Unified classification of metal-2D interactions for tailored functional materials
The modification of two-dimensional (2D) materials with metal atoms can lead to additional structures and properties; however, a systematic classification of metal-2D material interactions is still lacking. We propose a general framework for classifying these interactions based on two primary modes: metal atom adsorption on the surface and intercalation between layers. This framework, validated by first-principles calculations on representative van der Waals layered and nonlayered 2D materials interacting with transition metals (TMs) and alkali metals, provides a comprehensive explanation for experimental observations across various systems. Furthermore, the classification serves as a guide for designing stable and functional 2D materials. Our investigation of nonlayered borophene shows that interlayer-intercalated TM borides (TMBs) exhibit significantly higher stability than intralayer-doped TMBs. Physical property calculations further reveal that these sandwich-type TMBs possess superior mechanical stability and additional electronic properties, underscoring their potential for future applications.
Authors
- Chao He (ORCID: https://orcid.org/0000-0003-3609-5796)
- Xingxing Dong
- Xiao‐Bao Yang (ORCID: https://orcid.org/0000-0001-8851-1988)
- Chang-Chun He (ORCID: https://orcid.org/0000-0002-0131-7638)
- Shao-Gang Xu
- Hu Xu (ORCID: https://orcid.org/0000-0002-2254-5840)
- Feini Yan (ORCID: https://orcid.org/0000-0002-2729-1632)
- Peiyao Qin (ORCID: https://orcid.org/0009-0006-2067-9841)
- Fangfang Yang (ORCID: https://orcid.org/0000-0002-1585-3677)
Institutions
- Southern University of Science and Technology (CN)
- Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Physical Review Materials
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1103/4yh9-g5dp
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00