公益財団法人 セコム科学技術振興財団
研究成果報告書

研究課題名

分子を認識する二次元プラズモニックガスセンサアレイによる匂いの痕跡識別システム
Odor trace discrimination system using two dimensional plasmonic sensor arraywith molecular recognizing ability

研究期間
平成２９年１０月 ～ 令和 ４年 ３月

報告年月
令和 ４年 ６月
研究代表者
九州大学 大学院システム情報科学研究院 情報エレクトロニクス部門 教授
林 健司
Graduate school of information science and electrical engineering, Kyushu University
Professor
Kenshi Hayashi

1Abstract
Odor, the composition information of many volatile chemical substances, has extremely richinformation. If the traces of invisible odors can be visualized, it will be possible to identify human,objects, and situations and track movement routes. The visualized odor information can becompletely new information; where it is difficult to erase or disguise traces of odor information due toadhesion, enormous number of target chemicals, and invisibility. In addition, it is possible to acquire
hidden information that cannot be detected by the camera, and it gives abundant multidimensional
information that is completely different from visual information. The basic technology developed by
the group to realize such new odor visualization information sensing, (1) high-speed two-dimensional
plasmonic gas sensor, (2) surface modification technology and molecularly imprint technology for gas
selectivity, (3) chemical information identification technology like olfactory information processing.
The aim of this research is constructing odor trace identification system using a two-dimensional
odor image sensor which provides a new and huge information.
Based on the above research background and purpose, we conducted research and development andobtained the following results. First, we developed a device that can visualize odor traces and flows
by making a plasmonic gas sensor that detects volatile chemical substances at high speed andtwo-dimensional. A plasmonic gas sensor based on LSPR (localized plasmon resonance) is a deposit ofmetal nanoparticles whose optical characteristics change depending on the atmosphere on a glass
substrate. In this study, gold nanoparticles (AuNPs) on the order of 10 nm were densely spread bysputtering. This plasmonic gas sensor can control the gas responsiveness by the composition of theAu/Ag metal material, where gas discrimination ability was obtained by changing the Au/Ag
composition of core-shell nanoparticles.
Next, to visualize the flow and traces of multiple gases, it is necessary to create a sensor device inwhich Au/Ag core-shell nanoparticles with different response characteristics. Thus, we havecontrolled the Ag growth rate for each position of the sensor device by pixel-patterned lightirradiation, and created a two-dimensional odor image sensor for four types of Au/Ag core shells. As aresult, we succeeded in visualizing the flow of odors, and analyzed the difference in the response
pattern of the sub-pixels by the non-negative matrix decomposition technique, and identified thetype of odor as each element gas.
Regarding the identification of odor molecules, information was also acquired by dye modification of
the surface of metal nanoparticles by using the hyper-spectrum information. It analyzes and detects
huge amounts of information obtained from two-dimensional gas sensor devices by machine learning.
The target odorant could be identified with high accuracy.
We have developed a system that can identify traces of odors in real time by mounting the lastdeveloped sensor on the robot. This robot system is equipped with an 18-channel plasmonic gas
sensor configured by dye modification, and can detect multiple odors remaining on the floor while
traveling, and can identify odors by machine learning.
3