Unraveling the adhesion characteristics of ruthenium as an advanced metal interconnect material using machine learning potential
This study combines machine learning potential and steered molecular dynamics to provide atomic-level understanding of the adhesion properties of Ru/SiO 2 interfaces.
Authors
- Dae Sin Kim
- Kyoungmin Min (ORCID: https://orcid.org/0000-0002-1041-6005)
- Eunseog Cho (ORCID: https://orcid.org/0000-0001-5308-8278)
- Won‐Joon Son (ORCID: https://orcid.org/0000-0003-4087-4661)
- Hyeon-Seok Do (ORCID: https://orcid.org/0000-0001-8803-3402)
- Seungmin Lee (ORCID: https://orcid.org/0000-0002-0903-0973)
Institutions
- Yonsei University (KR)
- Samsung (South Korea) (KR)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4tc04870a
- Citations
- 2
- Primary Topic
- Semiconductor materials and devices
- Type
- article
- Field-Weighted Citation Impact
- 1.46