ANFIS modeling for bacteria detection based on GNR biosensor

Abstract

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.