The influence of Pr on thermal stability, microstructure, and magnetic properties of melt-spun (Nd1-xPrx)(10.5)(FeCoZr)(83.5)B-6(x = 0, 0.2, 0.4, 0.6, 0.8, 1.0) alloy was investigated. By sub-overquenching to get the ...The influence of Pr on thermal stability, microstructure, and magnetic properties of melt-spun (Nd1-xPrx)(10.5)(FeCoZr)(83.5)B-6(x = 0, 0.2, 0.4, 0.6, 0.8, 1.0) alloy was investigated. By sub-overquenching to get the mixture of amorphous and fine crystallites and post annealing under the optimum conditions, bonded magnets with the best magnetic properties were prepared. With the increase of Pr content, H-ci increases, but B-r decreases. (BH)(max) of magnets bonded with 3.25% (mass fraction) epoxy reaches the maximum of 70.6 kJ .m(-3) at x = 0.6 similar to 0.8. Substitution of Pr for Nd causes the crystallization temperature and crystallization energy to decrease. This thermal stability difference results in that (Nd0.8Pr0.8)(10.5)(FeCoZr)(83.5)B-6 alloy has a rougher and more inhomogeneous microstructure than that of (Nd(0.8)Pro(0.2))(10.5)(FeCoZr)(83.5)B-6 alloy, furthermore, leads to the decrease of B-r with the increase of Pr content.展开更多
For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fas...For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.展开更多
文摘The influence of Pr on thermal stability, microstructure, and magnetic properties of melt-spun (Nd1-xPrx)(10.5)(FeCoZr)(83.5)B-6(x = 0, 0.2, 0.4, 0.6, 0.8, 1.0) alloy was investigated. By sub-overquenching to get the mixture of amorphous and fine crystallites and post annealing under the optimum conditions, bonded magnets with the best magnetic properties were prepared. With the increase of Pr content, H-ci increases, but B-r decreases. (BH)(max) of magnets bonded with 3.25% (mass fraction) epoxy reaches the maximum of 70.6 kJ .m(-3) at x = 0.6 similar to 0.8. Substitution of Pr for Nd causes the crystallization temperature and crystallization energy to decrease. This thermal stability difference results in that (Nd0.8Pr0.8)(10.5)(FeCoZr)(83.5)B-6 alloy has a rougher and more inhomogeneous microstructure than that of (Nd(0.8)Pro(0.2))(10.5)(FeCoZr)(83.5)B-6 alloy, furthermore, leads to the decrease of B-r with the increase of Pr content.
基金Supported by the National Natural Science Foundation of China(51174091,61364013,61164013)Earlier Research Project of the State Key Development Program for Basic Research of China(2014CB360502)
文摘For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.
