Abstract

Multivariate models are a useful tool when studying the effect of explanatory variables on one or more explained variables, since it allows modeling the dynamics of complex systems based on simple analytical models with considerable certainty. Then, due to the drop in copper oxide ores grades, the leaching of copper sulphide minerals (secondary sulphides) has positioned itself as the benchmark of operation for the Chilean mining industry. Considering the above, the present work proposes the study of the effects of sulfuric acid, chlorine concentration and time on the extraction of copper from sulphured minerals (chalcocite), considering an experimental design, the surface optimization methodology and the adjustment of a quadratic model. The experimental data of leaching process were adjusted through a multiple regression analysis and were statistically analyzed. An analytical model was developed to represent the Cu extraction from Cu2S with the statistically significant variables (chloride concentration and time) that explain the variability of the adjusted model under the set of parameters sampled.