Student-Run Math Consulting at Stanford Melissa Aczon, Martin Gander, Margot Gerritsen, Tony Shardlow, Ronnie Sircar About the Articles Free Requires Subscription Purchase pp. About the Articles Theme Articles Free Requires Subscription Purchase pp. That is just one computational challenge posed by MEMS, a technology in which multitudes of interacting tiny machines can add computational behavior to materials and the environment in an embedded, massively distributed fashion. 17-29 Computational Methods for Design and Control of MEMS Micromanipulator Arrays Karl F. B hringer, Bruce R. Donald, Noel C. MacDonald, Gregory T.A. Kovacs, John W. Suh Arrays of MEMS devices can move and position tiny parts, such as integrated circuit chips, in flexible and predictable ways by oscillatory or ciliary action. The theory of programmable force fields can model this action, leading to algorithms for various types of micromanipulation that require no sensing of where the part is.
Experiments support the theory.
Computational Methods and Needs Stephen D. Senturia, Narayan Aluru, Jacob White Technologies for fabricating a variety of MEMS devices have developed rapidly, but computational tools that allow engineers to quickly design and optimize these micromachines have not kept pace. Inadequate simulation tools force MEMS designers to resort to physical prototyping. To realistically simulate the behavior of complete micromachines, algorithmic innovation is necessary in several areas. Several microelectromechanical systems have achieved commercial success. The barriers can still be formidable, though, and the path to success is often much different for MEMS than it was for mainstream semiconductors.