Enrichment of Se-Te-Au in the Jilongshan Au-Cu Skarn Deposit, Hubei Province: Insight from Pyrite Texture and Composition
Abstract
:1. Introduction
2. Geological Setting
2.1. Regional Geology
2.2. Deposit Geology
3. Materials and Methods
4. Results
4.1. Different Types of Ores and Related Petrography
4.2. Pyrite Types and Generational Characteristics
4.3. EMPA Analyses
4.4. LA-ICP-MS Analyses
5. Discussion
5.1. Pyrite Genesis
5.2. Occurence of Se, Te, and Au in Pyrite
5.3. Enrichment Conditions of Se, Te, and Au
- (1)
- Temperature
- (2)
- Redox Conditions
6. Conclusions
- The pyrite in the Jilongshan deposit can be divided into four different generations: Py1 is framboidal pyrite formed during the sedimentary period; Py2, Py3, and Py4 all belong to pyrite formed during the hydrothermal period.
- In the Jilongshan pyrites, Se mainly occurs as isomorphism. Tellurium can occur as both isomorphism and Te-bearing inclusions. Gold mainly occurs as lattice gold and in a small amount as native Au in pyrite.
- High temperatures contribute to the enrichment and precipitation of Se in hydrothermal pyrite, such as Py2 (median, 138 ppm) and Py3 (median, 344 ppm), while low temperatures and an increase in oxygen fugacity are conducive to the enrichment and precipitation of Au and Te in hydrothermal pyrite, particularly in Py4, which has average Te and Au concentrations of 140 ppm and 12 ppm, respectively.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Types | Fe | S | Pb | As | Te | Ag | Ni | Co | Au | Se | Total | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Py1 (n = 19) | Max | 46.98 | 52.60 | 1.99 * | 4.94 | 0.28 * | 0.69 * | 0.04 | 0.11 | 0.13 | 0.04 | 99.49 |
Min | 40.93 | 47.26 | 0.02 | 0.06 | 0.03 | 0.02 | 0.02 | 0.02 | 0.03 | 0.02 | 97.11 | |
Median | 45.47 | 51.39 | 0.21 | 0.89 | 0.26 | 0.05 | 0.04 | 0.06 | 0.08 | 0.03 | 98.13 | |
Mean | 45.13 | 51.25 | 0.54 | 1.19 | 0.19 | 0.17 | 0.03 | 0.06 | 0.08 | 0.03 | 98.11 | |
Py2 (n = 14) | Max | 47.80 | 53.49 | 0.07 | 0.08 | <dl | 0.05 | <dl | 0.06 | 0.14 | 0.03 | 101.01 |
Min | 45.55 | 51.77 | 0.07 | 0.04 | <dl | 0.04 | <dl | 0.02 | 0.06 | 0.02 | 97.55 | |
Median | 46.15 | 52.19 | 0.07 | 0.06 | <dl | 0.04 | <dl | 0.04 | 0.08 | 0.02 | 98.40 | |
Mean | 46.24 | 52.46 | 0.07 | 0.06 | <dl | 0.04 | <dl | 0.04 | 0.09 | 0.02 | 98.81 | |
Py3 (n = 20) | Max | 47.12 | 53.23 | 0.16 | 0.23 | 0.03 | 1.37 * | 0.11 | 0.09 | 0.10 | 0.23 * | 100.42 |
Min | 43.67 | 50.59 | 0.02 | 0.03 | 0.02 | 0.02 | 0.02 | 0.02 | 0.09 | 0.02 | 97.38 | |
Median | 46.35 | 52.50 | 0.08 | 0.10 | 0.02 | 0.08 | 0.04 | 0.04 | 0.09 | 0.05 | 99.04 | |
Mean | 46.02 | 52.38 | 0.08 | 0.12 | 0.02 | 0.27 | 0.04 | 0.04 | 0.09 | 0.06 | 98.97 | |
Py4 (n = 28) | Max | 47.03 | 53.73 | 0.25 | 2.73 | <dl | 0.51 * | 0.07 | 0.18 | 0.08 | 0.07 | 100.68 |
Min | 38.44 | 49.16 | 0.03 | 0.03 | <dl | 0.02 | 0.02 | 0.02 | 0.03 | 0.02 | 98.26 | |
Median | 46.45 | 52.79 | 0.04 | 0.07 | <dl | 0.05 | 0.02 | 0.04 | 0.05 | 0.04 | 99.51 | |
Mean | 46.07 | 52.70 | 0.08 | 0.31 | <dl | 0.09 | 0.04 | 0.05 | 0.05 | 0.04 | 99.51 |
