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1

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA

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Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA

3

Signal Processing, Inc., 13619 Valley Oak Circle, Rockville, MD 20850, USA





*

Author to whom correspondence should be addressed.



Abstract We have developed a simple way to generate binary patterns based on spectral slopes in different frequency ranges at fluctuation-enhanced sensing. Such patterns can be considered as binary -fingerprints- of odors. The method has experimentally been demonstrated with a commercial semiconducting metal oxide Taguchi sensor exposed to bacterial odors Escherichia coli and Anthrax-surrogate Bacillus subtilis and processing their stochastic signals. With a single Taguchi sensor, the situations of empty chamber, tryptic soy agar TSA medium, or TSA with bacteria could be distinguished with 100% reproducibility. The bacterium numbers were in the range of 2.5 × 104-106. To illustrate the relevance for ultra-low power consumption, we show that this new type of signal processing and pattern recognition task can be implemented by a simple analog circuitry and a few logic gates with total power consumption in the microWatts range. View Full-Text

Keywords: fluctuation-enhanced sensing; semiconducting metal oxide sensors; nano-sensors; ultra-low power sensor systems fluctuation-enhanced sensing; semiconducting metal oxide sensors; nano-sensors; ultra-low power sensor systems





Autor: Hung-Chih Chang 1, Laszlo B. Kish 1,* , Maria D. King 2 and Chiman Kwan 3

Fuente: http://mdpi.com/



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