Description: Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

This title appears in the Scientific Report : 2009

Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overla...

Personal Name(s):	Turek, M.
	Heiden, W. / Riesen, A. / Chhabdaa, T.A. / Schubert, J. / Zander, W. / Krüger, P. / Keusgen, M. / Schöning, M. J.
Contributing Institute:	Halbleiter-Nanoelektronik; IBN-1 Institut für Bio- und Nanosysteme - Bioelektronik; IBN-2 JARA-FIT; JARA-FIT
Published in:	Electrochimica acta, 54 (2009) S. 6082 - 6088
Imprint:	New York, NY [u.a.] Elsevier 2009
Physical Description:	6082 - 6088
DOI:	10.1016/j.electacta.2009.03.035
Document Type:	Journal Article
Research Program:	Grundlagen für zukünftige Informationstechnologien
Series Title:	Electrochimica Acta 54
Subject (ZB):	J Fuzzy logic Electronic tongue Cross-sensitivity Chalcogenide glass sensor Multi-component heavy metal solution
	Publikationsportal JuSER

Please use the identifier: http://dx.doi.org/10.1016/j.electacta.2009.03.035 in citations.

The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed. (C) 2009 Elsevier Ltd. All rights reserved.