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.

Structural, Electrical, And Optical Properties Of Inasxsb1-X Epitaxial Films Grown By Liquid-Phase Epitaxy

The InAsxSb1-x films were grown on (100) GaSb substrates by liquid-phase epitaxy, and their structural, electrical, and optical properties were investigated. The high-resolution x-ray diffraction results reveal that the single crystalline InAsxSb1-x films with a midrange composition are epitaxially grown on the GaSb substrates. Temperature dependence of the Hall mobility was theoretically modeled by considering several predominant scattering mechanisms. The results indicate that ionized impurity and dislocation scatterings dominate at low temperatures, while polar optical phonon scattering is important at room temperature (RT). Furthermore, the InAsxSb1-x films with the higher As composition exhibit the better crystalline quality and the higher mobility. The InAs0.35Sb0.65 film exhibits a Hall mobility of 4.62x10(4) cm(2) V-1 s(-1). The cutoff wavelength of photoresponse is extended to about 12 mu m with a maximum responsivity of 0.21 V/W at RT, showing great potential for RT long-wavelength infrared detection. (C) 2008 American Institute of Physics. [DOI: 10.1063/1.2989116]

Experimental Observation Of Electrical Instability Of Droplets On Dielectric Layer

Polydimethylsiloxane ( PDMS) has become the most widely used silicon-based organic polymer in bio-MEMS/NEMS devices. However, the inherent hydrophobic nature of PDMS hinders its wide applications in bio-MEMS/NEMS for efficient transport of liquids. Electrowetting is a useful tool to reduce the apparent contact angle of partially wetting conductive liquids and has been utilized widely in bio-MEMS/NEMS. Our experimental results show that the thin PDMS membranes exhibit good properties in electrowetting-on-dielectric. The electrical instability phenomenon of droplets was observed in our experiment. The sessile droplet lying on the PDMS membrane will lose its stability with the touch of the wire electrode to make the apparent contact angle change suddenly larger than 35 degrees. Contact mode can protect the dielectric layer from electrical breakdown effectively. Electrical breakdown process of dielectric layer was recorded by a high speed camera. It is found experimentally that a PDMS membrane of 4.8 mu m thick will not be destroyed due to the electric breakdown even at 800 V in the contact mode.

The vector fields admitting one-parameter spatial symmetry group and their reduction

For a n-dimensional vector fields preserving some n-form, the following conclusion is reached by the method of Lie group. That is, if it admits an one-parameter, n-form preserving symmetry group, a transformation independent of the vector field is constructed explicitly, which can reduce not only dimesion of the vector field by one, but also make the reduced vector field preserve the corresponding ( n - 1)-form. In partic ular, while n = 3, an important result can be directly got which is given by Me,ie and Wiggins in 1994.

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.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

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.