| Issue |
Metall. Res. Technol.
Volume 123, Number 3, 2026
|
|
|---|---|---|
| Article Number | 315 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1051/metal/2026001 | |
| Published online | 27 March 2026 | |
Original Article
Experimental determination and mechanism analysis of thermal conductivity in CaF2-CaO-Al2O3-MgO-TiO2 five component slag system
1
School of Materials and Metallurgy, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, PR China
2
School of Foreign Studies, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, PR China
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
1
August
2025
Accepted:
2
January
2026
Abstract
The determination of the thermal conductivity of slag is important for enhancing thermal efficiency and achieving greater accuracy in numerical simulations. This study focuses on the thermal conductivity of the CaF2-CaO-Al2O3-MgO-TiO2 slag system, which was determined using the transient hot-wire method. The effects of current intensity, temperature, and slag composition on thermal conductivity were investigated. Summarize the relationship between the thermal conductivity of slag and temperature as well as slag composition changes. The results indicate that, for slags with a porosity in the range 0.33∼0.35, the thermal conductivity of the solid slag (powdered bulk material) increases with temperature, whereas that of the liquid slag decreases with temperature. Furthermore, the thermal conductivity of the slag system increases with increasing CaF2 content and decreases linearly with increasing of MgO and TiO2 content. The formation of high thermal conductivity resistance, such as MgO∙Al2O3 and 2MgO∙TiO2 leads to a decrease in thermal conductivity. According to the above results, the relationship between the thermal conductivity of slag system and the temperature and the composition of slag system is summarized.
Key words: transient hot wire method / thermal conductivity / slag system / prediction model
© EDP Sciences, 2026
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