响应面法优化微生物浸出低品位钼矿工艺条件
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摘要
从钼矿区矿坑水中分离得到自然混合菌种,经驯化培养,用于浸出陕西洛南低品位钼矿。以浸出液中钼的含量作为评判指标,在单因素试验的基础上,通过响应面法优化得出了最佳浸出条件为:初始p H值2.0、Fe2+浓度5.00 g/L、Fe3+浓度2.90 g/L,此条件下钼浸出率为73.87%,而相应的无菌化学浸出实验的钼浸出率仅为12.65%。拟合得到二次回归方程模型的相关系数为R2=0.991 1,P<0.000 1,说明回归效果很好,失拟项P=0.671 0>0.05,失拟不显著,误差小,可用该模型对钼的微生物浸出率进行分析和预测。
Naturally mixed strains were isolated from the pit water in a molybdenum ore mine and adopted in the leaching process of low-grade molybdenum ore from Shaanxi Province after cultivation. Based on the single-factor test,the bioleaching conditions were optimized by using response surface methodology( RSM) with the content of molybdenum in the leach liquid as an evaluating index,including an initial p H value of 2.0,Fe2+concentration at 5.00 g/L,Fe3+concentration at 2.90 g/L. It is shown that the Mo leaching rate reached 73. 87% on the optimum leaching conditions,while the Mo leaching rate without bacterial just around 12.65%. The correlation coefficient of the quadratic regression equation after fitting was obtained as follows: R2= 0. 991 1,P < 0. 000 1,indicating an excellent regression effect. It is also shown that the lack of fit P( P = 0.671 0 > 0.05) was not significant with small error. It is concluded that the bioleaching rate of molybdenum can be evaluated and predicted by this model.
Naturally mixed strains were isolated from the pit water in a molybdenum ore mine and adopted in the leaching process of low-grade molybdenum ore from Shaanxi Province after cultivation. Based on the single-factor test,the bioleaching conditions were optimized by using response surface methodology( RSM) with the content of molybdenum in the leach liquid as an evaluating index,including an initial p H value of 2.0,Fe2+concentration at 5.00 g/L,Fe3+concentration at 2.90 g/L. It is shown that the Mo leaching rate reached 73. 87% on the optimum leaching conditions,while the Mo leaching rate without bacterial just around 12.65%. The correlation coefficient of the quadratic regression equation after fitting was obtained as follows: R2= 0. 991 1,P < 0. 000 1,indicating an excellent regression effect. It is also shown that the lack of fit P( P = 0.671 0 > 0.05) was not significant with small error. It is concluded that the bioleaching rate of molybdenum can be evaluated and predicted by this model.
引文
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[15]Zamani M A A,Hiroyoshi N,Tsunekaw A M,et al.Bioleaching of sarheshmeh molybdenum concentrate for extraction of rhenium[J].Hydrometallurgy,2005,80(1-2):23-31.
[2]陈勃伟,温建康.生物冶金中混合菌的作用[J].金属矿山,2008(4):13-17.
[3]刘红昌,聂珍媛,马亚龙,等.金属硫化矿微生物作用过程中界面硫化学形态转化及硫活化机制研究[J].矿物岩石地球化学通报,2017,36(S):653-654.
[4]刘丽君,刘双江,姜成英.嗜热微生物及在高温生物冶金过程中的应用[J].微生物学通报,2016,43(5):1101-1112.
[5]刘海英,李崇德.某低品位钼矿浮选工艺研究[J].有色金属(选矿部分),2013(1):35-39.
[6]俞娟,杨洪英,陈燕杰,等.低品位钼精矿的钼提取研究[J].东北大学学报(自然科学版),2011,32(8):1141-1144.
[7]周根茂,曾毅君,孟舒.用碱法从低品位难选辉钼矿中浸出钼的试验研究[J].湿法冶金,2015,34(6):466-469.
[8]卢涛,魏德洲,沈岩柏,等.胶硫钼矿型难选钼矿的微生物浸出试验研究[J].中国矿业大学学报,2016,45(1):157-142.
[9]邹平,周兴龙,张文彬,等.低品位硫化铜矿生物柱浸过程细菌种群结构及演替规律[J].过程工程学报,2009,9(1):88-94.
[10]Yaghobi Moghaddam M,Shafaei S Z,Noaparast M,et al.Empirical model for bio-extraction of copper from low grade ore using response surface methodology[J].Transactions of Nonferrous Metals Society of China,2015,25(12):4126-4143.
[11]张婧,邹平,孙珮石,等.化学-生物联合浸出次生硫化铜精矿的研究[J].矿冶工程,2015,35(6):123-127.
[12]Abdollahi H,Shafaei S Z,Noaparast M,et al.Bio-dissolution of Cu,Mo and Re from molybdenite concentrate using mix mesophilic microorganism in shake flask[J].Transactions of Nonferrous Metals Society of China,2013,23(1):219-230.
[13]Kummer W,Gutknecht W,Olson J G,et al.Recovery of molybdenum from molybdenum bearing sulfide materials by bioleaching in the presence of iron.US Pat:8268037[P].2012-09-18.
[14]李宏喣,王淀佐.生物冶金中的微生物及其作用[J].有色金属,2003,55(2):58-63.
[15]Zamani M A A,Hiroyoshi N,Tsunekaw A M,et al.Bioleaching of sarheshmeh molybdenum concentrate for extraction of rhenium[J].Hydrometallurgy,2005,80(1-2):23-31.