Numerical Models for the Optimal Synthesis of MicroElectroMechanical Systems (MEMS)

Dear Colleagues,

The Special Issue presents a broad overview of methods of both the analysis and synthesis of micro electro mechanical systems (MEMS) and devices, mainly addressed to scientists in the area of electrical and computer engineering as well as mechatronics.

A categorization commonly accepted of MEMS devices is based on the inherent physical principle exploited for actuation or sensing. Electrical actuation is the most common and the oldest one. In fact, capacitive transduction, coupled with electrostatic actuation, is used in many applications such as pressure sensors, micromotors, accelerometers, gyroscopes, and energy harvesters. In particular, pressure sensors became the first mass-produced MEMS device around 1995. On the other hand, electrostatic micromotors were the first devices to be designed and prototyped, exploiting silicon-integrated technology as early as the late 1980s.

In turn, thermal actuation is usually coupled with electrical actuation: usually, the conduction current overheats a structural component of the device thanks to the Joule effect; then, the gradient of temperature gives rise to a strain and, finally, to a displacement. This kind of electro-thermo-elastic device is interesting from the point of view of complex models because of its coupled-field behavior.

Finally, magnetic actuation offers technological advantages. For example, low voltages are needed for power supply, hence power loss is low; moreover, they are simple to control because of their linear response to the input signal. Even if they appear not to be used very extensively, magnetic MEMS fill some important niches in mechatronics, e.g., for those applications that need large force densities and broad strokes.

From the modelling viewpoint, it follows that multi-physics problems, characterized by the interaction of at least two physical domains, have to be considered: a set of coupled non-linear equations arises; in turn, single-physics problems consider a physical domain that is assumed to be only one, or the most important one, characterizing MEMS behavior.

Simulating a MEMS device by solving an analysis problem is essential to understand its behavior; nevertheless, the optimal synthesis of MEMS is a fascinating challenge that requires the solving of an inverse problem by means of methods of automated optimal design such as evolutionary computing algorithms, which, in turn, exploit a sequence of analysis problems to be iteratively solved. In order to solve analysis problems in a numerical fashion, many methods can be used: field models, circuit models, object-oriented models, and neural networks are just a few examples of approaches widely used in the community. Moreover, measurement-based models can be helpful, e.g., to validate numerical models of complex physical devices.

Because of the multidisciplinary nature of the covered topics, the skills of different authors acting in different areas of science and technology are definitely needed, and relevant contributions are welcome.

Prof. Paolo Di Barba
Dr. Maria Evelina Mognaschi
Prof. Sławomir Wiak
Guest Editors

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• MEMS devices and systems
• Analytical models
• Neural network models
• Field-circuit models
• Finite-element analysis
• Inverse problems
• Multiobjective optimization
• Evolutionary computing
• Object-oriented modelling
• Dynamic behavior of MEMS.