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Updated: Oct 4, 2025

A Standard and Reliable Method to Fabricate Two-Dimensional Nanoelectronics
Published on: August 28, 2018
Strain-Modulated Dissipation in Two-Dimensional Molybdenum Disulfide Nanoelectromechanical Resonators
Pengcheng Zhang1, Yueyang Jia1, Maosong Xie1
1University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China.
Abstract:
Resonant nanoelectromechanical systems (NEMS) based on two-dimensional (2D) materials such as molybdenum disulfide (MoS2) are interesting for highly sensitive mass, force, photon, or inertial transducers, as well as for fundamental research approaching the quantum limit, by leveraging the mechanical degree of freedom in these atomically thin materials. For these mechanical resonators, the quality factor (Q) is essential, yet the mechanism and tuning methods for energy dissipation in 2D NEMS resonators have not been fully explored. Here, we demonstrate that by tuning static strain and vibration-induced strain in suspended MoS2 using gate voltages, we can effectively tune the Q in 2D MoS2 NEMS resonators. We further show that for doubly clamped resonators, the Q increases with larger DC gate voltage, while fully clamped drumhead resonators show the opposite trend. Using DC gate voltages, we can tune the Q by ΔQ/Q = 448% for fully clamped resonators, and by ΔQ/Q = 369% for doubly clamped resonators. We develop the strain-modulated dissipation model for these 2D NEMS resonators, which is verified against our measurement data for 8 fully clamped resonators and 7 doubly clamped resonators. We find that static tensile strain decreases dissipation while vibration-induced strain increases dissipation, and the actual dependence of Q on DC gate voltage depends on the competition between these two effects, which is related to the device boundary condition. Such strain dependence of Q is useful for optimizing the resonance linewidth in 2D NEMS resonators toward low-power, ultrasensitive, and frequency-selective devices for sensing and signal processing.
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