• 文献标题:   Escherichia coli bacteria detection by using graphene-based biosensor
  • 文献类型:   Article
  • 作  者:   AKBARI E, BUNTAT Z, AFROOZEH A, ZEINALINEZHAD A, NIKOUKAR A
  • 作者关键词:   biosensor, nanosensor, microorganism, drug, neural net, support vector machine, regression analysi, medical computing, 2d monolayer honeycomb, 2d nanosensor structure, antibacterial drug screening, artificial neural network, bacteria detection, biosensor sensitivity level, biosensorbased bacterial detection, biosensordetected e, coli bacteria, biosensordetected escherichia coli, carbon allotrope, e, coli detection, escherichia coli detection, fieldeffect transistor structure, graphene currentvoltage characteristic, graphene device conductance, graphene iv characteristic, graphenebased biosensor, graphenebased nanosenor, ideal highthroughput bacterial detection platform, nanoelectronic biosensor sensitivity, nanosensor electrical propertie, nanosensor optical propertie, nanosensor physical propertie, nanosensor sensitivity level, nanosensorprovided detection area, nanosensorprovided sensitivity, pathogenic bacteriadetecting biosensor, sensing mechanism modeling, special nanosensor characteristic, support vector regression algorithm, twodimensional monolayer honeycomb
  • 出版物名称:   IET NANOBIOTECHNOLOGY
  • ISSN:   1751-8741 EI 1751-875X
  • 通讯作者地址:   Univ Teknol Malaysia
  • 被引频次:   7
  • DOI:   10.1049/iet-nbt.2015.0010
  • 出版年:   2015

▎ 摘  要

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 0-10(5) 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.