Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors

A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (⁠$SNR$⁠) and the limit-of-detection (⁠$LOD$⁠) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate $SNR$ and establish $LOD$ of critical-point flexure sensors. We find that a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved $SNR$ and $LOD$⁠. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.