| 학회 |
한국공업화학회 |
| 학술대회 |
2019년 봄 (05/01 ~ 05/03, 부산 벡스코(BEXCO)) |
| 권호 |
23권 1호 |
| 발표분야 |
(정밀화학) 정밀화학기술의 응용 |
| 제목 |
Fluorescent Pattern Generating Chemical Sensor Array: Volatile Organic Compounds Recognition Assisted by Machine Learning Algorithm |
| 초록 |
Fluorescent sensors have been used as powerful chemical tools in monitoring environmental condition, understanding biological system and diagnosis of diseases. However, signal from fluorescent sensors are often nonspecific and sensitive to environmental conditions, leading to artifacts and thereby resulting confusing experimental outcomes. Therefore robust fluorescent sensing system with the high accuracy is desirable. We synthesized 75-membered fluorescent-compound library based on indolizine core skeleton. Spotting of the fluorescent compound on cellulose paper allowed generation of fluorescent compound array. Exposure of the array with 35 different VOCs triggered different responding fluorescent patterns. PCA study revealed sensory array system successfully classify each VOC. 500 sample of sensor patterns for 5 different VOC types were passed through a series of image processing and machine learning algorithms, and our result shows an accuracy of 97% for identifying the VOC type. |
| 저자 |
김현기1, 최상기1, 안정모1, 신익수2, 고정길1, 김은하1
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| 소속 |
1아주대, 2숭실대 |
| 키워드 |
Indolizine; machine learning; volatile organic compound
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| E-Mail |
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