| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Donskoi, Eugene
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2021Characterisation of SFCA phases in iron ore sinter by combined optical microscopy and electron probe microanalysis (EPMA)
- 2021Characterisation of SFCA phases in iron ore sinter by combined optical microscopy and electron probe microanalysis (EPMA)
- 2021Transformation of Automated Optical Image Analysis Software Mineral4/Recognition4 to Mineral5/Recognition5
- 2021Automated Optical Image Analysis of Iron Ore Sintercitations
- 2020Advances in Optical Image Analysis Textural Segmentation in Ironmakingcitations
- 2018Importance of textural information in mathematical modelling of iron ore fines sintering performancecitations
- 2017Mineral 4/Recognition 4: A Universal Optical Image Analysis Package for Iron Ore, Sinter and Coke Characterizationcitations
- 2016Mineralogical quantification of iron ore sintercitations
- 2015Mineralogical quantification of iron ore sinter
- 2015Advances in optical image analysis of iron ore sinter
- 2015Automated optical image analysis of natural and sintered iron orecitations
- 2013Comparative study of iron ore characterisation using a scanning electron microscope and optical image analysiscitations
Places of action
| Organizations | Location | People |
|---|
article
Mineralogical quantification of iron ore sinter
Abstract
The mineralogy and microstructure of sinter play an important role in determining the physical and metallurgical properties of iron ore sinter. Characterisation of sinter phases is, therefore, a cost-effective and complementary tool to conventional physical and metallurgical testing of iron ore sinter in evaluating and predicting sinter quality. Over the years, CSIRO (Commonwealth Scientific and Industrial Research Organisation) has developed a scheme for characterising iron ore sinter which classifies primary sinter phases, such as un-reacted and partially reacted haematite, magnetite and remnant fluxes, and secondary phases including silico-ferrite of calcium and aluminium (SFCA), secondary haematite and magnetite, glass and larnite. Quantification of these phases has traditionally been carried out by manual point counting under a petrographic microscope. However, new technologies based on automated optical image analysis, quantitative X-ray diffraction and scanning electron microscopy are now available for evaluation. In this study, two sinter samples of varying chemistry were prepared and characterised using both point counting and automated optical image analysis. Quantification of sinter phases is a complementary tool for comparing the physical properties of sinter obtained from various sinter blends, and sinter phase quantification results can be used for comparing pot-grate sinter with different metallurgical properties.