Odorant cluster sensing based on molecular profile recognition materials
Project/Area Number |
25420409
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Measurement engineering
|
Research Institution | Kyushu University |
Principal Investigator |
Liu Chuanjun 九州大学, 味覚・嗅覚センサ研究開発センター, 准教授 (70599654)
|
Co-Investigator(Renkei-kenkyūsha) |
HAYASHI KENSHI 九州大学, システム情報科学研究院, 教授 (50202263)
|
Project Period (FY) |
2013-04-01 – 2016-03-31
|
Project Status |
Completed (Fiscal Year 2015)
|
Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
|
Keywords | 匂いセンサ / 分子インプリント / クラスターセンシング / バイオミメティック / QCMセンサアレイ / 多変量解析 / ソルゲル / センサアレイ / QCM / データ解析 / 分子プロファイル識別 / 匂い吸着分離 / パターン認識 / 嗅覚 |
Outline of Final Research Achievements |
A bioinspired odorant cluster sensing system was developed to imitate the olfactory sensory. A variety of molecular profile recognition materials were prepared by using molecular imprinting (MIP) technique. Their recognition ability was confirmed by GC/MS measurement and QCM sensing. The cluster sensing system was fabricated by the integration of a MIPs-loaded absorption/desorption modules and metal oxide semiconductor gas sensors based sensing modules. The system succeeded in the detection and recognition of odorants with different molecular profiles. The clustering of odorants based on molecular parameters was carried out by using different analysis approaches, among which t-distributed stochastic neighbor embedding (t-SNE) showed a good result in the odorant clustering. The above accomplishments make it possible to design sensor systems to detect odor in a way close to the olfactory perception.
|
Report
(4 results)
Research Products
(20 results)