Next Article in Journal
Building Intelligent Communication Systems for Handicapped Aphasiacs
Next Article in Special Issue
A Macroporous TiO2 Oxygen Sensor Fabricated Using Anodic Aluminium Oxide as an Etching Mask
Previous Article in Journal
Infiltration Route Analysis Using Thermal Observation Devices (TOD) and Optimization Techniques in a GIS Environment
Previous Article in Special Issue
Gas Sensors Based on Semiconducting Metal Oxide One-Dimensional Nanostructures
Sensors 2010, 10(1), 361-373; doi:10.3390/s100100361
Article

Binary Fingerprints at Fluctuation-Enhanced Sensing

1
,
1,* , 2
 and
3
1 Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA 2 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.
Received: 8 December 2009 / Revised: 23 December 2009 / Accepted: 28 December 2009 / Published: 5 January 2010
(This article belongs to the Special Issue Metal-Oxide Based Nanosensors)
View Full-Text   |   Download PDF [437 KB, uploaded 21 June 2014]   |  

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.
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
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
SciFeed

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
RIS
MDPI and ACS Style

Chang, H.-C.; Kish, L.B.; King, M.D.; Kwan, C. Binary Fingerprints at Fluctuation-Enhanced Sensing. Sensors 2010, 10, 361-373.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert