An unmodified graphene foam chemical sensor based on SVM for discrimination of chemical molecules with broad selectivity. Issue 69 (8th September 2017)
- Record Type:
- Journal Article
- Title:
- An unmodified graphene foam chemical sensor based on SVM for discrimination of chemical molecules with broad selectivity. Issue 69 (8th September 2017)
- Main Title:
- An unmodified graphene foam chemical sensor based on SVM for discrimination of chemical molecules with broad selectivity
- Authors:
- Yue, Weiwei
Hua, Hongling
Tian, Yanli
Li, Jianing
Jiang, Shouzhen
Tang, Caiyan
Xu, Shicai
Ma, Yong
Ren, Junfeng
Bai, Chengjie - Abstract:
- Abstract : Compared to conventional chemical sensors, this paper presented a chemical sensor system with broad selectivity for a variety of molecules without any surface modification. Abstract : Compared to conventional chemical sensors, this paper presented a chemical sensor system with broad selectivity for a variety of molecules without any surface modification. The system consisted of an unmodified graphene foam as sensing element, an electrical resistance time domain detection system and a Support Vector Machine (SVM) identification system. The chemical sensor adopted 3D graphene foam to increase the reaction area and improve the sensitivity for detecting target molecules. The electrical resistance time domain detection system was constructed to record the graphene resistance curve in real time with different molecules. Based on the diverse shapes of the electrical resistance curves, SVM was used to extract features of each resistance curve and discriminate the corresponding molecules via pattern recognition of each resistance curve without any graphene modification. As validation experiments, six kinds of chemical molecules (chloroform, acetone, ether, toluene, ethyl benzene and methanol) have been tested. The discrimination accuracy for each molecule could be above 98% which showed a broad selectivity for a variety of molecules. Furthermore, through theoretical calculation with the first principle, we concluded that different band structures of the graphene caused byAbstract : Compared to conventional chemical sensors, this paper presented a chemical sensor system with broad selectivity for a variety of molecules without any surface modification. Abstract : Compared to conventional chemical sensors, this paper presented a chemical sensor system with broad selectivity for a variety of molecules without any surface modification. The system consisted of an unmodified graphene foam as sensing element, an electrical resistance time domain detection system and a Support Vector Machine (SVM) identification system. The chemical sensor adopted 3D graphene foam to increase the reaction area and improve the sensitivity for detecting target molecules. The electrical resistance time domain detection system was constructed to record the graphene resistance curve in real time with different molecules. Based on the diverse shapes of the electrical resistance curves, SVM was used to extract features of each resistance curve and discriminate the corresponding molecules via pattern recognition of each resistance curve without any graphene modification. As validation experiments, six kinds of chemical molecules (chloroform, acetone, ether, toluene, ethyl benzene and methanol) have been tested. The discrimination accuracy for each molecule could be above 98% which showed a broad selectivity for a variety of molecules. Furthermore, through theoretical calculation with the first principle, we concluded that different band structures of the graphene caused by different molecules were the mechanism for the graphene chemical sensor system to discriminate chemical molecules with selectivity. This work may present a new strategy for research and application for graphene chemical sensors. … (more)
- Is Part Of:
- RSC advances. Volume 7:Issue 69(2017)
- Journal:
- RSC advances
- Issue:
- Volume 7:Issue 69(2017)
- Issue Display:
- Volume 7, Issue 69 (2017)
- Year:
- 2017
- Volume:
- 7
- Issue:
- 69
- Issue Sort Value:
- 2017-0007-0069-0000
- Page Start:
- 43560
- Page End:
- 43566
- Publication Date:
- 2017-09-08
- Subjects:
- Chemistry -- Periodicals
540.5 - Journal URLs:
- http://pubs.rsc.org/en/Journals/JournalIssues/RA ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c7ra07963j ↗
- Languages:
- English
- ISSNs:
- 2046-2069
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8036.750300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 4596.xml