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PLSR as a new XRD method for downstream processing of ores: – case study: Fe2+ determination in iron ore sinter

  • Uwe König (a1), Thomas Degen (a1) and Nicholas Norberg (a1)

Abstract

The use of high-speed detectors made X-ray diffraction (XRD) become an important tool for process control in mining and metal industries. Decreasing ore qualities and increasing prices for raw materials require a better control of processed ore and a more efficient use of energy. Traditionally quality control of iron ore sinter has relied on time-consuming wet chemistry. The mineralogical composition that defines the physical properties such as hardness or reducibility is not monitored. XRD analysis in combination with Rietveld quantification and statistical data evaluation using partial least-squares regression (PLSR) has been successfully established to determine the mineralogical composition and the Fe2+ content of iron ore sinter within an analysis time of less than 10 min per sample. A total of 35 iron ore sinter samples were measured and evaluated using PLSR and the Rietveld method. The results were compared with wet chemistry data. PLSR results show accuracy for the Fe2+ content of ±0.14%. No pure phases, crystal structures, or complex modeling of peak shapes are required. The Rietveld method was used to quantify the total phase composition of the samples. The Fe2+ content could be calculated from all phases present. Both methods take the full XRD pattern into account and can be simultaneously applied on the same measurement. PLSR was found to be the more robust method if only Fe2+ results are required. The Rietveld method helps predict other parameters such as the compressional strength of the sinter by monitoring all existing phases (e.g., larnite, C2S, or silico-ferrite of calcium and aluminum phases).

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a)Author to whom correspondence should be addressed. Electronic mail: uwe.konig@panalytical.com

References

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De Jong, S. (1993). “SIMPLSR: an alternative approach to partial least squares regression,” Chemometr. Intell. Lab. Syst. 18, 251263.
Ghosh, A. and Chatterjee, A. (2008). Ironmaking and Steel Making: Theory and Practice (PHI Learning Private Ltd., New Dehli, India).
Hamilton, J. D. G., Hoskins, B. F., Mumme, W. G., Borbidge, W. E., and Montague, M. A. (1989). “The crystal structure and crystal chemistry of Ca2.3Mg0.8Al1.5Si1.1O20 (SFCA): solid solutions limits and selected phase relationships of SFCA in the SiO2–Fe2O3–CaO(–Al2O3) system,” Neues Jahrb. Mineral. 161, 126.
Ishikawa, Y., Shimomura, Y., Sasaki, M., and Toda, H. (1983). “Improvement on sinter quality based on the mineralogical properties of ores,” Ironmak. Proc. 42, 1729.
Kwang-Su, P., Hyeseon, L., Chi-Hyuck, J., Kwang-Hyun, P., Jae-Won, J., and Seung-Bin, K. (2000). “Rapid determination of FeO content in sinter ores using DRIFT spectra and multivariate Calibrations,” Chemometr. Intell. Lab. Syst. 51, 163173.
Lohninger, H. (1999). Teach/Me – Data Analysis (Springer–Verlag, Berlin).
Mumme, W. G., Clout, J. M. F., and Gable, R. W. (1998). “The crystal structure of SFCA-I, Ca3.18Fe3+14.66 Al1.34Fe2+0.82O28, a homologue of the aenigmatite structure type, and new crystal structure refinements of ß-CFF, Ca2.99Fe3+14.30Fe2+0.55O25 and Mg-free SFCA, Ca2.45Fe3+9.04Al1.74Fe2+0.16Si0.6O20,” Neues Jahrb. Mineral. 173, 93117.
Patrick, T. R. C. and Lovel, R. R. (2001). “Leaching dicalcium silicates from iron ore sinter to remove phosphorus and other contaminants,” ISIJ 41, 128135.
Pownceby, M. I. and Clout, J. M. F. (2003). “Importance of fine ore chemical composition and high temperature phase relations: applications to iron ore sintering and pelletizing,” Min. Proc. Extractive Metall. (Trans. Inst. Min. Metal. C) 112, 4451.
Rietveld, H. M. (1969). “A profile refinement method for nuclear and magnetic structures,” J. Appl. Crystallogr. 2, 6571.
Van den Berg, T. (2008). “An assessment of the production of fine material in iron ore sinter,” MSc Thesis, Department of Materials Science and Metallurgical Engineering, University of Pretoria, Pretoria, February 2008; p. 130.
Wold, H. (1966). “Estimation of principal components and related models by iterative least Squares,” in Multivariate Analysis, edited by Krishnaiaah, P. R. (Academic Press, New York), pp. 391420.

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