JOURNAL ARTICLE
Insight into the Grain Refining Mechanism of Al–Ti–C and the Interfacial Properties between the Inoculants and Aluminum.
Published In: Physica Status Solidi (B), 2024, v. 261, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Zhao, Dahong; Xie, Cheng; Xiao, Zhengbing; Huang, Shita 3 of 3
Abstract
The grain refinement mechanism of Al–Ti–C grain refiners used in the casting procedure of aluminum has been studied by first‐principles calculation. Considering the controversy over Al3Ti, TiC, or Al3Ti–TiC as nucleation sites, the adsorption behavior of possible nucleation surfaces for Al atoms, including adsorption energies and adsorption sites, as well as the interfacial properties of Al/Al3Ti/TiC are calculated and compared. In the results, it is shown that the Al3Ti(112) surface has a stronger adsorption capacity for Al than TiC. By using the edge‐to‐edge matching crystallographic model and the calculation of the adsorption energy, it is found that the monolayer Al3Ti(112) can be stabilized on the TiC(100) surface, and the combination of TiC and monolayer Al3Ti can significantly improve the adsorption capacity of Al. Interfacial electronic structure analysis shows stronger chemical bonding between Al and Ti at the Al/Al3Ti/TiC interface compared to Al/Al3Ti, which explains that the monolayer Al3Ti covering the TiC surface has the strongest adsorption capacity for Al atoms. Therefore, it is speculated that TiC with a monolayer of Al3Ti covering the surface will serve as a potential nucleation site during grain refinement, which will provide a theoretical reference for future research work. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Physica Status Solidi (B). 2024/04, Vol. 261, Issue 4, p1
- Document Type:Article
- Subject Area:Geology
- Publication Date:2024
- ISSN:0370-1972
- DOI:10.1002/pssb.202300387
- Accession Number:176536464
- Copyright Statement:Copyright of Physica Status Solidi (B) is the property of Wiley-Blackwell 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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