Mineralogy of Iron Ore Sinters, 3rd Edition

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy".

Deadline for manuscript submissions: 28 November 2025 | Viewed by 323

Special Issue Editors


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Guest Editor
CSIRO Mineral Resources, Research Way, Clayton, VIC 3168, Australia
Interests: applied/process mineralogy; experimental petrology and phase equilibria; geometallurgy; iron ore characterization and processing (beneficiation, agglomeration, sintering); ore mineralogy; materials characterization (SEM, EPMA, in situ XRD); heavy mineral sand deposits; uranium deposits; hydrometallurgy
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Guest Editor
Department of Materials Science and Engineering, Institute of Science Tokyo, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan
Interests: ferrous and nonferrous metallurgy; thermophysical properties of liquid and solid oxides; phase diagrams of iron ore sinter; recycle of ironmaking slags and refractories

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Guest Editor
Department of Materials Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
Interests: high temperature processing (incl. mineral processing, sintering, ironmaking & steelmaking, recycling of industrial wastes, microwave processing, etc.); thermodynamics of inorganic materials at high temperatures (including nano phase diagram); physical properties of inorganic materials at high temperatures (surface tension, viscosity, thermal conductivity, structure, etc.); smart factory (ICT, digital twin, machine learning)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Iron ore sintering is an important stage in the production of steel from iron ore. Sinter can constitute more than 60% of the ferrous burden in modern blast furnaces in Japan and most blast furnaces in Europe. Iron ore sintering is a high-temperature process that converts iron ore fines (<6–8 mm in size, too small for direct feed into the blast furnace) into larger agglomerates containing bonding phases, unmelted nuclei and pores. The sinter must possess the chemical, physical, metallurgical and gas permeability characteristics required for efficient blast furnace operation, and these are controlled in part via the sinter mineralogy. Although a mature field of research, the progressive decline in iron ore grades requires that innovative research into all aspects of the mineralogy of iron ore sinter, including its effect on the physical and mechanical properties, continues. For this Special Issue (Volume III), a follow-up to two previous Special Issues from 2019 and 2022, we welcome contributions detailing fundamental physical chemical studies, experimental and theoretical studied on mineralogy or iron ore sinters. This includes detailed characterization of the formation mechanisms of sinter mineral phases. We also solicit methodological studies employing cutting-edge analytics. This Special Issue will contribute to ensuring a better understanding of how iron ore sinter mineralogy impacts sinter quality.

Dr. Mark I. Pownceby
Prof. Dr. Miyuki Hayashi
Prof. Dr. Joonho Lee
Guest Editors

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Keywords

  • sinter mineralogy
  • crystal structures
  • phase equilibria
  • characterisation
  • formation mechanisms

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Published Papers (1 paper)

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Research

24 pages, 2999 KiB  
Article
Research on Prediction Method of Ferrous Oxide Content in Sinter Based on Optimized Neural Network
by Shaohui Li, Yuanyuan Cao, Zhenjie Zhou, Xinghua Li and Yanlong Zhu
Minerals 2025, 15(6), 553; https://doi.org/10.3390/min15060553 - 22 May 2025
Viewed by 235
Abstract
As a key parameter in the sintering process, the ferrous oxide content of sinter can reflect the working condition, energy consumption level, and quality level of the final sintered products in the sintering process. It has become a key problem to realize the [...] Read more.
As a key parameter in the sintering process, the ferrous oxide content of sinter can reflect the working condition, energy consumption level, and quality level of the final sintered products in the sintering process. It has become a key problem to realize the prediction of ferrous oxide content in sinter and feedback control of sinter quality accordingly. The two commonly used methods for detecting ferrous oxide content in industrial production currently do not meet real-time requirements and cannot provide timely feedback for production regulation. Therefore, research on real-time prediction technology of ferrous oxide content in sinter was carried out, and an optimized back propagation neural network model was established to realize the mapping between characteristic parameters and the FeO content in sinter. The characteristic parameters include image parameters and process parameters. Through the research on the brightness change trend of the machine tail cross-section image, the best cross-section image acquisition method based on brightness difference is realized, and image parameters are obtained by image processing technology. The process parameters were selected using correlation analysis. Through data processing techniques such as data cleaning, normalization, and feature fusion, feature parameters were obtained as input vectors for the neural network. To improve prediction accuracy and system stability, an adaptive learning rate and genetic algorithm were used to optimize the traditional BP neural network. The average test error of the optimized prediction model was 0.32%. Taking actual data production as an example, test data on the FeO content of sinter were extracted from the laboratory. Compared with the FeO content predicted by the system, the prediction time of the system was about 2 h earlier than the test time. In terms of prediction accuracy, the average absolute error was 0.25%, and the absolute prediction error was not more than ±1%. Full article
(This article belongs to the Special Issue Mineralogy of Iron Ore Sinters, 3rd Edition)
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