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Numerous reports have elucidated the importance of mechanical resonators comprising quantum-dot-embedded carbon nanotubes (CNTs) for studying the effects of single-electron transport. However, there is a need to investigate the single-electron transport that drives a large amplitude into a nonlinear regime. Herein, a CNT hybrid device has been investigated, which comprises a gate-defined quantum dot that is embedded into a mechanical resonator under strong actuation conditions. The Coulomb peak positions synchronously oscillate with the mechanical vibrations, enabling a single-electron "chopper" mode. Conversely, the vibration amplitude of the CNT versus its frequency can be directly visualized via detecting the time-averaged single-electron tunneling current. To understand this phenomenon, a general formula is derived for this time-averaged single-electron tunneling current, which agrees well with the experimental results. By using this visualization method, a variety of nonlinear motions of a CNT mechanical oscillator have been directly recorded, such as Duffing nonlinearity, parametric resonance, and double-, fractional-, mixed- frequency excitations. This approach opens up burgeoning opportunities for investigating and understanding the nonlinear motion of a nanomechanical system and its interactions with electron transport in quantum regimes.

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Publication history
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Acknowledgements

Publication history

Received: 12 August 2020
Revised: 08 October 2020
Accepted: 08 October 2020
Published: 30 October 2020
Issue date: April 2021

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature

Acknowledgements

This work was supported by the National Key Research and Development Program of China (Nos. 2018YFA0208400 and 2018YFA0306102), the National Natural Science Foundation of China (Nos. 11904014, 51727805, 91836102 and 61704164), the China Postdoctoral Science Foundation (Nos. 2018M641152 and BX20180022), the Beijing Advanced Innovation Center for Future Chips (ICFC), and the Beijing Advanced Innovation Centre for Big Data and Brain Computing (BDBC).

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