Abstract

Multivariate models are a useful tool when studying the effects of independent variables on one or more dependent variables, since this approach allows modeling of the dynamics of complex systems based on simple analytical models with considerable certainty. Due to the decrease in the copper oxide mineral grades, leaching of copper sulfide minerals (secondary sulfides) has positioned itself as a benchmark of operation for the Chilean mining industry. The present work proposes the study of the effects of sulfuric acid, chloride concentration and time on the extraction of copper from sulfuric minerals (chalcocite), considering an experimental design, the surface optimization methodology and the adjustment of a quadratic model. The experimental data were adjusted by multiple regression analysis and were statistically analyzed. A model was developed to represent the copper extraction from the Cu2S mineral as a function of the statistically significant variables (chloride concentration and time) that contribute to explain the variation of the response variable under the set of parameters sampled.