The Effect of the Textural Characteristics of Iron Ore Processing Tailings on the Processes of Iron Recovery From Them

Document Type : Research - Paper

Authors

1 Ph.D Student, Department of Mining Engineering, University of Kashan, Kashan, Iran

2 Associate Professor, Faculty of Mining Engineering, Amirkabir University of Technology, Tehran, Iran

Abstract

The present study aims to identify and quantify the textural characteristics of granulated iron ore tailing depots to investigate these characteristics' effect on the tailings reprocessing behavior. After sampling from the tailings depots and classifying them into six size fractions, chemical analyses, and optical and electron microscopic studies were conducted on each fraction. By processing the images and coding in MATLAB software, a quantitative parameter related to the interlocking of the target mineral with gangues—termed the association index (AI)—was determined. Mineralogical studies indicate the presence of magnetite and hematite, along with their complex interlocking with other metallic minerals and gangue. Based on the AI calculated for each fraction, the highest interlock occurs between magnetite and hematite, attributed to the martitization of magnetite to hematite. In the size fraction above 250 microns, the highest AI is observed for magnetite with the following minerals: calcite, diopside, garnet, and quartz. In this fraction, the ratio of AI to the grades of pyrite and chalcopyrite exceeds 1, indicating that magnetite is preferable to these minerals. The magnetic separation results confirmed that pyrite and chalcopyrite were recovered into the magnetic concentrate in sizes over 250 microns. This can significantly aid in copper mineral recovery as a pre-treatment step.

