Portable optical-based electronic nose using dual-sensors array applied for volatile discrimination

At present, electronic nose (e-nose) has become a popular tool to classify odor samples in various industries. However, most high-performance e-nose systems are in the form of desktop, thus limiting their uses in many areas of applications where analysis must be performed on site. In this work, we h...

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Bibliographic Details
Main Authors: Treenet Thepudom, Sumana Kladsomboon, Tawee Pogfay, Adisorn Tuantranont, Teerakiat Kerdcharoen
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
Subjects:
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/14037
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Institution: Mahidol University
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Summary:At present, electronic nose (e-nose) has become a popular tool to classify odor samples in various industries. However, most high-performance e-nose systems are in the form of desktop, thus limiting their uses in many areas of applications where analysis must be performed on site. In this work, we have developed a portable optical-based e-nose that features several advantages over traditional e-nose systems, namely changeable dual sensor arrays, plug-in low-cost LED sources and switchable air/liquid sample handling. The measurement of this e-nose is based on detection of the absorption change of Zinc-5,10,15,20-tetra-phenyl-21H,23H-porphyrin (ZnTPP) and Zinc-2,9,16,23-tetra- tert-butyl-29H,31H-phthalocyanine (ZnTTBPc) thin films, as prepared by spin coating on glass substrates. By observing absorption changes of the abovementioned two types of the optically-active thin films within a narrow spectral region as produced by eight LED light sources, an array of 16 chemical sensors was created for this e-nose. We have tested this e-nose with three types of alcohols such as ethanol, methanol and isopropanol. Finally, principal component analysis (PCA) was used to analyze the data from both thin film gas sensors. The results of PCA confirm that the optical-based e-nose based on dual-sensors array successfully discriminates three types of VOCs. © 2012 IEEE.