The study of mineral recovery from ores needs a detailed comprehension of the properties of the rocks before any process is applied in order to improve the mineral extraction. Process mineralogy refers to the utilization of knowledge about the minerals in order to forecast and solve problems related to the process of ore processing while petrography refers to the classification of the rocks using microscopic techniques. With the diminishing ore grades worldwide, a comprehensive characterization of minerals becomes necessary in order to ensure efficient utilization of resources and energy (Kao et al., 2018).
Traditional method of ore characterization is through optical petrography. Mineral associations and textures are determined by viewing thin sections of the ores using a polarizing light microscope. Although this technique involves subjective observation and effort, it remains important in providing a baseline examination of the mineral assemblage in order to gain an insight of the geological situation.
The first optical examination is usually followed by X-ray Diffraction (XRD), which is a common technique used to determine the bulk mineralogy. X-ray Diffraction is an extremely fast and precise analytical method, where mineral composition is correlated with diffraction density and can be quantitatively and qualitatively identified within an ore sample (Ali et al., 2023). The bulk composition data acquired with the help of XRD allows selecting the comminution equipment and chemical agents for further concentration process.
The automated mineralogy technology like Scanning Electron Microscope in conjunction with Energy Dispersive X-ray spectroscopy (SEM-EDS) is essential to carry out a particle-by-particle analysis. The information derived by quantitative geometrical data from QEMSCAN and MLA technology provides accurate data on mineral association, grain size distribution and liberation percentage (Warlo et al., 2019). This implies that the technology provides information on the liberation of valuable minerals and those trapped in waste gangue.
Although automatic mineralogy offers good information two-dimensionally, XCT is becoming more common for the analysis of samples three-dimensionally. XCT is a technique that uses non-invasive methods to calculate linear attenuation coefficients for the 3D pixels (voxels), thus enabling the visualization of the rock textures and structures at different scales (Warlo et al., 2021). The use of 3D images helps the assessment of the real distribution of dense minerals before their crushing.
To sum up, these techniques practiced together each day create the basis of geometallurgy for mining companies. The metallurgists obtain important information through these techniques and make sound decisions. This helps avoid errors in laboratories and improves the efficiency of circuits by optimizing them.
References
Ali, A., Zhang, N., & Santos, R. M. (2023). Mineral characterization using scanning electron microscopy (SEM): A review of the fundamentals, advancements, and research directions. Applied Sciences, 13(23), 12600. https://doi.org/10.3390/app132312600
Kao, M.-C., Pegoraro, A. F., Kingston, D. M., Stolow, A., Kuo, W.-C., Mercier, P. H. J., Gogoi, A., Kao, F.-J., & Ridsdale, A. (2018). Direct mineralogical imaging of economic ore and rock samples with multi-modal nonlinear optical microscopy. Scientific Reports, 8. https://doi.org/10.1038/s41598-018-34779-9
Warlo, M., Bark, G., Wanhainen, C., Butcher, A. R., Forsberg, F., Lycksam, H., & Kuva, J. (2021). Multi-scale X-ray computed tomography analysis to aid automated mineralogy in ore geology research. Frontiers in Earth Science, 9. https://doi.org/10.3389/feart.2021.789372
Warlo, M., Wanhainen, C., Bark, G., Butcher, A. R., McElroy, I., Brising, D., & Rollinson, G. K. (2019). Automated quantitative mineralogy optimized for simultaneous detection of (precious/critical) rare metals and base metals in a production-focused environment. Minerals, 9(7), 440. https://doi.org/10.3390/min9070440
