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Design optimization of piezoresistive cantilevers for force sensing in air and water

J. Appl. Phys. 106, 064310 (2009); doi:10.1063/1.3224965

Published 23 September 2009

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Joseph C. Doll, Sung-Jin Park, and Beth L. Pruitt
Department of Mechanical Engineering, Stanford University, Stanford, California 94305-4040, USA
Piezoresistive cantilevers fabricated from doped silicon or metal films are commonly used for force, topography, and chemical sensing at the micro- and macroscales. Proper design is required to optimize the achievable resolution by maximizing sensitivity while simultaneously minimizing the integrated noise over the bandwidth of interest. Existing analytical design methods are insufficient for modeling complex dopant profiles, design constraints, and nonlinear phenomena such as damping in fluid. Here we present an optimization method based on an analytical piezoresistive cantilever model. We use an existing iterative optimizer to minimimize a performance goal, such as minimum detectable force. The design tool is available as open source software. Optimal cantilever design and performance are found to strongly depend on the measurement bandwidth and the constraints applied. We discuss results for silicon piezoresistors fabricated by epitaxy and diffusion, but the method can be applied to any dopant profile or material which can be modeled in a similar fashion or extended to other microelectromechanical systems. ©2009 American Institute of Physics
History: Received 6 May 2009; accepted 13 August 2009; published 23 September 2009
Permalink: http://link.aip.org/link/?JAPIAU/106/064310/1
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KEYWORDS and PACS

Keywords
PACS
  • 07.07.Df
    Sensors (chemical, optical, electrical, movement, gas, etc.); remote sensing
  • 84.32.Ff
    Conductors, resistors
  • 85.30.-z
    Semiconductor devices
  • 85.85.+j
    Micro- and nano-electromechanical systems (MEMS/NEMS) and devices
  • 85.40.Ry
    Impurity doping, diffusion and ion implantation technology (microelectronics)
  • YEAR: 2009

RELATED DATABASES

PUBLICATION DATA

ISSN:
0021-8979 (print)   1089-7550 (online)
Publisher:
AIP is a member of CrossRef AIP

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