Pratama Istiadi Guntoro


Project Overview

The project concerns itself with developing X-ray Micro Tomography (μCT) as a novel tool in geometallurgy. High power μCT, developed for advanced manufacturing, is able to produce a 3D model of rocks and in so doing expose grain boundaries. In this project, such information will be used for breakage modelling and virtual particles generation for process simulation. The work itself divided into two main parts.

Firstly, to characterize standard drill core sample with μCT. This part concerns itself with refining methods for extracting information from μCT data, including mineralogical composition, size and shape distribution, and textural descriptors.

Secondly, validating the information through simulating a texture based on the information from the μCT data. The resulting simulated rock (mineral) texture will then be used for predictive breakage modelling in which particle population are generated. The knowledge of how rocks will break in a mill will allow mineral processing plants to find-tune the setting of their crushers and mills more efficiently, aiding the conservation of energy.


  • Guntoro, P. I., Ghorbani, Y., Butcher, A. R., Kuva, J., Rosenkranz, J. (2020). Textural Quantification and Classification of Drill Cores for Geometallurgy: Moving Toward 3D with X-ray Microcomputed Tomography (µCT). Natural Resources Research.
  • Guntoro, P.I., Tiu, G., Ghorbani, Y., Lund, C., Rosenkranz, J. (2019). Application of machine learning techniques in mineral phase segmentation for X-ray microcomputed tomography (µCT) data. Miner. Eng. 142, 105882.
  • Guntoro, P.I., Ghorbani, Y., Koch, P.-H., Rosenkranz, J. (2019). X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods. Minerals 9, 183.
  • Guntoro, P.I., Jokilaakso, A., Hellstén, N., Taskinen, P. (2018). Copper matte – slag reaction sequences and separation processes in matte smelting. J. Min. Metall. Sect. B Metall. 54, 301–311.

Conference Presentations


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