Lecture

Non-linear Effects in MEMS Cantilevers

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In course

MICRO-470: Scaling laws in micro & nanosystems

This class adresses scaling laws in MEMS/NEMS. The dominant physical effects and scaling effects when downsizing sensors and actuators in microsystems are discussed, across a broad range of actuation principles. ...

Description

This lecture explores the non-linear effects in MEMS cantilevers, focusing on materials and geometrical aspects. It discusses the importance of non-linear effects when motion exceeds 40% of the spring thickness, providing examples and simulations in micro and nanosystems.

Instructors (3)

Philippe Renaud

Philippe Renaud is Professor at the Microsystem Laboratory (LMIS4) at EPFL. He is also the scientific director of the EPFL Center of MicroNanoTechnology (CMI). His main research area is related to micronano technologies in biomedical applications (BioMEMS) with emphasis on cell-chips, nanofluidics and bioelectronics. Ph. Renaud is invloved in many scientifics papers in his research area. He received his diploma in physics from the University of Neuchâtel (1983) and his Ph.D. degree from the University of Lausanne (1988). He was postdoctoral fellow at University of California, Berkeley (1988-89) and then at the IBM Zürich Research Laboratory in Switzerland (1990-91). In 1992, he joined the Sensors and Actuators group of the Swiss Center for Electronics and Microtechnology (CSEM) at Neuchâtel, Switzerland. He was appointed assistant professor at EPFL in 1994 and full professor in 1997. In summer 1996, he was visiting professor at the Tohoku University, Japan. Ph. Renaud is active in several scientific committee (scientific journals, international conferences, scientific advisory boards of companies, PhD thesis committee). He is also co-founder of the Nanotech-Montreux conference. Ph. Renaud is committed to valorization of basic research through his involvement in several high-tech start-up companies.

Niels Quack

Prof. Dr. Niels Quack received the M.Sc. degree from Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, in 2005, and the Dr.Sc. degree from Eidgenössische Technische Hochschule Zürich (ETH), Zürich, Switzerland, in 2010. From 2011 to 2015, he was Postdoctoral Researcher and Visiting Scholar with the Integrated Photonics Laboratory, Berkeley Sensor and Actuator Center, University of California, Berkeley, CA, USA. From 2014 to 2015, he was Senior MEMS Engineer with Sercalo Microtechnology, Neuchâtel, Switzerland. He is currently an SNSF Assistant Professor with Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. He has authored and co-authored more than 50 papers in leading technical journals and conferences. His research interests include photonic micro and nanosystems, with an emphasis on diamond photonics and silicon photonic MEMS. He is Steering Committee Member of the IEEE International Conference on Optical MEMS and Nanophotonics (OMN) and served as General Chair of the IEEE OMN 2018 and the Latsis Symposium 2019 on Diamond Photonics. He is a Senior Member of IEEE, Member of The Optical Society (OSA) and life member of SPIE.

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Related concepts (12)

Simulation

A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.

Computer simulation

Computer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering.

Business simulation

Business simulation or corporate simulation is simulation used for business training, education or analysis. It can be scenario-based or numeric-based. Most business simulations are used for business acumen training and development. Learning objectives include: strategic thinking, decision making, problem solving, financial analysis, market analysis, operations, teamwork and leadership. The business gaming community seems lately to have adopted the term business simulation game instead of just gaming or just simulation.

Training simulation

In business, training simulation is a virtual medium through which various types of skills can be acquired. Training simulations can be used in a variety of genres; however they are most commonly used in corporate situations to improve business awareness and management skills. They are also common in academic environments as an integrated part of a business or management course. The word simulation implies an imitation of a real-life process, usually via a computer or other technological device, in order to provide a lifelike experience.

Material

Material is a substance or mixture of substances that constitutes an object. Materials can be pure or impure, living or non-living matter. Materials can be classified on the basis of their physical and chemical properties, or on their geological origin or biological function. Materials science is the study of materials, their properties and their applications. Raw materials can be processed in different ways to influence their properties, by purification, shaping or the introduction of other materials.

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