Title :
Escherichia coli bacteria detection by using graphene-based biosensor
Author :
Akbari, Elnaz ; Buntat, Zolkafle ; Afroozeh, Abdolkarim ; Zeinalinezhad, Alireza ; Nikoukar, Ali
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. Malaysia, Johor Bahru, Malaysia
Abstract :
Graphene is an allotrope of carbon with two-dimensional (2D) monolayer honeycombs. A larger detection area and higher sensitivity can be provided by graphene-based nanosenor because of its 2D structure. In addition, owing to its special characteristics, including electrical, optical and physical properties, graphene is known as a more suitable candidate compared to other materials used in the sensor application. A novel model employing a field-effect transistor structure using graphene is proposed and the current-voltage (I-V) characteristics of graphene are employed to model the sensing mechanism. This biosensor can detect Escherichia coli (E. coli) bacteria, providing high levels of sensitivity. It is observed that the graphene device experiences a drastic increase in conductance when exposed to E. coli bacteria at 0-105 cfu/ml concentration. The simple, fast response and high sensitivity of this nanoelectronic biosensor make it a suitable device in screening and functional studies of antibacterial drugs and an ideal high-throughput platform which can detect any pathogenic bacteria. Artificial neural network and support vector regression algorithms have also been used to provide other models for the I-V characteristic. A satisfactory agreement has been presented by comparison between the proposed models with the experimental data.
Keywords :
biosensors; drugs; medical computing; microorganisms; nanosensors; neural nets; regression analysis; support vector machines; 2D monolayer honeycombs; 2D nanosensor structure; E. coli detection; Escherichia coli detection; antibacterial drug screening; artificial neural network; bacteria detection; biosensor sensitivity level; biosensor-based bacterial detection; biosensor-detected E. coli bacteria; biosensor-detected Escherichia coli; carbon allotrope; field-effect transistor structure; graphene I-V characteristics; graphene current-voltage characteristics; graphene device conductance; graphene-based biosensor; graphene-based nanosenor; ideal high-throughput bacterial detection platform; nanoelectronic biosensor sensitivity; nanosensor electrical properties; nanosensor optical properties; nanosensor physical properties; nanosensor sensitivity level; nanosensor-provided detection area; nanosensor-provided sensitivity; pathogenic bacteria-detecting biosensor; sensing mechanism modeling; special nanosensor characteristics; support vector regression algorithms; two-dimensional monolayer honeycombs;
Journal_Title :
Nanobiotechnology, IET
DOI :
10.1049/iet-nbt.2015.0010