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  5. Gate-Switchable Molecular Diffusion on a Graphene Field-Effect Transistor

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Article
en
2024

Gate-Switchable Molecular Diffusion on a Graphene Field-Effect Transistor

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0 Files

en
2024
Vol 18 (35)
Vol. 18
DOI: 10.1021/acsnano.4c05808

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Kenji Watanabe
Kenji Watanabe

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Franklin Liou
Hsin‐Zon Tsai
Zachary A. H. Goodwin
+16 more

Abstract

Controlling the surface diffusion of particles on 2D devices creates opportunities for advancing microscopic processes such as nanoassembly, thin-film growth, and catalysis. Here, we demonstrate the ability to control the diffusion of F4TCNQ molecules at the surface of clean graphene field-effect transistors (FETs) via electrostatic gating. Tuning the back-gate voltage (VG) of a graphene FET switches molecular adsorbates between negative and neutral charge states, leading to dramatic changes in their diffusion properties. Scanning tunneling microscopy measurements reveal that the diffusivity of neutral molecules decreases rapidly with a decreasing VG and involves rotational diffusion processes. The molecular diffusivity of negatively charged molecules, on the other hand, remains nearly constant over a wide range of applied VG values and is dominated by purely translational processes. First-principles density functional theory calculations confirm that the energy landscapes experienced by neutral vs charged molecules lead to diffusion behavior consistent with experiment. Gate-tunability of the diffusion barrier for F4TCNQ molecules on graphene enables graphene FETs to act as diffusion switches.

How to cite this publication

Franklin Liou, Hsin‐Zon Tsai, Zachary A. H. Goodwin, Yiming Yang, Andrew S. Aikawa, Brian R. P. Angeles, Sergio Pezzini, Luc Nguyen, Sergey Trishin, Zhichao Cheng, Shizhe Zhou, Paul W. Roberts, Xiaomin Xu, Kenji Watanabe, Takashi Taniguchi, V. Bellani, Feng Wang, Johannes Lischner, Michael F. Crommie (2024). Gate-Switchable Molecular Diffusion on a Graphene Field-Effect Transistor. , 18(35), DOI: https://doi.org/10.1021/acsnano.4c05808.

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Publication Details

Type

Article

Year

2024

Authors

19

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.4c05808

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