| Autor: |
Yangen Li, Jun-Ping Du, Shuhei Shinzato, Shigenobu Ogata |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
npj Computational Materials, Vol 10, Iss 1, Pp 1-10 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2057-3960 |
| DOI: |
10.1038/s41524-024-01322-6 |
| Popis: |
Abstract In this study, we utilized a quantitative atomistic analysis approach to investigate the impact of chemical ordering structures on the diffusion behavior of interstitials and vacancies within the CrCoNi medium entropy alloy (MEA), employing an advanced neural network interatomic potential (NNP). We discovered that the degree of chemical ordering, which can be precisely controlled through annealing at elevated temperatures, significantly influences both interstitial and vacancy diffusion. This phenomenon contributes to the notable sluggish diffusion characteristic of CrCoNi, largely attributable to the restriction of diffusion pathways in regions with lower degree of chemical ordering. We also emphasized the crucial role of operating temperature on diffusion, which should be remained well below the annealing temperature to preserve the sluggish diffusion effect. Our research sheds light on the interplay between chemical ordering and defect diffusion in MEAs, and it proposes effective strategies for tailoring the diffusivity of MEAs by altering their chemical ordering. These insights are instrumental in the development of next-generation materials, which are optimized for use in challenging environments, such as high-temperature and irradiation conditions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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