&lt;title&gt;Environmental test bench for reliability studies: influence of the temperature on rf switches with metallic membranes&lt;/title&gt;

Lafontan, Xavier; Touze, Christophe Le; Wenk, B.; Kolesnik, Inna; Pressecq, F.; Perez, Guy; Nicot, Jean-Marc; Dardalhon, M.; Rigo, Sebastien

doi:10.1117/12.462864

Cited by 18 publications

(11 citation statements)

References 2 publications

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“…Due to their electrical and mechanical nature, MEMS devices traditionally have been analyzed in both electrical and mechanical domains [5][6][7]. Coupling between the two domains was achieved using empirical/analytical expressions or via full-wave analysis.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network modeling of RF MEMS resonators

Lee

Park

Niu

et al. 2004

Int J RF and Microwave Comp Aid Eng

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In this article, a novel and efficient approach for modeling radio-frequency microelectromechanical system (RF MEMS) resonators by using artificial neural network (ANN) modeling is presented. In the proposed methodology, the relationship between physical-input parameters and corresponding electrical-output parameters is obtained by combined circuit/full-wave/ANN modeling. More specifically, in order to predict the electrical responses from a resonator, an analytical representation of the electrical equivalent-network model (EENM) is developed from the well-known electromechanical analogs. Then, the reduced-order, nonlinear, dynamic macromodels from 3D finite-element method (FEM) simulations are generated to provide training, validating, and testing datasets for the ANN model. The developed ANN model provides an accurate prediction of an electrical response for various sets of driving parameters and it is suitable for integration with an RF/microwave circuit simulator. Although the proposed approach is demonstrated on a clamped-clamped (C-C) beam resonator, it can be readily adapted for the analysis of other micromechanical resonators.

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Section: Introductionmentioning

confidence: 99%

Artificial neural network modeling of RF MEMS resonators

Lee

Park

Niu

et al. 2004

Int J RF and Microwave Comp Aid Eng

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“…In applications where significant temperature variations are expected, such as in aircraft condition monitoring and distributed satellites communication, as well as during device packaging [Mercado et al, 2003;, the effect of temperature on the device performance is a major concern. Lafontan et al have reported on the effects of temperature on MEMS switches pull-in voltage [Lafontan et al, 2002]. This study shows that a moderate temperature increase may cause buckling of the switch structure, leading to premature failure of the device.…”

Section: Introductionmentioning

confidence: 89%

Mechanical Behavior of a Bi-Layer Cantilever Micro-Beam Subjected to Electrostatic Force, Mechanical Shock and Thermal Moment

Rezazadeh

Pashapour

Abdolkarimzadeh

2011

Int. J. Appl. Mechanics

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In the present work, we study the static and dynamic behavior of a bi-layer cantilever micro-beam and its pull-in instability subjected to simultaneous effects of thermal moment, electrostatic force and mechanical shock. The nonlinear governing equation in the static case has been linearized using a Step-by-Step Linearization Method (SSLM) and the resulted linear equation has been solved using a Finite Difference Method (FDM). The obtained results for some cases have been compared to the existing results and good agreement achieved. The dynamic response of the system owing to application of a mechanical shock and a step DC voltage for thermally actuated micro-beam have been accomplished by a partial differential equation. A Reduced-Order Model (ROM) has been used to simulate the dynamic behavior of the micro-beam. The effects of temperature changes and mechanical shock on the pull-in behavior have been studied and obtained results show an earlier pull-in phenomenon experience when these effects are considered.

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“…It has been reported that a moderate temperature increase may cause buckling of the switch structure, which leads to a premature failure of the device. On the other hand, temperature reduction could result in a significant increase of the pull-in voltage, which is undesirable [5]. Therefore, it is relevant to design a switch with a structure and materials that are almost insensitive to temperature variations.…”

Section: Introductionmentioning

confidence: 98%

Reliability of capacitive RF MEMS switches at high and low temperatures

Zhu

Espinosa

2004

Int J RF and Microwave Comp Aid Eng

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Some applications of RF MEMS switches, such as aircraft condition monitoring and distributed satellite communication, present a unique challenge for device design and reliability. This article examines these switches when operational temperatures in the range ؊60°C to 100°C are envisioned. The basic operation of a capacitive MEMS switch is described and two tools for examining device reliability, modeling, and on-chip experimentation, are discussed in the case of capacitive MEMS switches. 1D, 2D, and 3D models are presented with emphasis on 3D coupled-field finite-element analysis, including temperature effects. Results and findings from the 3D simulations are reported. In particular, the advantages of employing corrugated membranes in the design of RF MEMS switches are assessed. Their performance in terms of reliability as a function of temperature is quantified. The effects of corrugation on the geometric parameters are discussed in the context of device-design optimization. In order to assess reliability experimentally, the M-test and the membrane deflection experiment (MDE) are reviewed due to their on-chip characteristic and simplicity. Ways in which these experimental/computational methodologies can be combined for identifying material properties and device performance is also highlighted.

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<title>Environmental test bench for reliability studies: influence of the temperature on rf switches with metallic membranes</title>

Cited by 18 publications

References 2 publications

Artificial neural network modeling of RF MEMS resonators

Artificial neural network modeling of RF MEMS resonators

Mechanical Behavior of a Bi-Layer Cantilever Micro-Beam Subjected to Electrostatic Force, Mechanical Shock and Thermal Moment

Reliability of capacitive RF MEMS switches at high and low temperatures

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