High tuning range AlSi RF MEMS capacitors fabricated with sacrificial amorphous silicon surface micromachining

This paper reports the fabrication and electrical characterization of high tuning range AlSi RF MEMS capacitors. We present experimental results obtained by a surface micromachining process that uses dry etching of sacrificial amorphous silicon to release Al-1%Si membranes and has a low thermal budget (<450 °C) being compatible with CMOS post-processing. The proposed silicon sacrificial layer dry etching (SSLDE) process is able to provide very high Si etch rates (3-15 μm/min, depending on process parameters) with high Si: SiO2 selectivity (>10,000:1). Single- and double-air-gap MEMS capacitors, as well as some dedicated test structures needed to calibrate the electro-mechanical parameters and explore the reliability of the proposed technology, have been fabricated with the new process. S-parameter measurements from 100 MHz up to 2 GHz have shown a capacitance tuning range higher than 100% with the double-air-gap architecture. The tuning range can be enlarged with a proper DC electrical bias of the capacitor electrodes. Finally, the reported results make the proposed MEMS tuneable capacitor a good candidate for above-IC integration in communications applications. © 2004 Elsevier B.V. All rights reserved.

Effects of mechanical and electrical coupling on the parametric sensitivity of mode localized sensors

We compare and contrast the effects of two distinctly different mechanisms of coupling (mechanical and electrical) on the parametric sensitivity of micromechanical sensors utilizing mode localization for sensor applications. For the first time, the strong correlation between mode localization and the phenomenon of 'eigenvalue loci-veering' is exploited for accurate quantification of the strength of internal coupling in mode localized sensors. The effects of capacitive coupling-spring tuning on the parametric sensitivity of electrically coupled resonators utilizing this sensing paradigm is also investigated and a mass sensor with sensitivity tunable by over 400% is realized. ©2009 IEEE.

Tailoring the electrical properties of carbon nanotube-polymer composites

Advances in functionality and reliability of nanocomposite materials require careful formulation of processing methods to ultimately realize the desired properties. An extensive study of how the variation in fabrication process would affect the mechanism of conductivity and thus the final electrical properties of the carbon nanotube-polymer composite is presented. Some of the most widely implemented procedures are addressed, such as ultrasonication, melt shear mixing, and addition of surfactants. It is hoped that this study could provide a systematic guide to selecting and designing the downstream processing of carbon nanocomposites. Finally, this guide is used to demonstrate the fabrication and performance of a stretchable (pliable) conductor that can reversibly undergo uniaxial strain of over 100%, and other key applications are discussed. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Parasitic feedthrough cancellation techniques for enhanced electrical characterization of electrostatic microresonators

Capacitive parasitic feedthrough is an impediment that is inherent to all electrically interfaced micron scale resonant devices, resulting in increased challenges to their integration in more complex circuits, particularly as devices are scaled to operate at higher frequencies for RF applications. In this paper, a technique to cancel the undesirable effects of capacitive feedthrough that was previously proposed is here developed for an on-chip implementation. The method reported in this paper benefits from the simplicity of its implementation, and its effectiveness is demonstrated in this paper. This technique is demonstrated for two disk-plate resonators that have been excited in the wine glass mode at 5.4 MHz, though applicable to almost any electrically interfaced resonator. Measurements of the electrical transmission from these resonators show that the magnitude of the frequency response of the system is enhanced by up to 19 dB, while the phase is found to shift through a full 180° about the resonant frequency. This method is proposed as a useful addition to other techniques for enhancing the measured response of electrostatic micromechanical resonators. © 2009 Elsevier B.V. All rights reserved.

Fabrication and electrical characteristics of carbon nanotube-based microcathodes for use in a parallel electron-beam lithography system

The development of the Nanolith parallel electron-beam writing head was discussed. The fabrication and electrical characteristics of carbon nanotube-based microcathodes for use in the lithographic system were described. The microcathode exhibited a peak current of 10.5 μA at 48 V when operated with a duty cycle of 0.5 percent.

Electrical and field emission investigation of individual carbon nanotubes from plasma enhanced chemical vapour deposition

Plasma enhanced chemical vapour deposition (PECVD) is a controlled technique for the production of vertically aligned multiwall carbon nanotubes for field emission applications. In this paper, we investigate the electrical properties of individual carbon nanotubes which is important for designing field emission devices. PECVD nanotubes exhibit a room temperature resistance of 1-10 kΩ/μm length (resistivity 10-6 to 10-5 Ω m) and have a maximum current carrying capability of 0.2-2 mA (current density 107-108 A/cm2). The field emission characteristics show that the field enhancement of the structures is strongly related to the geometry (height/radius) of the structures and maximum emission currents of ∼ 10 μA were obtained. The failure of nanotubes under field emission is also discussed. © 2002 Elsevier Science B.V. All rights reserved.

Parameter Estimation for Hidden Markov Models with Intractable Likelihoods

Approximate Bayesian computation (ABC) is a popular technique for analysing data for complex models where the likelihood function is intractable. It involves using simulation from the model to approximate the likelihood, with this approximate likelihood then being used to construct an approximate posterior. In this paper, we consider methods that estimate the parameters by maximizing the approximate likelihood used in ABC. We give a theoretical analysis of the asymptotic properties of the resulting estimator. In particular, we derive results analogous to those of consistency and asymptotic normality for standard maximum likelihood estimation. We also discuss how sequential Monte Carlo methods provide a natural method for implementing our likelihood-based ABC procedures.

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.

Sequential Monte Carlo computation of the score and observed information matrix in state-space models with application to parameter estimation

Sequential Monte Carlo (SMC) methods are popular computational tools for Bayesian inference in non-linear non-Gaussian state-space models. For this class of models, we propose SMC algorithms to compute the score vector and observed information matrix recursively in time. We propose two different SMC implementations, one with computational complexity $\mathcal{O}(N)$ and the other with complexity $\mathcal{O}(N^{2})$ where $N$ is the number of importance sampling draws. Although cheaper, the performance of the $\mathcal{O}(N)$ method degrades quickly in time as it inherently relies on the SMC approximation of a sequence of probability distributions whose dimension is increasing linearly with time. In particular, even under strong \textit{mixing} assumptions, the variance of the estimates computed with the $\mathcal{O}(N)$ method increases at least quadratically in time. The $\mathcal{O}(N^{2})$ is a non-standard SMC implementation that does not suffer from this rapid degrade. We then show how both methods can be used to perform batch and recursive parameter estimation.