Moiré Potential Independent of Moiré Size Down to a Few Nanometers in Sliding Ferroelectrics
Sliding ferroelectricity represents a way to realize atomically thin ferroelectric materials. Due to the moiré pattern formed during the stacking process, the alternating ferroelectric domain network provides an attractive superlattice of electrostatic potential to modulate the electronic structures of another material sitting on it. The relationship between the ferroelectric potential magnitude and the moiré size, however, has been controversial in the literature. In addition, how strong the potential remains for domain sizes down to the 10 nm range is unclear. In this study, we use contact-mode scanning tunneling microscopy with high spatial and energy resolution to show that the moiré potential is independent of the domain size ranging from hundreds to several nanometers. We also show that the electrostatic potential is determined solely by the specific materials used to fabricate the stack. This study provides important information for sliding ferroelectrics and can foster their application in modulating other materials.
Authors
- Jiamin Xue (ORCID: https://orcid.org/0000-0002-1892-1743)
- Xinyu Lv (ORCID: https://orcid.org/0000-0002-2589-6486)
- Takashi Taniguchi (ORCID: https://orcid.org/0000-0002-1467-3105)
- Kenji Watanabe (ORCID: https://orcid.org/0000-0003-3701-8119)
- Jianming Lü (ORCID: https://orcid.org/0000-0002-1558-4040)
- Jian Liao (ORCID: https://orcid.org/0000-0002-6525-4664)
Institutions
- Peking University (CN)
- National Institute for Materials Science (JP)
- ShanghaiTech University (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2025-04-14
- DOI
- https://doi.org/10.1021/acs.nanolett.5c00676
- Primary Topic
- Adhesion, Friction, and Surface Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- National Natural Science Foundation of China
- Japan Society for the Promotion of Science
- Core Research for Evolutional Science and Technology