Keywords

Main Subjects

References

  1. Rumpf, H. (1973). “Physical aspects of comminution and new formulation of a law of comminution”. Powder Technology, 7(3): 145-159.
  2. Dunham, S., and Vann, J. (2007). “Geometallurgy, geostatistics and project value—does your block model tell you what you need to know”. In: Proceedings of the Project Evaluation Conference, Melbourne, Australia, 19-20.
  3. Lynch, A. (2015). “Comminution Handbook”. Australasian Institute of Mining and Metallurgy.
  4. Lotter, N. O., Kowal, D. L., Tuzun, M. A., Whittaker, P. J., and Kormos, L. (2003). “Sampling and flotation testing of Sudbury Basin drill core for process mineralogy modelling”. Minerals Engineering, 16(9): 857-864.
  5. Becker, M., Brough, C., Reid, D., Smith, D., and Bradshaw, D. (2008). “Geometallurgical characterisation of the Merensky Reef at Northam Platinum Mine; comparison of normal, pothole and transitional reef types”. In: International Congress for Automated Mineralogy, 391-399.
  6. Hunt, J. A., Berry, R., Walters, S., Bonnici, N., Kamenetsky, M., Nguyen, K., and Evans, C. L. (2008). “A new look at mineral maps and the potential relationships of extracted data to mineral processing behaviours”. In: Ninth International Congress for Applied Mineralogy, AusIMM., 429-432.
  7. Walters, S. (2008). “An overview of new integrated geometallurgical research”. Australasian Institute of Mining and Metallurgy Publication Series, 79-82.
  8. Can, N. M., Celik, I. B., Bicak, O., and Altun, O. (2013). “Mass balance and quantitative mineralogy studies for circuit modification”. Mineral Processing and Extractive Metallurgy Review, 34(5): 348-365.
  9. Tungpalan, K., Wightman, E., and Manlapig, E. (2015). “Relating mineralogical and textural characteristics to flotation behaviour”. Minerals Engineering, 82: 136-140.
  10. Wills, B. A., and Napier-Munn, T. (2016). “Wills’ Mineral Processing Technology: An Introduction to the Practical Aspects of Ore Treatment and Mineral Recovery, seventh ed”. Elsevier Science and Technology.
  11. Rincon, J., Gaydardzhiev, S., and Stamenov, L. (2019). “Investigation on the flotation recovery of copper sulphosalts through an integrated mineralogical approach”. Minerals Engineering, 130: 36-47.
  12. Bahrami, A., Abdollahi, M., Mirmohammadi, M., Kazemi, F., Danesh, A., and Shokrzadeh, M. (2020). “A process mineralogy approach to study the efficiency of milling of molybdenite circuit processing”. Scientific Reports, 10(1): 21211.
  13. Zhang, J., and Subasinghe, N. (2012). “Extracting ore texture information using image analysis”. Mineral Processing and Extractive Metallurgy, 121(3): 123-130.
  14. Lund, C., Lamberg, P., and Lindberg, T. (2015). “Development of a geometallurgical framework to quantify mineral textures for process prediction”. Minerals Engineering, 82: 61-77.
  15. Hilden, M. M., and Powell, M. S. (2017). “A geometrical texture model for multi-mineral liberation prediction”. Minerals Engineering, 111: 25-35.
  16. Parian, M., Mwanga, A., Lamberg, P., and Rosenkranz, J. (2018). “Ore texture breakage characterization and fragmentation into multiphase particles”. Powder Technology, 327: 57-69.
  17. Sousa, R., Futuro, A., Fiúza, A., and Leite, M. M. (2020). “Pre-concentration at crushing sizes for low-grade ores processing–Ore macro texture characterization and liberation assessment”. Minerals Engineering, 147: 106156
  18. Perez-Barnuevo, L., Lévesque, S., and Bazin, C. (2018). “Automated recognition of drill core textures: A geometallurgical tool for mineral processing prediction”. Minerals Engineering, 118: 87-96.
  19. Nguyen, A., Tungpalan, K., Evans, C., Manlapig, E., Jackson, J., Nguyen, K., and Valenta, R. (2021). “A method for rapid estimation of processing behaviour based on ore texture”. Minerals Engineering, 171: 107111.
  20. Zhang, Y., Francois, N., Henley, R. W., Knuefing, L., Turner, M., Saadatfar, M., Brink, F., and Knackstedt, M. (2024). “In-situ study of texture-breakage coupling in a copper ore using X-ray micro-CT”. Minerals Engineering, 205: 108464.
  21. Bonnici, N., Hunt, J. A., Walters, S. G., Berry, R., and Collett, D. (2008, September). “Relating textural attributes to mineral processing: Developing a more effective approach for the Cadia East Cu–Au porphyry deposit”. In: Proceedings of the ninth international congress for applied mineralogy conference (ICAM), 4-5.
  22. Lamberg, P. (2011). “Particles-the bridge between geology and metallurgy”. In: Proceedings of Conference in Mineral Engineering, Luleå, Sweden, 1-16.
  23. Kazemi, F., and Abdollahzadeh, A. A. (2024). “Valorisation of iron ore tailing piles: utilisation of element-to-mineral conversion and association index to building mineralogical modal”. Canadian Metallurgical Quarterly, 1-14.
  24. Galvão, J. L. B., Andrade, H. D., Brigolini, G. J., Peixoto, R. A. F., and Mendes, J. C. (2018). “Reuse of iron ore tailings from tailings dams as pigment for sustainable paints”. Journal of Cleaner Production, 200: 412-422.
  25. Lamberg, P., Rosenkranz, J., Wanhainen, C., Lund, C., Minz, F., Mwanga, A., and Parian, M. (2013, September). “Building a geometallurgical model in iron ores using a mineralogical approach with liberation data”. In: Proceedings of the Second AusIMM International Geometallurgy Conference, Brisbane, Australia, 317-324.
  26. Parian, M. (2017). “Development of a geometallurgical framework for iron ores-A mineralogical approach to particle-based modeling”. Doctoral dissertation, Luleå University of Technology.
  27. Koch, P. H., Lund, C., and Rosenkranz, J. (2019). “Automated drill core mineralogical characterization method for texture classification and modal mineralogy estimation for geometallurgy”. Minerals Engineering, 136: 99-109.
  28. Lishchuk, V., Lund, C., Koch, P. H., Gustafsson, M., and Pålsson, B. I. (2019). “Geometallurgical characterisation of Leveäniemi iron ore–Unlocking the patterns”. Minerals Engineering, 131: 325-335.
Journal of Mineral Resources Engineering
Volume 10, Issue 2 - Serial Number 36
September 2025
Pages 117-135

Files

History

  • Receive Date: 22 June 2024
  • Revise Date: 05 October 2024
  • Accept Date: 19 September 2024

Share

How to cite

Statistics