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.

准确量化次生和原生硫化物矿物对于资源评估、矿石加工和采矿作业的长期可持续性至关重要。除了可视化绘图和自动矿物量化之外，还可以利用化学分析来表征矿床的矿物学特征。通过评估某些矿物可以从其他矿物中选择性溶解的条件，化学评估可以提供低丰度矿物的地球化学形态数据，例如存在于低品位铜矿石中的铜/硫化铁。然而，硫化铜矿物的选择性溶解尚未得到充分研究。在这里，我们评估使用潜在的选择性溶解条件来区分表生硫化铜和下生硫化铜。通过表征黄铜矿、铜铜矿、斑铜矿、磷灰石、黄铜矿和黄铁矿精矿的溶解动力学，我们发现碱性氰化（而不是过氧化氢或在氧化剂存在下的酸浸）选择性地溶解表生硫化铜，可以应用在连续提取方案中估计尾矿样品的硫化物矿物学。氰化物在 5-15 分钟内完全溶解辉铜矿和铜钴矿，而在酸性氧化介质中溶解仅部分溶解硫化铜。黄铁矿、黄铜矿、磷灰石和斑铜矿在 0.5% KCN (1 mg/mL) 浸出 10 分钟下分别显示大约 1、10、30 和 40% 的铜回收率。氰化物浸出在智利拉安迪纳 Piuquenes 蓄水池中连续提取斑岩铜尾矿样品中的应用，与先前提出的过氧化氢溶解方法相比，改善了次生硫化物的选择性溶解，从而使其与原生硫化物矿物区分开来。通过氰化选择性浸出表生硫化物提供了一种廉价而有效的方法来估计铜矿石中的硫化铜矿物学，促进采矿作业的可持续性和资源评估。