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Nature. 2009 Apr 23;458(7241):1001-4. doi: 10.1038/nature07932.

Universal transduction scheme for nanomechanical systems based on dielectric forces.

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Fakultät für Physik and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität, Geschwister-Scholl-Platz 1, 80539 München, Germany.


Any polarizable body placed in an inhomogeneous electric field experiences a dielectric force. This phenomenon is well known from the macroscopic world: a water jet is deflected when approached by a charged object. This fundamental mechanism is exploited in a variety of contexts-for example, trapping microscopic particles in an optical tweezer, where the trapping force is controlled via the intensity of a laser beam, or dielectrophoresis, where electric fields are used to manipulate particles in liquids. Here we extend the underlying concept to the rapidly evolving field of nanoelectromechanical systems (NEMS). A broad range of possible applications are anticipated for these systems, but drive and detection schemes for nanomechanical motion still need to be optimized. Our approach is based on the application of dielectric gradient forces for the controlled and local transduction of NEMS. Using a set of on-chip electrodes to create an electric field gradient, we polarize a dielectric resonator and subject it to an attractive force that can be modulated at high frequencies. This universal actuation scheme is efficient, broadband and scalable. It also separates the driving scheme from the driven mechanical element, allowing for arbitrary polarizable materials and thus potentially ultralow dissipation NEMS. In addition, it enables simple voltage tuning of the mechanical resonance over a wide frequency range, because the dielectric force depends strongly on the resonator-electrode separation. We use the modulation of the resonance frequency to demonstrate parametric actuation. Moreover, we reverse the actuation principle to realize dielectric detection, thus allowing universal transduction of NEMS. We expect this combination to be useful both in the study of fundamental principles and in applications such as signal processing and sensing.


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