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Odor Sensing Technologies for Visualization of Odor Quality and Space

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Abstract

In recent years, sensors for objective evaluation of quality and quantity of odor substances have shown a wide range of potential applications in many fields. However, the odor quality is difficult to be expressed by quantitative data because the odor sensation is brought about by a variety of volatile compounds, which form a complicated, subjective olfactory sense. Recent progress in molecular biological research of the olfactory system have shown that an odor cluster map produced on the surface of olfactory bulb through olfactory receptors presents essential information for brain to perceive odorants. The clustering perception model provides us with a new concept to design odor sensors with performance equivalent to mammalian olfactory system. The biological-inspired odor sensing based on various molecular recognition technologies, such as partial structure recognized water membrane/Pt electrodes, benzene-patterned self-assembled monolayer (SAM) layers, size and polarity selected molecular sieve materials, and molecularly imprinted polymer (MIP) adsorbents, are introduced to construct an artificial odor map and to evaluate the odor quality. On the other hand, odorants in our living environment can only be perceived by the sense of our olfactory, and odor space is invisible to eyes. The temporal and spatial distribution of odorants in environment is also important information for human and other animals. However, the visualization of odor space by using conventional sensor technologies is a difficult task due to the limited spatiotemporal resolution. Here optical sensing technologies based on fluorescence imaging and localized surface plasmon resonance (LSPR) are developed to visualize the spatiotemporal distribution of odorants in environment. In addition, the application of the developed sensors in the visualization of human body odor and odor release from fragrance encapsulated cyclodextrin inclusion complexes are presented also.

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Authors and Affiliations

  1. Department of Electronics, Graduate School of Information Science and Electric Engineering, Kyushu University, 744 Motooka, Nishi-ku, 819-0395, Fukuoka, Japan

    Chuanjun Liu & Kenshi Hayashi

Authors
  1. Chuanjun Liu
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  2. Kenshi Hayashi
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Correspondence to Kenshi Hayashi .

Editor information

Editors and Affiliations

  1. National Tsing Hua University, Hsichu, Taiwan

    Youn-Long Lin

  2. Korea Advanced Institute of Science and Technology, Daejeon, Korea, DPR (North Korea)

    Chong-Min Kyung

  3. Kyushu University, Fukuoka, Japan

    Hiroto Yasuura

  4. Tsinghua University, Beijing, China

    Yongpan Liu

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© 2015 Springer International Publishing Switzerland

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Liu, C., Hayashi, K. (2015). Odor Sensing Technologies for Visualization of Odor Quality and Space. In: Lin, YL., Kyung, CM., Yasuura, H., Liu, Y. (eds) Smart Sensors and Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-14711-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-14711-6_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14710-9

  • Online ISBN: 978-3-319-14711-6

  • eBook Packages: EngineeringEngineering (R0)

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