JOURNAL ARTICLE
Influence of Graphite Contents on Microstructure and Properties of Fe-based Laser Cladding Layer on Ductile Iron.
Published In: Lasers in Engineering (Old City Publishing), 2025, v. 59, n. 4-6. P. 345 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: CHEN, CHENGMING; BI, JINPENG; SUI, MINGCHAO; LV, YUEXIA; Zhao, Wei; Zhang, Hui 3 of 3
Abstract
In this study, the FeV50 content in the alloy powder was kept unchanged with the vanadium-carbon molar ratio varying at 1:1.6, 1:1.2, 1:0.8, 1:0.4 and 1:0, aiming to optimize the forming quality and properties of Fe-based laser cladding layer on ductile iron. The effects of different graphite contents on the microstructure and properties of the cladding layer were further analyzed. The research results showed that, the vanadium carbides in the cladding layer were uniformly distributed. The number of pore defects and cracks in the cladding layer shows a decreasing trend in case of decreasing the graphite addition. The decrease of graphite addition also results in a decrease in the number of carbides in the cladding layer, and there is an initial increase and then a decrease in the microhardness of the cladding layer. Furthermore, the corrosion resistance of the cladding layer increases with the decrease of graphite addition. When the addition of graphite powder is set at 4.57 wt. %, the optimal hardness and self-corrosion current density of the cladding layer can be achieved at 915 HV0.2 and 1.6x10-5 Am/cm², respectively. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Lasers in Engineering (Old City Publishing). 2025/07, Vol. 59, Issue 4-6, p345
- Document Type:Article
- Subject Area:Geology
- Publication Date:2025
- ISSN:0898-1507
- Accession Number:187890137
- Copyright Statement:Copyright of Lasers in Engineering (Old City Publishing) is the property of Old City Publishing, Inc. 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.)
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