What is MEMS smart sensor technology like?

Last Update Time: 2023-08-29 18:10:02

MEMS pressure smart sensor

Because piezoelectric sensing MEMS resonators have the characteristics of self-driving and self-sensing, ultra-low driving voltage, low power consumption, and circuit impedance matching, it is more attractive than other modes such as electromagnetic resonance to integrate into network sensing systems. However, the figure of merit (Q) of the piezoelectric sensing MEMS resonator needs to be improved. In 2008, J. Lu et al. reported a high-Q monocrystalline silicon cantilever compatible with CMOS, which is used for ultra-sensitive quality inspection with a chip integrated piezoelectric driver. CMOS compatible monocrystalline silicon cantilever beams with on-chip integrated piezoelectric lead zirconate titanate (PZT) drivers are used for sensitive quality inspection. The design of separating the PZT driver can successfully suppress the dissipated energy and other negative effects on the PZT film. The gauge of the integrated varistor Wheatstone bridge detects the resonant frequency for better integration and compatibility with CMOS circuits. The test results show that the Q value of a cantilever with a width of 30um and a length of 100um is 1 115, which is several times higher than the Q value of the reported integrated micro cantilever.

The development of nano-scale sensing structures such as carbon nanotubes (CNT), graphene and nanowires for pressure sensors has become one of the important development directions. These sensors exhibit novel sensitivity, rapid response and high spatial resolution.  Carbon nanotubes have small size (1-100nm in diameter), good electrical and mechanical properties.

In 2015, A. Gafar et al. reported a MEMS piezoresistive pressure sensor based on carbon nanotubes. The CNT-based MEMS piezoresistive pressure sensor formed by the electrophoretic micro-assembly process successfully integrates the CNT sensing elements in the polymethyl methacrylate (PMMA) diaphragm array. The simulation results show that the biocompatibility and low Cost application requirements, it can replace silicon pressure sensors. Graphene oxide is a very important derivative of graphene, a two-dimensional crystal with good mechanical, thermal and electrical properties. Graphene oxide foam has excellent elastic properties and relatively high dielectric constant, and it is a new component of wearable electronic devices in the future.

In 2017, S. Wan et al. reported the study of graphene oxide as a high-performance dielectric material for capacitive pressure sensors. The graphene oxide foam is sandwiched between thin polyester layers with pattern electrodes by wet coating, freezing and drying processes to prepare a capacitive pressure sensor using graphene oxide as a high-performance medium. It has high efficiency, Features such as low cost, large area integration and graphics. The sensor can detect a micro pressure of 0.24 Pa, and has a fast response time (about 100 ms) and high sensitivity (about 0.8 kPa⁻¹); its sensitivity is 2 x 10³ higher than that of the polydimethylsiloxane layer. The sensor has good durability (can withstand more than 1000 loading/unloading cycles and more than 1000 bending experiments) and spatial resolution of positioning pressure.

In 2016, H. P. Phan et al. reported on the piezoresistive effect of P-type 3C-SiC nanowires (NW) fabricated from top to bottom. A 3C-SiC thin film with a carrier concentration of 5 x 10¹⁸ was epitaxially grown on a Si substrate, and p-type 3C-SiC nanowires (5um x 300nm x 300nm) were fabricated using focused ion beam technology. The nanowire is used as a varistor in the Wheatstone bridge circuit for tensile stress experiment (0280uɛ). Experimental results show that its measurement factor is 35, which is an order of magnitude higher than that of hard materials such as carbon nanotubes and graphene. SiC NW has a large measurement factor, the linear relationship between the change of related resistance and the applied stress, showing its potential for nanomechanical system sensing.

 

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