Methods for enhanced electrical transduction and characterization of micromechanical resonators

This paper details the design and enhanced electrical transduction of a bulk acoustic mode resonator fabricated in a commercial foundry MEMS process utilizing 2.5 μm gaps. The I-V characteristics of electrically addressed silicon resonators are often dominated by capacitive parasitics, inherent to hybrid technologies. This paper benchmarks a variety of drive and detection principles for electrostatically driven square-extensional mode resonators operating in air via analytical models accompanied by measurements of fabricated devices with the primary aim of enhancing the ratio of the motional to feedthrough current at nominal operating voltages. In view of ultimately enhancing the motional to feedthrough current ratio, a new detection technique that combines second harmonic capacitive actuation and piezoresistive detection is presented herein. This new method is shown to outperform previously reported methods utilizing voltages as low as ±3 V in air, providing a promising solution for low voltage CMOS-MEMS integration. To elucidate the basis of this improvement in signal output from measured devices, an approximate analytical model for piezoresistive sensing specific to the resonator topology reported here is also developed and presented. © 2010 Elsevier B.V. All rights reserved.

Enhanced transduction methods for electrostatically driven MEMS resonators

Electrically addressed silicon bulk acoustic wave microresonators offer high Q solutions for applications in sensing and signal processing. However, the electrically transduced motional signal is often swamped by parasitic feedthrough in hybrid technologies. With the aim of enhancing the ratio of the motional to feedthrough current at nominal operating voltages, this paper benchmarks a variety of drive and detection principles for electrostatically driven square-extensional mode resonators operating in air and in a foundry MEMS process utilizing 2μm gaps. A new detection technique, combining second harmonic capacitive actuation and piezoresistive detection, outperforms previously reported methods utilizing voltages as low as ± 3V in air providing a promising solution for low voltage CMOS-MEMS integration. ©2009 IEEE.

An overview of sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, are numerical techniques based on Importance Sampling for solving the optimal state estimation problem. The task of calibrating the state-space model is an important problem frequently faced by practitioners and the observed data may be used to estimate the parameters of the model. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed for this task accompanied with a discussion of their advantages and limitations.