Co | Ni | Cu | Zn | Ge | As | Se | Ag | Cd | Sb | Te | Au | TI | Bi | Pb | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Py1 * (n = 16) | Max | 1.1 | 4.7 | 5481 | 17,116 | 11 | 88,106 | 23 | 5197 | 1419 | 6068 | 10,105 | 726 | 3618 | 4.3 | 19,189 |
Min | 1.1 | 3.7 | 991 | 8.1 | 5.1 | 17,548 | 15 | 656 | 8.5 | 785 | 407 | 28 | 890 | 0.40 | 3600 | |
Median | 1.1 | 4.2 | 3440 | 74 | 7.0 | 31,149 | 20 | 1902 | 23 | 1992 | 2163 | 142 | 2480 | 0.87 | 13,654 | |
Mean | 1.1 | 4.2 | 3408 | 1795 | 7.4 | 44,319 | 20 | 2483 | 159 | 2940 | 3682 | 256 | 2158 | 1.4 | 12,529 | |
Py2 (n = 26) | Max | 1102 | 797 | 138 | 269 | 7.0 | 1667 | 924 | 17 | <dl | 3.7 | 208 | 0.09 | 0.05 | 89 | 98 |
Min | 4.2 | 1.8 | 3.2 | 11 | 1.7 | 5.6 | 8.1 | 0.06 | <dl | 0.59 | 1.6 | 0.00 | 0.01 | 0.03 | 0.00 | |
Median | 135 | 23 | 7.0 | 118 | 5.4 | 182 | 138 | 2.1 | <dl | 0.95 | 30 | 0.05 | 0.02 | 3.0 | 3.1 | |
Mean | 294 | 187 | 24 | 129 | 5.1 | 393 | 244 | 4.5 | <dl | 1.7 | 47 | 0.05 | 0.02 | 18 | 13 | |
Py3 (n = 15) | Max | 652 | 274 | <dl | 2728 | 6.1 | 865 | 613 | 944 | 306 | 122 | 9.2 | 0.80 | 34 | 21 | 179 |
Min | 34 | 13 | <dl | 2327 | 4.9 | 26 | 201 | 88 | 17 | 0.76 | 3.3 | 0.11 | 0.22 | 0.53 | 15 | |
Median | 194 | 66 | <dl | 2626 | 5.3 | 159 | 344 | 234 | 40 | 41 | 4.9 | 0.52 | 0.80 | 2.4 | 62 | |
Mean | 248 | 83 | <dl | 2560 | 5.4 | 297 | 345 | 334 | 83 | 54 | 6.0 | 0.46 | 8.6 | 4.7 | 75 | |
Py4 (n = 21) | Max | 216 | 164 | 830 | 259 | 9.7 | 3031 | 388 | 550 | 70 | 468 | 494 | 145 | 230 | 56 | 618 |
Min | 1.7 | 1.3 | 1.9 | 4.8 | 4.3 | 109 | 0.20 | 0.10 | 1.3 | 0.68 | 3.2 | 0.08 | 0.01 | 0.00 | 2.4 | |
Median | 5.7 | 8.5 | 119 | 29 | 5.7 | 1008 | 114 | 20 | 2.9 | 31 | 90 | 2.9 | 2.0 | 0.69 | 133 | |
Mean | 39 | 23 | 287 | 65 | 5.8 | 1292 | 165 | 70 | 12 | 100 | 140 | 12 | 28 | 6.5 | 162 |
Area | N | Mean | Median | Max | Standard Deviation | Skewness |
---|---|---|---|---|---|---|
104-1-1 | 292 | 10.0 | 9.7 | 23.4 | 4.18 | 0.56 |
104-1-2 | 64 | 13.0 | 12.6 | 23.0 | 3.81 | 0.17 |
104-1-3 | 125 | 13.2 | 12.6 | 30.0 | 4.19 | 1.01 |
104-2-1 | 64 | 12.9 | 12.9 | 26.8 | 5.43 | 0.31 |
104-2-2 | 121 | 11.9 | 11.3 | 34.4 | 5.19 | 0.85 |
104-2-3 | 14 | 30.6 | 31.5 | 44.5 | 7.70 | 0.11 |
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Nan, G.; Xu, J.; Liu, W.; Chen, S.; Cen, Z.; Jiang, J. Enrichment of Se-Te-Au in the Jilongshan Au-Cu Skarn Deposit, Hubei Province: Insight from Pyrite Texture and Composition. Minerals 2023, 13, 1516. https://doi.org/10.3390/min13121516
Nan G, Xu J, Liu W, Chen S, Cen Z, Jiang J. Enrichment of Se-Te-Au in the Jilongshan Au-Cu Skarn Deposit, Hubei Province: Insight from Pyrite Texture and Composition. Minerals. 2023; 13(12):1516. https://doi.org/10.3390/min13121516
Chicago/Turabian StyleNan, Guizhou, Jing Xu, Wenyuan Liu, Suyu Chen, Zhihui Cen, and Jichen Jiang. 2023. "Enrichment of Se-Te-Au in the Jilongshan Au-Cu Skarn Deposit, Hubei Province: Insight from Pyrite Texture and Composition" Minerals 13, no. 12: 1516. https://doi.org/10.3390/min13121516