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2020 | Book

Introduction Read chapter Read first chapter

MEMS: Field Models and Optimal Design

Authors: Prof. Paolo Di Barba, Prof. Slawomir Wiak

Publisher: Springer International Publishing

Book Series : Lecture Notes in Electrical Engineering

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book highlights numerical models as powerful tools for the optimal design of Micro-Electro-Mechanical Systems (MEMS). Most MEMS experts have a background in electronics, where circuit models or behavioral models (i.e. lumped-parameter models) of devices are preferred to field models. This is certainly convenient in terms of preliminary design, e.g. in the prototyping stage. However, design optimization should also take into account fine-sizing effects on device behavior and therefore be based on distributed-parameter models, such as finite-element models. The book shows how the combination of automated optimal design and field-based models can produce powerful design toolboxes for MEMS. It especially focuses on illustrating theoretical concepts with practical examples, fostering comprehension through a problem-solving approach. By comparing the results obtained using different methods, readers will learn to identify their respective strengths and weaknesses. In addition, special emphasis is given to evolutionary computing and nature-inspired optimization strategies, the effectiveness of which has already been amply demonstrated. Given its scope, the book provides PhD students, researchers and professionals in the area of computer-aided analysis with a comprehensive, yet concise and practice-oriented guide to MEMS design and optimization. To benefit most from the book, readers should have a basic grasp of electromagnetism, vector analysis and numerical methods.

Table of Contents

Frontmatter
1. Introduction
Abstract
This introductory monograph presents a broad overview of methods of both analysis and synthesis of Micro Electro Mechanical Systems (MEMS) and devices, mainly addressed to graduate students and young researchers in the area of electrical and computer engineering as well as mechatronics. Throughout the book each theoretical concept is illustrated by means of case studies, following a problem-solving approach and never forgetting that the engineering task is just that of formulating and solving problems in a computational fashion. Having this in mind, the authors have collected the experience they have accumulated while teaching electromagnetics and electromechanics at various levels and in different countries, in this book, which is intended to be valid for an international audience.
Paolo Di Barba, Slawomir Wiak
2. MEMS Modelling: Distributed versus Lumped Parameter Models
Abstract
The miniaturisation of electromechanical systems is impacting our society as deeply as did the mass production of electronic systems in the last few decades. However, only in more recent times the design of MEMS has been approached in a systematic way, by employing methods and algorithms of automated optimal design (AOD).
Paolo Di Barba, Slawomir Wiak
3. Engineering Electrostatics and Boundary-Value Problems
Abstract
In a domain Ω with boundary Γ, filled in by a dielectric material, in the presence of free electric charges distributed with density ρ(C m−3) in Ω and/or electric charges distributed with density σ(C m−2) along Γ, the electrostatic field is defined by field strength \(\overline{E} ({\text{V m}}^{ - 1} )\) as well as by flux density \(\overline{D} ({\text{C m}}^{ - 2} )\).
Paolo Di Barba, Slawomir Wiak
4. Engineering Magnetostatics and Boundary-Value Problems
Abstract
In a domain Ω, having boundary Γ, containing permanent magnets, i.e. aggregates of magnetic dipoles or, from now on, steady electric current distributed with density \(\overline{J}\) (A m−2), a magnetostatic field is set up; it is defined by field strength \(\overline{H}\) (A m−1) as well as flux density \(\overline{B}\) (Wb m−2 = T).
Paolo Di Barba, Slawomir Wiak
5. Steady Conduction Field and Boundary-Value Problems
Abstract
In a domain Ω, having boundary Γ, filled in by a conducting material, when a voltage—constant with time—is set up across Γ, a steady conduction field originates; it is defined by field strength \(\overline{E}\) (V m−1) and current density \(\overline{J}\) (A m−2).
Paolo Di Barba, Slawomir Wiak
6. From Fields to Circuits
Abstract
In general, the twofold presence of a movable charge distributed with density ρ (Cm-3) and an impressed current density \(\overline{J}_{0}\) (A m−2) variable with time gives origin to the electromagnetic field.
Paolo Di Barba, Slawomir Wiak
7. Device Miniaturization Principles
Abstract
If the size of a mechanical device is reduced by a factor 10, its mass—and, consequently, inertial and gravitational forces—decrease by a factor 103; on the other side, forces depending on the device surface like the electrostatic interaction due to surface charge density, decrease by a factor 102. Therefore, the ratio of the electrostatic forces to the inertial ones increase by a factor 10; this remark stands as one of the main reasons behind the exploitation of electric field for generating motion in a device exhibiting sub-millimetric size.
Paolo Di Barba, Slawomir Wiak
8. Numerical Methods for Field Analysis of MEMS
Abstract
The finite element method has, in recent decades, become by far the most popular technique in computational electromagnetism. Many general purpose computer codes have been developed which provide toolboxes for computer-aided-design (CAD) of devices and systems. The technique is not suitable for hand calculations, and the algorithm is somewhat complicated; nevertheless, the formulation of the simplest two-dimensional case shall be followed to demonstrate the principle and to clarify some aspects of the applications.
Paolo Di Barba, Slawomir Wiak
9. Coupled Fields: Multi-physics Analysis of MEMS
Abstract
When investigating the behaviour of a MEMS device, it might be necessary to model different physical domains which co-exist and interact in the same materials. The relevant analysis implies to solve a system of partial derivative equations, the unknowns of which are time-varying fields acting in the region under study. This is a general concept of coupled-field problem, sometimes referred to as a multiphysics field problem.
Paolo Di Barba, Slawomir Wiak
10. Numerical Methods for MEMS Design: Inverse Problems
Abstract
In engineering science, direct problems are defined as those where, given the input or the cause of a phenomenon or of a process in a device, the purpose is that of finding the output or the effect.
Paolo Di Barba, Slawomir Wiak
11. Numerical Methods for MEMS Design: Automated Optimization
Abstract
As stated in Sect. 10.​3, the problem of identifying or reconstructing a given quantity, based on known data e.g. measurements, is called an inverse problem. Loosely speaking, an inverse problem is one in which an effect is measured and the cause of it is to be determined.
Paolo Di Barba, Maria Evelina Mognaschi
12. From MEMS to NEMS
Abstract
Nanotechnology, as the scientific and technological discipline dealing with the design, fabrication and application of systems whose dimensions or tolerances are in the domain of nanometers, is becoming increasingly important in many industrial and scientific areas. Nanotechnologies and nanoscience are triggered by diverse fields and applications but on the other hand, they trigger by themselves future industrial and practical solutions. One of the most important challenges observed nowadays in nanotechnology is driving the manufacturing processes to sub-nm accuracy level for critical features and positioning tasks.
Teodor Gotszalk
13. Numerical Case Studies: Forward Problems
Abstract
Electrostatic micromotors were the first MEMS which had been designed and prototyped exploiting Silicon integrated technology.
Paolo Di Barba, Maria Evelina Mognaschi
14. Numerical Case Studies: Inverse Problems
Abstract
Optimization plays a key role in the design of any device or system, and this is especially true for MEMSs. The issue is to find a design space for a device which will satisfy the performance specifications. Often, they include several design criteria which cannot all be met at the same time. This leads to the concept of multi-objective optimization, i.e., a search which attempts to satisfy several goals simultaneously.
Maria Evelina Mognaschi
Backmatter
Metadata
Title
MEMS: Field Models and Optimal Design
Authors
Prof. Paolo Di Barba
Prof. Slawomir Wiak
Copyright Year
2020
Electronic ISBN
978-3-030-21496-8
Print ISBN
978-3-030-21495-1
DOI
https://doi.org/10.1007/978-3-030-21496-8