journal article·2019-01-01

Vibration detection schemes based on absorbance tuning in monolayer molybdenum disulfide mechanical resonators

Fengnan Chen, Chen Yang, Wenjing Mao, Heng Lu, Kevin G Schädler, Antoine Reserbat-Plantey, Johann Osmond, Guoyang Cao, Xiaofeng Li, Chinhua Wang, Ying Yan, Joel Moser

2D Materials· Volume 6· Issue 1
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Abstract

Abstract Mechanical resonators based on monolayer molybdenum disulfide, a two-dimensional semiconductor, offer the possibility of harnessing light-matter interaction to develop sensitive detection schemes. These schemes consist in measuring fluctuations in the mechanical response of the resonator, such as fluctuations of its displacement spectrum, induced by minute changes in its environment. The accuracy of detecting such changes depends on how accurately the temperature of vibrations is known. However, using light to measure the mechanical response modifies vibrational temperature, making this detection challenging. We propose two complementary detection schemes that may enable us to measure the response of the resonator optically with optimal accuracy. The first scheme is based on minimizing the absorbance of the monolayer while ensuring that the reflectance of the resonator strongly varies with displacement. This scheme minimizes absorptive heating of the monolayer and optomechanical cooling and heating of its flexural vibrations, while preserving the capability of using reflectometry to detect vibrations. The second scheme is based on maximizing the derivative of the absorbance with respect to monolayer displacement. This scheme utilizes the modulation of absorbed energy and may relate modulations of photoluminescence intensity to the modulations of displacement. Both schemes can be controlled by tuning the equilibrium position of the monolayer using electrostatic pressure.
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Research context

OpenAlex topics: Mechanical and Optical Resonators · Photonic and Optical Devices · Advanced Fiber Laser Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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