Graphene resonant sensors have shown strong competitiveness with respect to sensitivity and size. To advance the applications of graphene resonant sensors, the damage behaviors of graphene harmonic oscillators after thermal annealing and laser irradiation were investigated by morphology analysis and frequency domain vibration characteristics. The interface stress was proven to be the key factor that directly affected the yield of resonators. The resulting phenomenon could be improved by appropriately controlling the annealing temperature and size of resonators, thereby achieving membrane intactness of up to 96.4%. However, micro-cracks were found on the graphene sheets when continuous wave (CW) laser power was more than 4 mW. Moreover, the fluctuating light energy would also cause mechanical fatigue in addition to the photothermal effect, and the threshold damage power for the sinusoidally modulated laser was merely 2 mW. In this way, based on the amplitude-frequency surface morphology of the graphene resonator, the thermal time constant of the order of a few microseconds was confirmed to evaluate the damage of the graphene oscillator in situ and in real time, which could be further extended for those resonators using other 2D materials.

This study proposes a high-sensitivity resonant graphene accelerometer based on a pressure-induced sensing mechanism. The accelerometer design encompasses an optical fiber and a vacuum-sealed graphene resonator affixed to a silicon sensitive film, incorporating a proof mass. This indirect sensing mechanism effectively mitigates the vibration mode aliasing of graphene and the proof mass while ensuring a minimal energy loss in the operating resonator. The mechanical vibration of graphene is excited and detected through an all-fiber optical system. Notably, the proposed sensor demonstrates a sensitivity of 34.3 kHz/g within the range of 0–3.5 g, which is eight times higher than comparable accelerometers utilizing a proof mass on a graphene membrane. This work exhibits a novel, to the best of our knowledge, approach to an acceleration measurement using 2D resonators, exhibiting distinct advantages in terms of compact size and heightened sensitivity.

A miniature high-sensitivity Fabry-Perot (F-P) resonant pressure sensor was developed by transferring multilayer graphene (MLG) onto a copper mesh with a bore diameter of 20 μm. The resonance of graphene membrane suspended and clamped on the copper mesh was opto-thermally excited and detected via optical fiber F-P interference. The measured resonant behaviors showed that the sensor achieved a maximum resonant frequency of 1.11 MHz with a good sensitivity of 10.4 kHz/kPa in the tested range of 0.01 to 50 kPa, which is much higher than that of common silicon resonant pressure sensor with a normal sensitivity of 0.1-0.4 kHz/kPa. Also, the output stability within 4200 seconds demonstrated an extremely low frequency deviation of 0.18% at 6 mW of optical power and 0.16% at 5 mW of optical power, thereby verifying a great potential in highly sensitive pressure measurement.

In consideration of the presented optical-thermally excited resonant mass detection scheme, molecular dynamics calculations are performed to investigate the thermal actuation and resonant mass sensing mechanism. The simulation results indicate that an extremely high temperature exists in a 6% central area of the graphene sheet exposed to the exciting laser. Therefore, constraining the laser driving power and enlarging the laser spot radius are essential to weaken the overheating in the middle of the graphene sheet, thus avoiding being burned through. Moreover, molecular dynamics calculations demonstrate a mass sensitivity of 214 kHz/zg for the graphene resonator with a pre-stress of 1 GPa. However, the adsorbed mass would degrade the resonant quality factor from 236 to 193. In comparison, the sensitivity and quality factor could rise by 1.3 and 4 times, respectively, for the graphene sheet with a pre-stress of 5 GPa, thus revealing the availability of enlarging pre-stress for better mass sensing performance.