The Relation between Trace Element Composition of Cu-(Fe) Sulfides and Hydrothermal Alteration in a Porphyry Copper Deposit: Insights from the Chuquicamata Underground Mine, Chile
Bibliographic record
Abstract
Porphyry Cu-Mo deposits are among the world’s largest source of Cu, Mo, and Re, and are also an important source of other trace elements, such as Au and Ag. Despite the fact that chalcopyrite, bornite, and pyrite are the most common sulfides in this deposit type, their trace element content remains poorly constrained. In particular, little is known about minor and trace elements partitioning into Cu-(Fe) sulfides as a function of temperature and pH of the hydrothermal fluid. In this study, we report a comprehensive geochemical database of chalcopyrite, bornite, and pyrite in the super-giant Chuquicamata porphyry Cu-Mo deposit in northern Chile. The aim of our study, focused on the new Chuquicamata Underground mine, was to evaluate the trace element composition of each sulfide from the different hydrothermal alteration assemblages in the deposit. Our approach combines the electron microprobe analysis (EMPA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of sulfide minerals obtained from six representative drill cores that crosscut the chloritic (propylitic), background potassic, intense potassic, and quartz-sericite (phyllic) alteration zones. Microanalytical results show that chalcopyrite, bornite, and pyrite contain several trace elements, and the concentration varies significantly between hydrothermal alteration assemblages. Chalcopyrite, for example, is a host of Se (≤22,000 ppm), Pb (≤83.00 ppm), Sn (≤68.20 ppm), Ag (≤45.1 ppm), Bi (≤25.9 ppm), and In (≤22.8 ppm). Higher concentrations of Se, In, Pb, and Sn in chalcopyrite are related to the high temperature background potassic alteration, whereas lower concentrations of these elements are associated with the lower temperature alteration types: quartz-sericite and chloritic. Bornite, on the other hand, is only observed in the intense and background potassic alteration zones and is a significant host of Ag (≤752 ppm) and Bi (≤2960 ppm). Higher concentrations of Ag and Sn in bornite are associated with the intense potassic alteration, whereas lower concentrations of those two elements are observed in the background potassic alteration. Among all of the sulfide minerals analyzed, pyrite is the most significant host of trace elements, with significant concentrations of Co (≤1530 ppm), Ni (≤960 ppm), Cu (≤9700 ppm), and Ag (≤450 ppm). Co, Ni, Ag, and Cu concentration in pyrite vary with alteration: higher Ag and Cu concentrations are related to the high temperature background potassic alteration. The highest Co contents are associated with lower temperature alteration types (e.g., chloritic). These data indicate that the trace element concentration of chalcopyrite, bornite, and pyrite changed as a function of hydrothermal alteration is controlled by several factors, including temperature, pH, fO2, fS2, and the presence of co-crystallizing phases. Overall, our results provide new information on how trace element partitioning into sulfides relates to the main hydrothermal and mineralization events controlling the elemental budget at Chuquicamata. In particular, our data show that elemental ratios in chalcopyrite (e.g., Se/In) and, most importantly, pyrite (e.g., Ag/Co and Co/Cu) bear the potential for vectoring towards porphyry mineralization and higher Cu resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".