Direct imaging and electronic structure modulation of moiré superlattices at the 2D/3D interface
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s41467-021-21363-5.pdf
Description
Published version
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7.5 MB
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Checksum (MD5)
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Author(s)
Reidy, Kate
Varnavides, Georgios
Thomsen, Joachim Dahl
Kumar, Abinash
Pham, Thang
Blackburn, Arthur M
Anikeeva, Polina
Narang, Prineha
LeBeau, James M
Ross, Frances M
Date Issued
2021
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Reidy, Kate, Varnavides, Georgios, Thomsen, Joachim Dahl, Kumar, Abinash, Pham, Thang et al. 2021. "Direct imaging and electronic structure modulation of moiré superlattices at the 2D/3D interface." Nature Communications, 12 (1).
Version
Final published version
Abstract
The atomic structure at the interface between two-dimensional (2D) and three-dimensional (3D) materials influences properties such as contact resistance, photo-response, and high-frequency electrical performance. Moiré engineering is yet to be utilized for tailoring this 2D/3D interface, despite its success in enabling correlated physics at 2D/2D interfaces. Using epitaxially aligned MoS /Au{111} as a model system, we demonstrate the use of advanced scanning transmission electron microscopy (STEM) combined with a geometric convolution technique in imaging the crystallographic 32 Å moiré pattern at the 2D/3D interface. This moiré period is often hidden in conventional electron microscopy, where the Au structure is seen in projection. We show, via ab initio electronic structure calculations, that charge density is modulated according to the moiré period, illustrating the potential for (opto-)electronic moiré engineering at the 2D/3D interface. Our work presents a general pathway to directly image periodic modulation at interfaces using this combination of emerging microscopy techniques. 2
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Research Laboratory of Electronics
McGovern Institute for Brain Research at MIT
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/S41467-021-21363-5
