4.8 Article

Engineering of Numerous Moire Superlattices in Twisted Multilayer Graphene for Twistronics and Straintronics Applications

期刊

ACS NANO
卷 15, 期 7, 页码 12358-12366

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.1c04286

关键词

Moire materials; twisted multilayer graphene (tMLG); twistronics; STM; big data applications; transport properties; 2D nanoelectronics

资金

  1. Ministry of Science and Higher Education of the Russian Federation [075-15-2020-791]

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Researchers have successfully synthesized twisted multilayer graphene with a large number of monolayers, observing the two-dimensional nature of electron transport and high carrier mobility. The presence of multiple Moire superlattices poses a challenge for the production of next-generation devices for nanoelectronics and computing applications.
Because of their unique atomic structure, 2D materials are able to create an up-to-date paradigm in fundamental science and technology on the way to engineering the band structure and electronic properties of materials on the nanoscale. One of the simplest methods along this path is the superposition of several 2D nanomaterials while simultaneously specifying the twist angle between adjacent layers (theta), which leads to the emergence of Moire superlattices. The key challenge in 2D nanoelectronics is to obtain a nanomaterial with numerous Moire superlattices in addition to a high carrier mobility in a stable and easy-to-fabricate material. Here, we demonstrate the possibility of synthesizing twisted multilayer graphene (tMLG) with a number of monolayers N-L = 40-250 and predefined narrow ranges of theta = 3-8 degrees, theta = 11-15 degrees, and theta = 26-30 degrees. A 2D nature of the electron transport is observed in the tMLG, and its carrier mobilities are close to those of twisted bilayer graphene (tBLG) (with. = 30 degrees) between h-BN layers. We demonstrate an undoubtful presence of numerous Moire superlattices simultaneously throughout the entire tMLG thickness, while the periods of these superlattices are rather close to each other. This offers a challenge of producing a next generation of devices for nanoelectronics, twistronics, and neuromorphic computing for large data applications.

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