Planar and van der Waals heterostructures for vertical tunnelling single electron transistors
Gwangwoo Kim, Sung-Soo Kim, Jonghyuk Jeon, Seong In Yoon, Seokmo Hong,, Young Jin Cho, Abhishek Misra, Servet Ozdemir, Jun Yin, Davit Ghazaryan,, Mathew Holwill, Artem Mishchenko, Daria V. Andreeva, Yong-Jin Kim, Hu Young, Jeong, A-Rang Jang, Hyun-Jong Chung, Andre K. Geim

TL;DR
This paper demonstrates the fabrication of vertical single electron tunnelling transistors using combined in-plane and van der Waals heterostructures, specifically integrating graphene quantum dots within hexagonal boron nitride to improve device reproducibility and control.
Contribution
It introduces a novel approach of combining in-plane and van der Waals heterostructures for single electron transistors, utilizing hexagonal boron nitride barriers to enhance reproducibility.
Findings
Reduced localized states along quantum dot perimeters
Reproducible transistors using hexagonal boron nitride barriers
Enhanced device design flexibility
Abstract
Despite a rich choice of two-dimensional materials, which exists these days, heterostructures, both vertical (van der Waals) and in-plane, offer an unprecedented control over the properties and functionalities of the resulted structures. Thus, planar heterostructures allow p-n junctions between different two-dimensional semiconductors and graphene nanoribbons with well-defined edges; and vertical heterostructures resulted in the observation of superconductivity in purely carbon-based systems and realisation of vertical tunnelling transistors. Here we demonstrate simultaneous use of in-plane and van der Waals heterostructures to build vertical single electron tunnelling transistors. We grow graphene quantum dots inside the matrix of hexagonal boron nitride, which allows a dramatic reduction of the number of localised states along the perimeter of the quantum dots. The use of hexagonal…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
