Abstract
The characterization of non-metallic inclusions is crucial for understanding their origin, behavior, and modification during steelmaking and is directly connected to process optimization and improving product quality. SEM/EDS is the state-of-the-art characterization technique, measuring microscale morphology and elemental composition of non-metallic inclusions. Automated SEM/EDS analysis evaluates thousands of microscopic particles on a sample within hours, enabling the assessment of steel cleanness. However, challenges such as artifact misinterpretation and steel matrix effects on EDS accuracy must be considered to ensure reliable results. Furthermore, the widely used standardless EDS analysis is limited to elemental compositions normalized to 100 weight-%, restricting its applicability for more detailed characterizations.
This study introduces and verifies a framework for steel cleanness evaluation including automated and manual SEM/EDS analysis, data processing, and computational thermodynamics. Artifacts, with shares up to 42 %, were effectively removed from automated SEM/EDS data. A matrix correction method adjusted non-metallic inclusion typification based on elemental thresholds. This significantly changed number densities of individual types, with a maximum increase of 798 %, and improved the overall representation. Additionally, a novel mapping technique was developed to calculate phase equilibria based on EDS data, determining number and distribution of phases in complex non-metallic inclusions at 1600 °C. Experimental cross-validation was performed using TEM. This mapping technique provides more insights into the characteristics of non-metallic inclusions compared to conventional standardless EDS analysis. The proposed framework represents a robust approach for advancing steel cleanness evaluations, enabling deeper studies on the formation and modification of non-metallic inclusions.
