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Optimization of manganese-rich slag extraction from low-manganese ore smelting by response surface methodology

作     者:Shuang-ping Yang Jiang-han Li Wen-bing Gao Hai-jin Liu Shuang-ping Yang;Jiang-han Li;Wen-bing Gao;Hai-jin Liu

作者机构:College of Metallurgical EngineeringXi’an University of Architecture and TechnologyXi’an710055ShaanxiChina 

出 版 物:《Journal of Iron and Steel Research(International)》 (钢铁研究学报(英文版))

年 卷 期:2022年第29卷第10期

页      面:1573-1582页

核心收录:

学科分类:080602[工学-钢铁冶金] 0709[理学-地质学] 0819[工学-矿业工程] 08[工学] 0806[工学-冶金工程] 0703[理学-化学] 

主  题:Low-manganese high-iron ore Manganese-rich slag Response surface methodology Manganese recovery 

摘      要:Manganese-rich slag is a raw material for smelting silicon–manganese alloys using an electric furnace.The blast furnace method is the main method for smelting manganese-rich slag.This method has the problems of a long process,large coke consumption,and easy volatilization of metals such as lead and zinc,which affects smelting safety.A new technology for smelting manganese-rich slag with low-manganese high-iron ore by smelting reduction optimization was proposed.This technology has the advantages of a short process,low energy consumption,low carbon emissions,and comprehensive recycling of lead,zinc,and other metals.According to the chemical composition,X-ray diffraction analysis,and particle size analysis of Cote d’Ivoire low-manganese ore,an experiment was carried out on manganese-rich slag by reduction–smelting separation.Combined with the design scheme of the Box–Behnken principle,three experimental factors(temperature,basicity,and carbon content)were selected as the influences to study.The influence that each factor has on the recovery rate of manganese was studied by response surface methodology,and the experimental factors were optimized.The results show that under the conditions of a reduction-smelting temperature of 1402℃,basicity of R=0.10,and carbon content of 10 mass%,the recovery rate of manganese is 97%.A verification experiment was carried out under the optimal conditions,and the error was only 1.24%;this proves that the response surface method prediction model is reliable and accurate.This is of great significance for the comprehensive utilization of lean-manganese ore resources.

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