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contributor authorBajaj, Nikhil
contributor authorRhoads, Jeffrey F.
contributor authorChiu, George T.-C.
date accessioned2017-11-25T07:20:54Z
date available2017-11-25T07:20:54Z
date copyright2017/19/7
date issued2017
identifier issn0022-0434
identifier otherds_139_11_114505.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236744
description abstractMicro- and millimeter-scale resonant mass sensors have received widespread attention due to their robust and sensitive performance in a wide range of detection applications. A key performance metric for such systems is the sensitivity of the resonant frequency of a device to changes in mass, which needs to be calibrated. This calibration is complicated by the fact that the position of the added mass on a sensor can have an effect on the measured sensitivity—therefore, a spatial sensitivity mapping is needed. To date, most approaches for experimental sensitivity characterization are based upon the controlled addition of small masses, e.g., the direct attachment of microbeads via atomic force microscopy or the selective microelectrodeposition of material, both of which are time consuming and require specialized equipment. This work proposes a method of experimental spatial sensitivity measurement that uses an inkjet system and standard sensor readout methodology to map the spatially dependent sensitivity of a resonant mass sensor—a significantly easier experimental approach. The methodology is described and demonstrated on a quartz resonator. In the specific case of a Kyocera CX3225 thickness-shear mode resonator, the location of the region of maximum mass sensitivity is experimentally identified.
publisherThe American Society of Mechanical Engineers (ASME)
titleCharacterizing the Spatially Dependent Sensitivity of Resonant Mass Sensors Using Inkjet Deposition
typeJournal Paper
journal volume139
journal issue11
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4036873
journal fristpage114505
journal lastpage114505-6
treeJournal of Dynamic Systems, Measurement, and Control:;2017:;volume( 139 ):;issue: 011
contenttypeFulltext


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