4.7 Article

Analysis of iron ore pellets properties concerning raw material mineralogy for effective utilization of mining waste

Journal

POWDER TECHNOLOGY
Volume 400, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.powtec.2022.117259

Keywords

Iron ore slimes; Loss on ignition; Pellet properties; Mineralogy; Empirical model

Funding

  1. CSIR-Institute of Minerals and Materials Technology, Bhubaneswar

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This study focuses on the utilization of iron ore slimes without beneficiation by blending with high-grade fines to make iron ore pellets. The properties of the pellets and the mineralogy were investigated, and an empirical correlation was developed to predict the pellet properties based on feed mineralogical data.
The value addition in iron ore mining waste generated from washing or beneficiation plants is a challenging task. The iron ore slimes, which contain low iron content with high gangue minerals like kaolinite, gibbsite, and quartzite, cannot be used directly for iron production. The present study focuses on utilization of iron ore slimes without beneficiation by blending with high-grade fines for making iron ore pellets. The pellets were prepared by adding slimes in different weight proportions (0, 10, 20, 30, 40, and 50%) with high-grade iron ore fines. The high-grade iron ore fines contain 64% Fe, 2.25% LOI, and Blaine number 2975 cm(2)/g, whereas iron ore slimes contain 52.45% Fe, 5.60% LOI, and Blaine number 7046 cm(2)/g. Pellets were produced without using bentonite as the binder. The pellet properties, such as drop number, green and dry compressive strength and moisture content of green pellet, cold compressive strength, porosity, swelling index, reduction degradation index, and reducibility index of fired pellet, have been investigated. The pellet mineralogy was analyzed using x-ray diffraction and optical microscope. The empirical correlation has been developed incorporating feed mineralogical data based on kaolinite and goethite to predict the physical and metallurgical properties of pellet. (C) 2022 Elsevier B.V. All rights reserved.

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