regression (SVR) analysis to establish the prediction model of the seed comprehensive germination index. The whale optimization algorithm (WOA) was used to optimize the kernel parameters of the SVR. The optimized hybrid WOA–SVR model predicted the optimal comprehensive germination index of aged cotton (Gossypium spp.) seeds to be 329, the optimal HVEF dosage was 3.64 kV/cm × 99 s, and the frequency was 1.4 Hz. The aged cotton seeds were treated with the optimal HVEF and the germination test was carried out. Compared with the check (CK), the comprehensive germination index of seeds increased by 48%. The research results provided a new method and new idea for the optimal design of parameters for seed treatment with HVEF.
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