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Microsystem Technologies

, Volume 20, Issue 4–5, pp 559–569 | Cite as

A phase-locked loop frequency tracking system for portable microelectromechanical piezoresistive cantilever mass sensors

  • Hutomo Suryo WasistoEmail author
  • Qing Zhang
  • Stephan Merzsch
  • Andreas Waag
  • Erwin Peiner
Technical Paper

Abstract

A closed-loop circuit is developed in this work for tracking the resonant frequency of silicon microcantilever mass sensors. The proposed closed-loop system is mainly based on a phase-locked loop (PLL) circuit. To lock onto the resonant frequency of the resonator, an actuation signal generated from a voltage-controlled oscillator is fed back to the input reference signal of the cantilever sensor. In addition to the PLL circuit, an instrumentation amplifier and an active low-pass filter are connected to the system for gaining the cantilever output signal and transforming a rectangular PLL output signal into a sinusoidal signal used for sensor actuation, respectively. To demonstrate the functionality of the system, a self-sensing silicon cantilever resonator with a built-in piezoresistive Wheatstone bridge is fabricated and integrated with the circuit. A piezoactuator is employed to actuate the cantilever into resonance. From the measurement results, the integrated closed-loop system is successfully employed to characterize a 9.4 kHz cantilever sensor under ambient temperature cross-sensitivity yielding a sensor temperature coefficient of −32.8 ppm/°C. In addition to it, the sensor was also exposed to exhaled human breath condensates and e-cigarette aerosols to test the sensor sensitivity obtained from mass-loading effects. With a high frequency stability (i.e., a frequency deviation as low as 0.02 Hz), this developed system is intended to support the miniaturization of the instrumentation modules for cantilever-based nanoparticle detectors (CANTORs).

Keywords

Resonant Frequency Exhale Breath Condensate Loop Filter Wheatstone Bridge Instrumentation Amplifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank Juliane Arens, Doris Rümmler, and Karl-Heinz Lachmund for their valuable technical assistances. This work is performed in the collaborative project “NanoExpo” funded by the German Federal Ministry of Education and Research (BMBF) within the cluster “NanoCare” under No. 03X0098A.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hutomo Suryo Wasisto
    • 1
    Email author
  • Qing Zhang
    • 1
  • Stephan Merzsch
    • 1
  • Andreas Waag
    • 1
  • Erwin Peiner
    • 1
  1. 1.Institute of Semiconductor Technology (IHT)Braunschweig University of TechnologyBrunswickGermany

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