Highly selective acetone detector based on a separation channel and semiconductor gas sensor

被引:8
作者
Du, Haiying [1 ]
Sun, Ruizhi [2 ]
Su, Jing [3 ]
Sun, Yanhui [4 ]
Xia, Kaili [1 ]
Cong, Liying [1 ]
Cui, Hemin [5 ]
机构
[1] Dalian Minzu Univ, Coll Mech & Elect Engn, Dalian 116600, Peoples R China
[2] Shenzhen Univ, Coll Informat Engn, Shenzhen 518061, Peoples R China
[3] Dalian Med Univ, Hosp 2, Dalian 116044, Peoples R China
[4] Dalian Minzu Univ, Coll Informat & Commun Engn, Dalian 116600, Peoples R China
[5] Dalian Zhonghuida Sci Instrument Co Ltd, Dalian 116085, Peoples R China
基金
中国国家自然科学基金;
关键词
exhaled acetone; gas chromatography; semiconductor gas sensor; time-sharing conversion switch; BREATH; GC/MS; MS;
D O I
10.1088/1361-6501/abe666
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Acetone is a biomarker of diabetics. The exhaled acetone concentration of diabetics is higher than that of a healthy person. Semiconductor gas sensors provide an accurate non-invasive detection method for low-concentration breath acetone of diabetics, but the their selectivity presents a drawback. In order to detect the concentration of exhaled acetone accurately from exhaled breath, an acetone detector based on a separation channel and semiconductor gas sensors is presented in this paper. Carbon dioxide, acetone, and ethanol were simulated and separated by a gas chromatography (GC) column in the separation channel. The separated time of carbon dioxide, exhaled acetone, and ethanol are 25 s, 236 s, and 574 s at room temperature, respectively. Carbon dioxide, acetone, and ethanol flow into three gas detection channels with the control of a time-sharing conversion switch. Then, carbon dioxide, acetone, and ethanol can be detected accurately by the semiconductor gas sensors. Exhaled acetone can be measured as low as 1 ppm within 5 min without any interference. A highly selective acetone detector based on GC and semiconductor technology has potential in monitoring and detecting diabetes as well as safe driving in a non-invasive way.
引用
收藏
页数:8
相关论文
共 41 条
[31]   GC-MS libraries for the rapid identification of metabolites in complex biological samples [J].
Schauer, N ;
Steinhauser, D ;
Strelkov, S ;
Schomburg, D ;
Allison, G ;
Moritz, T ;
Lundgren, K ;
Roessner-Tunali, U ;
Forbes, MG ;
Willmitzer, L ;
Fernie, AR ;
Kopka, J .
FEBS LETTERS, 2005, 579 (06) :1332-1337
[32]  
Smith D., 2020, CLIN MASS SPECTROM
[33]   Chemotherapy control by breath profile with application of SPME-GC/MS method [J].
Ulanowska, Agnieszka ;
Trawinska, Ewa ;
Sawrycki, Piotr ;
Buszewski, Boguslaw .
JOURNAL OF SEPARATION SCIENCE, 2012, 35 (21) :2908-2913
[34]   Evaluation of Septa Quality for Automatic SPME-GC-MS Trace Analysis [J].
Ulanowska, Agnieszka ;
Ligor, Tomasz ;
Amann, Anton ;
Buszewski, Bogus-Law .
JOURNAL OF CHROMATOGRAPHIC SCIENCE, 2012, 50 (01) :10-14
[35]   Highly selective detection of methanol over ethanol by a handheld gas sensor [J].
van den Broek, J. ;
Abegg, S. ;
Pratsinis, S. E. ;
Guentner, A. T. .
NATURE COMMUNICATIONS, 2019, 10 (1)
[36]   Is breath acetone a biomarker of diabetes? A historical review on breath acetone measurements [J].
Wang, Zhennan ;
Wang, Chuji .
JOURNAL OF BREATH RESEARCH, 2013, 7 (03)
[37]   Synthesis and excellent acetone sensing properties of porous WO3 nanofibers [J].
Wei, Shaohong ;
Zhao, Guoyan ;
Du, Weimin ;
Tian, Qingqing .
VACUUM, 2016, 124 :32-39
[38]   Preparation and Gas Sensing Properties of In2O3/Au Nanorods for Detection of Volatile Organic Compounds in Exhaled Breath [J].
Xing, Ruiqing ;
Xu, Lin ;
Song, Jian ;
Zhou, Chunyang ;
Li, Qingling ;
Liu, Dali ;
Song, Hong Wei .
SCIENTIFIC REPORTS, 2015, 5
[39]  
Yong-Bo HE., 2018, MACHINE TOOL HYDRAUL
[40]   Acetone-sensing properties of doped ZnO nanoparticles for breath-analyzer applications [J].
Yoo, Ran ;
Park, Yunji ;
Jung, Hwaebong ;
Rim, Hyun Jun ;
Cho, Sungmee ;
Lee, Hyun-Sook ;
Lee, Wooyoung .
JOURNAL OF ALLOYS AND COMPOUNDS, 2019, 803 :135-144