Abstract
Accurate quantification of secondary and primary sulfide minerals is fundamental for resource evaluation, ore processing, and long-term sustainability of mining operations. In addition to visual mapping and automated mineral quantification, chemical analysis can also be harnessed to characterize the mineralogy of ore deposits. By evaluating the conditions in which certain minerals can be selectively dissolved from others, a chemical evaluation could provide geochemical speciation data of low-abundance minerals, such as copper/iron sulfides present in low-grade copper ores. The selective dissolution of copper sulfide minerals is, however, understudied. Here, we evaluate the use of potential selective dissolution conditions to differentiate supergene copper sulfides from hypogene copper sulfides. By characterizing the dissolution kinetics of chalcocite, covellite, bornite, enargite, chalcopyrite, and pyrite concentrates, we found that alkaline cyanidation (and not hydrogen peroxide or acid leaching in the presence of oxidizing agents) selectively dissolves supergene copper sulfides, which can be applied in a sequential extraction scheme to estimate the sulfide mineralogy of tailings samples. Cyanide completely dissolved chalcocite and covellite within 5–15 min, whereas dissolution in acid oxidative media only partially dissolved copper sulfides. Pyrite, chalcopyrite, enargite, and bornite under 0.5% KCN leaching (1 mg/mL) for 10 min showed approximately 1, 10, 30, and 40% of copper recovery, respectively. Cyanide leaching applied in sequential extractions of porphyry copper tailings samples from the Piuquenes impoundment, La Andina, Chile, improved the selective dissolution of secondary sulfides compared to a previously proposed hydrogen peroxide dissolution method, thus allowing their differentiation from primary sulfide minerals. The selective leaching of supergene sulfides by cyanidation provides a cheap and efficient method to estimate the copper sulfide mineralogy in copper ores, facilitating the sustainability and resource evaluation of mining operations.
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