@inproceedings{d471ef96450445cdacb887ac2933236a,
title = "A high sensitivity MEMS gravimeter with electrically tunable stiffness",
abstract = "This paper reports on a high sensitivity capacitive micro-electromechanical systems (MEMS) gravimeter. The high sensitivity is achieved by the low resonant frequency structure and large sensing capacitance. An electrical tuning method was employed to reduce the stiffness. The resulting resonance frequency was as small as 1Hz. To attain the large capacitance, a through-silicon Deep-RIE method was applied to a 525μm thick silicon layer. A cascaded demodulation method is adopted in the readout circuit. This capacitive gravimeter demonstrated a sensitivity of 293 pF/g. The voltage sensitivity is 0.96 VGal. The gravimeter has a noise floor of 0.8μ Gal Hz.",
keywords = "MEMS, electrical tuning, gravimeter",
author = "Chengzhi Yi and Jun Wu and Tamio Ikehashi",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 11th IEEE International Symposium on Inertial Sensors and Systems, INERTIAL 2024 ; Conference date: 25-03-2024 Through 28-03-2024",
year = "2024",
doi = "10.1109/INERTIAL60399.2024.10502072",
language = "English",
series = "INERTIAL 2024 - 11th IEEE International Symposium on Inertial Sensors and Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "INERTIAL 2024 - 11th IEEE International Symposium on Inertial Sensors and Systems, Proceedings",
}