Effect of process parameters on the texture evolution of Fe-6.5 wt% Si soft magnetic alloys manufactured via laser powder bed fusion
- Authors
- Lee, Hansol; Choi,Youngsin; Ahn, Jonghyuk; Lee, Kwiyoung; Kim, Yerim; Choi, Joonphil; Lee,Haksung; Kim,Jongryoul
- Issue Date
- Oct-2024
- Publisher
- Elsevier Ltd
- Keywords
- Energy density; Fe-Si; Laser powder bed fusion; Magnetic properties; Microstructure; Texture
- Citation
- Journal of Materials Processing Technology, v.331, pp 1 - 12
- Pages
- 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Materials Processing Technology
- Volume
- 331
- Start Page
- 1
- End Page
- 12
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/120327
- DOI
- 10.1016/j.jmatprotec.2024.118521
- ISSN
- 0924-0136
1873-4774
- Abstract
- Numerous attempts have been made to manufacture high-Si steels using a laser powder bed fusion process. It has been established that controlling texture is critical to enhancing their magnetic properties. In this study, a comprehensive analysis was conducted to ascertain the texture evolution in Fe-Si alloys under various laser powers (P) and scanning speeds (V). The analysis revealed that texture formation in the fusion process is primarily influenced by two factors: P/V, the line energy density, and P/V, associated with enthalpy. Both the melt-pool sizes and the threshold value for the transition in melting mode were effectively characterized by the P/V term, while the P/V term proved essential for texture development under the same melting mode. In keyhole mode, an increase in P/V led to a transition from the {001}<100> to the {111}<1−10> texture. In conduction mode, an increase in P/V led to a transition from the {001}<100> to the {001}<110> texture, along with the development of a strong θ-fiber texture at intermediate P/V values. Furthermore, by examining the mechanisms behind the development of these textures, potential conditions for the development of a strong Goss texture were identified. Finally, significant improvements in magnetic properties were achieved through texture optimization. © 2024 Elsevier B.V.
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