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MEMS switch, top view

MEMS switch, top view. (Larger image)

Uncertainty models improve system design

Decorative initial cap One of the most promising applications of micro-fabrication technology is in the development of small, ultra-fast mechanical switches called radio-frequency microelectromechanical (RF-MEMS) switches. These switches have applications in radio and communication and, says Assistant Professor Matt Allen, they even could replace transistors in some applications, potentially reducing the power consumption in cell phones and other portable electronic devices.

As is the case with many emerging technologies, researchers must overcome a number of hurdles associated with the micro-switches—not least of which is developing a switch that is durable enough for the applications.

MEMS switch, side view

MEMS switch, side view. (Larger image)

Among those hurdles is switch failure. Based on their tests, researchers at Sandia National Laboratories have suggested that large forces can be developed in the switches if they close too quickly. As a result, the switches fail prematurely.

In soon-to-be published research, Allen and a group of Sandia researchers reveal that fabricators actually can worsen the problem if they don’t pay careful attention to uncertainty and variability in the switches. “The processes used to create these switches lead to significant uncertainties in their dimensions—as one might expect, considering that they are trying to control the thickness of parts that measure only a few microns, or less than a tenth of the diameter of a human hair,” says Allen.

Allen’s group of researchers was charged with predicting the performance of these switches and improving the design. They created a model for the dimensional uncertainty in the switches and then used that model to predict the performance of an ensemble of nominally identical switches. “One key was developing a model that captured the dominant physics, yet could be evaluated quickly so that the performance of hundreds of randomly selected switches could be evaluated,” says Allen.

Matt Allen

Matt Allen (Larger image)

By reducing the computation time of their models from hours to seconds, Allen and his colleagues were able to predict switch performance and explore a number of alternative designs.

The design of these micro-mechanical switches is simple: a thin gold plate held above a set of electrical contacts by four leaf springs. An electrostatic force pulls the plate down to the contacts, closing the circuit. As the plate approaches the contacts, that force becomes stronger and the plate accelerates.

Sandia researchers discovered a strong correlation between switch life and the plate speed as it reaches the electrical contacts. So, the solution seemed simple. Rather than just turning on the voltage that closes the switch, they delivered a voltage pulse that moved the switches just enough that they coasted to an almost-closed position. “Then they would turn on a voltage that was just sufficient to hold the switches there,” says Allen.

The idea works great, he says, if you’re only dealing with one switch with known dimensions. But over hundreds of switches on an array, these critical dimensions vary widely—as well as the distance that the switch has to move. “It’s kind of like landing an airplane and not knowing how far away the ground is,” says Allen.

It turns out that because the voltage shape the designers originally proposed caused only a small fraction of the switches to close softly, the rest would experience even higher forces than they would have if the voltage had not been shaped at all.

To correct that problem, Allen and his colleagues modeled not only the nominal switch, but an ensemble of switches from the manufacturing process, by using random variables for the switch dimensions and properties. “So now, rather than having a switch with thickness t and height above the contacts h, we have random values there,” says Allen.

He and his colleagues reviewed several methods for analyzing this model and settled on creating a model that approximated the physics of the system in known ways, rather than approximating the effect of uncertainty. Because the model was small enough, the group could apply very robust statistical methods that could accurately deal with the complicated, nonlinear system. Then, they ran a simulation of an entire batch of random switches in a matter of minutes, enabling them to test changes—for example, a different design for the switch, or a manufacturing process revision—that might improve the switch design or performance. “We were able to explore different designs and predict, quantitatively how much they would improve the performance,” says Allen.

With Sandia researchers Jordan Massad, Richard Field and Christopher Dyck, Allen is the lead author of a paper about the modeling work that will appear in the Journal of Vibration and Acoustics.

 


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Date last modified: Friday, 4-January-2008 11:49:00 CDT
Date created: 4-January-2008

 

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