• 文献标题:   A new approach for prediction of graphene based ISFET using regression tree and neural network
  • 文献类型:   Article
  • 作  者:   AKBARI E, MORADI R, AFROOZEH A, ALIZADEH A, NILASHI M
  • 作者关键词:   graphene, isfet, iv characteristic, k, regression tree, ann
  • 出版物名称:   SUPERLATTICES MICROSTRUCTURES
  • ISSN:   0749-6036
  • 通讯作者地址:   Ton Duc Thang Univ
  • 被引频次:   2
  • DOI:   10.1016/j.spmi.2019.04.011
  • 出版年:   2019

▎ 摘  要

In this work, ion sensitive field effect transistor (ISFET) which is a device sensitive to the ions in a solution is employed. It is shown that under a fixed bias configuration, the voltage change causes a subsequent change in the surface potential of graphene thin film, which induces a detectable current change in the conducting channel between drain and source electrodes. Thus the transduction from an analog signal as an ion concentration(K+) changes to an electrical signal as current change can be achieved. For prediction purpose, the regression tree algorithm and artificial neural network (ANN) have been employed to predict the I-V characteristic, however ANN outperforms the regression tree approach and gives more accurate results.