ANFIS modeling for bacteria detection based on GNR biosensor
BACKGROUND: Graphene is an allotrope of carbon with two-dimensional (2D) monolayer honeycombs. A larger detection area and higher sensitivity can be provided by a graphene based nanosenor because of its two-dimensional structure. In addition, owing to its special characteristics including electrical...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
John Wiley and Sons Ltd
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/72472/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937458242&doi=10.1002%2fjctb.4761&partnerID=40&md5=18d3eb15c0860564dae9ac4d661bef8b |
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| Summary: | BACKGROUND: Graphene is an allotrope of carbon with two-dimensional (2D) monolayer honeycombs. A larger detection area and higher sensitivity can be provided by a graphene based nanosenor because of its two-dimensional structure. In addition, owing to its special characteristics including electrical, optical and physical properties, graphene is a known more suitable candidate than other materials for use in sensor applications. RESULT: In this research, a set of novel models employing field effect transistor (FET) structures using graphene has been proposed and the current-voltage (I-V) characteristics of graphene have been employed to model the sensing mechanism. An adaptive neuro fuzzy inference system (ANFIS) algorithm has been used to provide another model for the current-voltage (I-V) characteristic. CONCLUSION: It has been observed that the graphene device experiences a large increase in conductance when exposed to Escherichia coli bacteria at 0-104 cfu mL-1 concentrations. Accordingly, the proposed model exhibits satisfactory agreement with the experimental data and this biosensor can detect E. coli bacteria providing high levels of sensitivity. |
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