Maifanite is a nature medicinal stone used in many fields for long time. Theresearch on it showed that there are many trace elements in maifanite. In this paper, 36 traceelements in maifanite were determined by outer ...Maifanite is a nature medicinal stone used in many fields for long time. Theresearch on it showed that there are many trace elements in maifanite. In this paper, 36 traceelements in maifanite were determined by outer cover electrode atomic emission spectrometry, and thedetermination conditions were studied systematically. The results show that the concentrations ofelements, which are beneficial to human health, are higher, and the elements harmful to peoplehealth such as As, Cd, Hg, Cr, and Pb are tiny in maifanite. The precision and the accuracy werealso discussed.展开更多
Conditions of gallium plating of metal electrodes were studied in the paper. It was found that stability of gallium cover depends on the material and is increasing in the raw: stainless steel 08Х18Н12Т < Steel 1...Conditions of gallium plating of metal electrodes were studied in the paper. It was found that stability of gallium cover depends on the material and is increasing in the raw: stainless steel 08Х18Н12Т < Steel 1, Steel 2, Steel 3, Steel 45 < Ni < Cd < Cu. Phase composition of the electrode surface layer obtained after gallium plating was studied. It was found that gallium with nickel form Ga36Ni64(Ga Ni2) compound and gallium with copper form CuGa2compound. Different acids were used for electrode leaching: H2SO4;HNO3;H3PO4;HCI. It was shown that only hydrochloric acid is suit-able for gallium plating of the electrodes.展开更多
In order to improve the mechanical properties of deposited metal of ilmenite type welding electrode, CeO2/La rare earth elements were added into electrodes based on E4301 electrode, then electrodes were produced, test...In order to improve the mechanical properties of deposited metal of ilmenite type welding electrode, CeO2/La rare earth elements were added into electrodes based on E4301 electrode, then electrodes were produced, test plates were welded, and mechanical properties were tested based on National Standards of China. For the sake of solving the problems of large amount of mechanical properties tests, long test cycle and high test cost during the conventional production process of electrode, a prediction model of the mechanical properties of deposited metal based on Takagi-Sugeno （T-S） fuzzy neural network was established. Mn, Si and C contents of medium manganese in electrode, CeO2, and La contents of electrode and welding speed were selected as input variables of the prediction model, and the tensile strength, lower yield strength, elongation, impact energy and hardness of de- posited metal were selected as output variables. Finally, predicting experiment was done under test samples, and results show that average relative prediction error of the tensile strength, lower yield strength, elongation and hardness are 0.91%, 2.57 %, 4.94 % and 1.94 %, respec- tively, which reach the need of actual production. The re- sults of prediction show that the mechanical properties of deposited metal of electrode containing rare earth can be forecasted accurately through material composition of electrode and welding parameters based on T-S fuzzy neural network model.展开更多
文摘Maifanite is a nature medicinal stone used in many fields for long time. Theresearch on it showed that there are many trace elements in maifanite. In this paper, 36 traceelements in maifanite were determined by outer cover electrode atomic emission spectrometry, and thedetermination conditions were studied systematically. The results show that the concentrations ofelements, which are beneficial to human health, are higher, and the elements harmful to peoplehealth such as As, Cd, Hg, Cr, and Pb are tiny in maifanite. The precision and the accuracy werealso discussed.
文摘Conditions of gallium plating of metal electrodes were studied in the paper. It was found that stability of gallium cover depends on the material and is increasing in the raw: stainless steel 08Х18Н12Т < Steel 1, Steel 2, Steel 3, Steel 45 < Ni < Cd < Cu. Phase composition of the electrode surface layer obtained after gallium plating was studied. It was found that gallium with nickel form Ga36Ni64(Ga Ni2) compound and gallium with copper form CuGa2compound. Different acids were used for electrode leaching: H2SO4;HNO3;H3PO4;HCI. It was shown that only hydrochloric acid is suit-able for gallium plating of the electrodes.
基金financially supported by the National Natural Science Foundation of China (No.51305178)Xuzhou City Science and Technology Plan Project (No. XC12A013)the Research and Innovation Key Project of Graduate of Jiangsu Normal University (No. 2013YZD016)
文摘In order to improve the mechanical properties of deposited metal of ilmenite type welding electrode, CeO2/La rare earth elements were added into electrodes based on E4301 electrode, then electrodes were produced, test plates were welded, and mechanical properties were tested based on National Standards of China. For the sake of solving the problems of large amount of mechanical properties tests, long test cycle and high test cost during the conventional production process of electrode, a prediction model of the mechanical properties of deposited metal based on Takagi-Sugeno （T-S） fuzzy neural network was established. Mn, Si and C contents of medium manganese in electrode, CeO2, and La contents of electrode and welding speed were selected as input variables of the prediction model, and the tensile strength, lower yield strength, elongation, impact energy and hardness of de- posited metal were selected as output variables. Finally, predicting experiment was done under test samples, and results show that average relative prediction error of the tensile strength, lower yield strength, elongation and hardness are 0.91%, 2.57 %, 4.94 % and 1.94 %, respec- tively, which reach the need of actual production. The re- sults of prediction show that the mechanical properties of deposited metal of electrode containing rare earth can be forecasted accurately through material composition of electrode and welding parameters based on T-S fuzzy neural network model.
