We’re pleased to share the HELIOS project 5th peer reviewed article publication by Mert Saraçoğlu (Doctoral Researcher at KU Leuven) in Metallurgical and Materials Transactions B! The full article is available here:
https://doi.org/10.1007/s11663-026-04192-z
Abstract
This study presents a stepwise thermodynamic equilibrium model to predict slag evolution during the argon–oxygen decarburization (AOD) process in stainless steelmaking. The model incorporates key process parameters, including gas composition, pressure, reductant type, flux ratios, and temperature, across the decarburization, reduction, and cooling stages. Thermodynamic predictions were validated against experimental data, including XRD and EPMA–WDS analyses of industrial slag samples. The model enables optimization of the decarburization stage by allowing stepwise variations in gas composition, temperature, initial steel chemistry, and the average ferrostatic pressure within the furnace. It accurately captures the dynamic phase transformations occurring in the slag, including the formation of MgCr2O4 and CaCr2O4 during decarburization, as well as bredigite, merwinite, and cuspidine under different CaO/SiO2 and MgO/SiO2 ratios during reduction. Consequently, the model provides a consistent explanation of slag phase evolution throughout the entire process. It also reveals the influence of reductant strategy (Si vs Si–Al mixtures) and flux composition on phase stability, Cr retention, and slag homogeneity. Characterization studies show that, during decarburization, CaO reacts with Cr2O3 to form a CaCr2O4 layer on the surface of the lime particles. Additionally, rapid cooling after tapping can kinetically hinder the full transformation of equilibrium phases, resulting in the persistence of metastable β-C2S. By accurately predicting slag behavior under industrial conditions, the model supports process optimization, improved Cr recovery during decarburization, reduced flux consumption, and overall, more efficient, sustainable stainless steelmaking operations.
Acknowledgments
The author also thanks the HELIOS – MSCA DN consortium for financial support and collaborative exchanges.
Funding
This project has received funding from the European Union’s Horizon Europe research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 101120068.
