Optimization of microwave-assisted roasting: Box-behnken design for oxidation of sulfide minerals and control of atmospheric sulfur in refractory gold ore pretreatment

Abdul Hapid , Siti Zullaikah , Mahfud Mahfud , Adji Kawigraha , Mifta Ulul Azmi , Irwan Haryanto , Haswi Purwandanu Soewoto , Alchris Woo Go , Suttichai Assabumrungrat
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Abstract

Response Surface Methodology and Box-Behnken Design have been applied to optimize microwave-assisted roasting of refractory gold ore. The roasting is used as a pretreatment for refractory gold ore to increase gold recovery during leaching. The roasting step consumes high energy and produces high sulfur emissions into the atmosphere. Optimization aims to obtain optimum roasting conditions with minimum energy consumption and sulfur emissions. The effects of microwave power (100–400W), NaClO3 composition (120–360 kg/tonne), water quantity (0–120 kg/tonne), and duration of roasting (5–30 minutes) have been investigated at the preliminary stage. In the optimization stage, three variables were studied with the roasting time fixed at 5 minutes. The optimum conditions for microwave-assisted roasting of refractory gold ore were achieved at 200W, NaClO3 of 200 kg/tonne ore, and water of 150 kg/tonne ore. Based on the optimization model, the predicted temperature and sulfur oxidation are 394 °C and 67.16 %, respectively. Model validation showed that the actual roasting temperature and sulfur oxidation are 404 °C and 67.28 %, respectively. The differences between the predicted and actual values of temperature and sulfur oxidation are 2.5 % and 0.18 %, respectively. With an accuracy surpassing 95 %, the optimization model is capable of predicting both temperature and sulfur oxidation.

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优化微波辅助焙烧:氧化硫化矿物和控制难处理金矿石预处理中的大气硫的箱式焙烧设计
微波辅助焙烧难处理金矿的优化采用了响应面方法和箱式贝肯设计。焙烧是难选金矿石的一种预处理方法,可在浸出过程中提高金的回收率。焙烧步骤能耗高,并向大气中排放大量硫磺。优化的目的是获得能耗和硫排放最小的最佳焙烧条件。初步阶段研究了微波功率(100-400W)、NaClO3 成分(120-360 公斤/吨)、水量(0-120 公斤/吨)和焙烧时间(5-30 分钟)的影响。在优化阶段,研究了三个变量,焙烧时间固定为 5 分钟。耐火金矿石微波辅助焙烧的最佳条件为 200 瓦、NaClO3 200 千克/吨矿石和水 150 千克/吨矿石。根据优化模型,预测温度和硫氧化率分别为 394 ℃ 和 67.16%。模型验证表明,实际焙烧温度和硫氧化度分别为 404 °C 和 67.28 %。温度和硫氧化的预测值与实际值之间的差异分别为 2.5 % 和 0.18 %。优化模型能够预测温度和硫氧化,准确率超过 95%。
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来源期刊
Case Studies in Chemical and Environmental Engineering
Case Studies in Chemical and Environmental Engineering Engineering-Engineering (miscellaneous)
CiteScore
9.20
自引率
0.00%
发文量
103
审稿时长
40 days
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