MICROSTRUCTURAL CHARACTERIZATION OF A Cr-Mo-W-Co HOT-WORK DIE STEEL AFTER TEMPERING.
Saved in:
| Title: | MICROSTRUCTURAL CHARACTERIZATION OF A Cr-Mo-W-Co HOT-WORK DIE STEEL AFTER TEMPERING. |
|---|---|
| Authors: | HA, SEONG-HO1, SHIN, YOUNG-CHUL1 ycshin@kitech.re.kr, LIM, SUNG-HWAN2 |
| Source: | Archives of Metallurgy & Materials. 2026, Vol. 71 Issue 2, p575-578. 4p. |
| Subjects: | Tempering, Microstructure, Scanning electron microscopy, Transmission electron microscopy, Electron backscattering, Chromium molybdenum steel, Carbides, Heat resistant steel |
| Abstract: | The microstructural characteristics of a Cr-Mo-W-Co hot-work die steel subjected to tempering were systematically investigated using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). All analyses were conducted under a unified tempering condition of 580°C for 6 h in order to establish a coherent interpretation of the stabilized microstructural state. SEM observations revealed the presence of micrometer-scale bright particles whose size and distribution remained unchanged after tempering, indicating that they are pre-existing carbides rather than tempering-induced precipitates. EBSD analysis showed a pronounced change in local crystallographic substructure after tempering, as evidenced by an increase in kernel average misorientation, suggesting sub-grain scale rearrangement within the matrix. TEM and selected area electron diffraction confirmed the formation of crystalline precipitates with well-defined interfaces, which could not be resolved by SEM. STEM-EDS analysis further demonstrated that these precipitates are Mo-W-rich complex alloy carbides incorporating multiple alloying elements. [ABSTRACT FROM AUTHOR] |
| Copyright of Archives of Metallurgy & Materials is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!