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Metal organic frameworks based microcantilever gas sensors for detection of volatile organic compounds

Metal Organic Frameworks (MOFs) are a new class of nanoporous materials with
high surface area, thermal/chemical stability and a taylorable pore size. These properties
make MOFs ideal for storage and gas separation applications. Piezoresistive
microcantilever sensors are microfabricated devices that are highly sensitive to surface
strain due to doped single crystal silicon regions. Changes in resistance generated by
surface strain can be measured with a high degree of accuracy using a Wheatstone bridge
and basic instrumentation. This thesis will discuss the use of piezoresistive
microcantilever sensors as a transduction mechanism for detection of volatile organic
compounds (VOC's) using MOF coatings. It will be shown that by coating a
microcantilever with MOFs it is possible to detect low levels of different VOC's
(hundreds of parts per million). Excellent sensitivity and a simple transduction
mechanism make these devices low power and highly compact. Such devices would be
capable of detecting a plethora of different analytes at low concentrations. Devices were
engineered for maximum response and microfabricated in the cleanroom with high yield.
A custom setup for testing the devices was designed and machined. A number of MOFs
were selected and tested, their response was recorded and analyzed. Twelve different
analytes including eleven VOC's and water were used to characterize the MOFs.
Microcantilever sensors were shown to be durable, reliable and stable in long term testing
despite being subjected to many different analytes. MOF coatings proved flexible,
durable, stable and reversible. This work will show a promising new technology for a
next generation gas sensor.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/49127
Date20 September 2013
CreatorsEllern, Ilya
ContributorsHesketh, Peter
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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