ANFIS modeling for bacteria detection based on GNR biosensor

作者：Akbari Elnaz; Buntat Zolkafle^*; Shahraki Elmira; Zeinalinezhad Alireza; Nilashi Mehrbakhsh

来源：Journal of Chemical Technology and Biotechnology, 2016, 91(6): 1728-1736.

DOI：10.1002/jctb.4761

• graphene nanoribbon (GNR)
• E. coli bacteria
• biosensor
• field effect transistor
• ANFIS
• I-V characteristics

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.

• 出版日期2016-6