Research on the Forecast Model of the Boron Removal from Metallurgical Grade Silicon by Slag Refining Based on GA-BP Neural Network

- Organization:
- The Minerals, Metals and Materials Society
- Pages:
- 8
- File Size:
- 81 KB
- Publication Date:
- Jan 1, 2014
Abstract
"A purification process was developed to removal impurity element boron from metallurgical grade silicon by electromagnetic induction slag melting. Vacuum melting furnace was used to purify boron in both Al2O3-MgO-CaO-SiO2 slag system and Al2O3-CaO-SiO2 slag system. The relationship between different slag chemistry and the removal of boron in silicon were studied using Back Propagation (BP) Neural Network model. The best slag chemistry for the removal of boron was predicted by Genetic Algorithm (GA) contributed by the use of Matlab. The results show that the mass fraction of Boron in silicon is reduced from 11.7496×10-6 to 2.3259×10-6 after slag melting in 28.96%Al2O3-3.43%MgO-36.24%CaO-31.37%SiO2 slag system. The relative error obtained with GA-BP Neural Network model was below 0.35%.IntroductionSolar energy, due to its low green house gas emissions, has been paid great attention. Accordingly, the demand for solar grade silicon (SoG-Si) has been growing rapidly. The quest for developing a low-cost method of producing SoG-Si has been moving forward in the last decade. Refining of metallurgical-grade silicon (MG-Si) attracts research interest due to its low material and energy costs, and more environmentally friendly technology in comparison to the traditional Simens process. As such, impurity elements in MG-Si must be removed to low levels for the photovoltaics (PV) cell to operate at optimum efficiency. Most impurities in metallurgical-grade silicon (MG-Si), especially metal elements, can be separated by directional solidification and the zone refining plasma-arc method [1, 2]. The main focus in refining MG-Si to SoG-Si is on the impurities which are the most difficult to remove. Boron has relatively high segregation coefficients (KB=0.8, concentration of Boron in solid silicon divided by its concentration in liquid silicon) [3] and higher vapor tension (the saturated vapor pressure of boron and silicon are 6.78×10-7 Pa and 0.4 Pa, respectively). The vacuum melting and directional solidification methods hence have no effects on boron removal.Slag refining involves melting MG-Si in the presence of a flux to produce a slag phase that can take up the impurity elements. The mechanism of slag refining is considered to include two main steps: the oxidation of boron and the absorption of boron oxide by slag materials. The oxidation of boron, described by the oxygen potential (PO2), resulting from the equilibrium Si and SiO2. The absorption of boron oxide, described as the slag basicity, is interpreted as expected to facilitate their extraction to alkali and alkali-earth oxides in the slag phase. Thus, effective removal may be obtained for a certain slag composition. Researchers [4-5] examined the effect of boron removal in CaO-SiO2 based ternary systems and showed that the addition of excess CaO can decrease the activity of SiO2. Researchers [6-8] studied the boron behaviors in CaO-SiO2-Al2O3, CaO-SiO2-Na2O, Al2O3-BaO-SiO2, CaO-SiO2-Li2O and Al2O3-CaO-MgO-SiO2 slag systems by adding boron in the silicon to a degree. Li2O, Na2O, MgO and BaO are thought to be associated with B2O3."
Citation
APA:
(2014) Research on the Forecast Model of the Boron Removal from Metallurgical Grade Silicon by Slag Refining Based on GA-BP Neural NetworkMLA: Research on the Forecast Model of the Boron Removal from Metallurgical Grade Silicon by Slag Refining Based on GA-BP Neural Network. The Minerals, Metals and Materials Society, 2014.