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.
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