Kavli Institute of Nanoscience , Delft University of Technology , Lorentzweg 1 , 2628 CJ , Delft , The Netherlands.
Department of Precision and Microsystems Engineering , Delft University of Technology , Mekelweg 2 , 2628 CD , Delft , The Netherlands.
Nano Lett. 2019 Feb 13;19(2):1282-1288. doi: 10.1021/acs.nanolett.8b04862. Epub 2019 Jan 31.
Stochastic switching between the two bistable states of a strongly driven mechanical resonator enables detection of weak signals based on probability distributions, in a manner that mimics biological systems. However, conventional silicon resonators at the microscale require a large amount of fluctuation power to achieve a switching rate in the order of a few hertz. Here, we employ graphene membrane resonators of atomic thickness to achieve a stochastic switching rate of 4.1 kHz, which is 100 times faster than current state-of-the-art. The (effective) temperature of the fluctuations is approximately 400 K, which is 3000 times lower than the state-of-the-art. This shows that these membranes are potentially useful to transduce weak signals in the audible frequency domain. Furthermore, we perform numerical simulations to understand the transition dynamics of the resonator and use analytical expressions to investigate the relevant scaling parameters that allow high-frequency, low-temperature stochastic switching to be achieved in mechanical resonators.
强驱动机械谐振器的两个双稳态之间的随机切换能够基于概率分布来检测弱信号,这种方式类似于生物系统。然而,传统的微尺度硅谐振器需要大量的涨落功率才能达到几赫兹的切换速率。在这里,我们采用原子厚度的石墨烯膜谐振器实现了 4.1 kHz 的随机切换速率,比当前的最先进水平快 100 倍。涨落的(有效)温度约为 400 K,比最先进水平低 3000 倍。这表明这些膜在转换可听频域的弱信号方面具有潜在的应用价值。此外,我们进行了数值模拟以了解谐振器的跃迁动力学,并使用解析表达式研究了相关的标度参数,这些参数允许在机械谐振器中实现高频、低温随机切换。