Optimization of bioleaching low-grade copper-molybdenum ore by response surface methodology

The process conditions of bioleaching low-grade copper-molybdenum ore were optimized via response surface methodology(RSM). Firstly, leaching temperature, pulp concentration and ferrous sulfate quantity were regarded as independent variables, leaching efficiencies of Cu and Mo were set as the dependent variables, and a scheme consisting of 17 experiments was designed. Secondly, via multiple regressions fitting analysis of experimental results, the quadratic polynomial regression models characterizing effect of factors, such as leaching temperature, pulp density and ferrous sulfate quantity, and their interactions on Cu and Mo leaching efficiencies were established. Finally, quadratic multinomial regression models were used to optimize bioleaching process. The results show that regression models have high reliability and simulation accuracy, and there are no other uncontrolled and non-negligible influence factors. Moreover, there is a favorable fitting degree between the experimental and predicted leaching efficiencies and the experimental error is very small. Regression models can represent the interrelationship among these variables. Three factors have significant effects on the leaching efficiencies of Cu and Mo, and the leaching temperature has the most significant effect on the leaching efficiencies of Cu and Mo, followed by pulp concentration and ferrous sulfate quantity. The optimum conditions of bioleaching low-grade copper-molybdenum ore are as follow: leaching temperature is 36 ℃, pulp density is 9.5% and ferrous sulfate quantity is 6.0 g. Under these optimum process conditions, average leaching efficiencies of Cu and Mo are 83.82% and 64.78%, respectively, which are basically consistent with the model predictive values of 84.03% and 65.33%. Thus, the optimization of low-grade copper-molybdenum ore bioleaching process by RSM is feasible. © 2021, Central South University Press. All right reserved.