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AlScN coating+High-sensitivity ScAlN piezoelectric MEMS accelerometer via bimorph structure design

Date: 2026-04-11 14:50:05     Hits: 0


This study presents a high-sensitivity, compact MEMS accelerometer based on a Scandium-doped Aluminum Nitride (ScAlN) piezoelectric bimorph cantilever. The device leverages a bimorph configuration with two ScAlN layers connected in parallel and multiple cantilevers connected in series to maximize voltage sensitivity while maintaining natural frequency. Analytical modeling, incorporating the effects of Mo electrodes and composite beam mechanics, predicts that the bimorph structure provides twice the capacitance of a unimorph, offering design freedom to improve signal-to-noise ratio (SNR) without altering the natural frequency.

Finite-element simulations (COMSOL) guide the optimization of cantilever length, proof mass coverage, and number of series-connected cantilevers, resulting in an optimized design with eight cantilevers in a 1.1 mm × 1.1 mm back-cavity area. The simulated natural frequency is 1364 Hz, and voltage sensitivity is maximized under capacitance constraints (Figures 4–6, pages 9–10).

Fabrication employs multi-layer deposition of Mo/ScAlN/Mo/ScAlN/Mo stacks, Al proof mass deposition, via formation, and backside DRIE release (Figure 7, page 11). Devices were characterized using a vibration shaker, reference accelerometer, and pre-amplifier readout, with capacitance and voltage sensitivity measured across 10–300 Hz. Experimental results confirm that the bimorph configuration maintains the same natural frequency as unimorph cantilevers while doubling capacitance, validating the theoretical model (Figures 8–10, pages 11–13).

The final device achieves a sensitivity of 12.94 mV g⁻¹ at 300 Hz and area-normalized sensitivity of 10.69 mV g⁻¹ mm⁻², outperforming comparable unimorph devices. The study demonstrates that bimorph ScAlN cantilever structures provide a high-performance solution for space-limited and low-frequency vibration monitoring applications, with practical implications for industrial machinery fault detection and structural health monitoring.


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