Analysis of Grain Size and Distribution in Fe-B-C Alloy Using Optical Microscopy and Image Analysis

Abstract

The size and morphology of the grains of a material and their distribution have a significant impact on the mechanical properties of the material (and their further application). Based on the data obtained from image analysis, it is possible to modify the microstructure of materials. Within the formation of a eutectic, borides occur along the austenite grain boundary. The cell size can be managed by technological process (forming) or by adding chemical elements. In this paper, a method of measuring the cell size of a hypoeutectic Fe-B-C alloy across the entire examined cross-section of the sample was researched by creating a mosaic from individual frames. Sample preparation allowing clear grain boundary visibility was essential. It was observed that the most effective results were achieved with quenched microstructures etched using Klemm I color etchant. A Zeiss optic microscope with AxioVision software (AxioVision SE64 Rel. 4.9.1.) was used for image acquisition, and mosaics were created using MosaiX software. This study revealed that, before further processing, images must be segmented to address color inconsistencies using average grayscale values. This preprocessing step enabled precise cell size analysis through an algorithm implemented in Scilab. The developed methodology was used to create sample maps for determining the grain size and its distribution in the Fe-B alloy. This automated approach provides a comprehensive dataset, enabling detailed analysis of both individual images and the entire sample. Manual grain size measurements were performed for verification, and statistical analysis demonstrated a close correspondence between the results. The results confirmed a significant impact of the added alloying elements on microstructural homogeneity in hypoeutectic Fe-B-C alloys. Homogeneity decreases with the addition of alloying elements such as chromium and vanadium, while tungsten contributes to a more stable grain size. A low gradient value shows small grain size changes from the core to the edge in the cross-section. Furthermore, the results show that higher amounts of chromium increase the average grain size values. The results demonstrate that automated methods allow for comprehensive analysis of the entire sample, enabling precise determination of grain size and other properties across the entire object rather than only on subjectively selected areas. This approach effectively eliminates the influence of human error, ensuring more reliable and consistent data.