Conducting Polymer Nanowires for Multi-Analyte Chemiresistive Sensing

• Main Author: Song, Edward
• Other Authors: Choi, Jin-Woo
• Format: Others
• Language: en
• Published: LSU 2014
• Subjects: Electrical & Computer Engineering
• Online Access: http://etd.lsu.edu/docs/available/etd-06062014-145406/

A conducting polymer nanowire-based chemiresistive sensor array was developed for the liquid-phase multi-analyte detection. The ability to distinguish and quantify multiple chemical species with a single sensory device can be useful in many areas including food industry, pollution control, biosensors, and explosives detection. A polyaniline nanowire is a good candidate for use as a chemiresistive sensing material due to its large resistivity change and ease of synthesis. However the two most important issues in chemiresistive sensors are the reproducibility in sensing and the selectivity in chemical species. For improving the reproducibility in polyaniline-based chemiresistive sensing, a self-calibration mechanism was proposed. This method utilizes two unique properties of polyaniline: one is the rate of the conductivity decay upon repeated cycling of the electrochemical potential, and the other is the position of the second redox potential, both of which are pH-dependent. These two properties were minimally affected by the polyanilines inherent limitations, i.e. hysteresis and degradation, and therefore were effective in obtaining repeatable measurements. In order to enhance the selectivity, a catalyst-based selective detection was proposed. This method is based on the concept that the catalytic reaction between the species and the catalysts causes a local pH change near the polyaniline nanowire network which changes the resistance of the polymer. Finally, a sensor array consisting of polyaniline nanowire-based chemiresistors with each sensing element modified with a unique catalyst was implemented for multi-analyte sensing of ascorbic acid, dopamine, and hydrogen peroxide. Principal component algorithm was applied for the classification and semi-quantification of the chemical species.