• 文献标题:   A Computational Model of Neural Learning to Predict Graphene Based ISFET
  • 文献类型:   Article
  • 作  者:   AKBARI E, MIR M, VASILJEVA MV, ALIZADEH A, NILASHI M
  • 作者关键词:   graphene, isfet, iv characteristic, k+, ann
  • 出版物名称:   JOURNAL OF ELECTRONIC MATERIALS
  • ISSN:   0361-5235 EI 1543-186X
  • 通讯作者地址:   Ton Duc Thang Univ
  • 被引频次:   1
  • DOI:   10.1007/s11664-019-07247-x
  • 出版年:   2019

▎ 摘  要

In this study, the graphene ion-sensitive field-effect transistor in an electrolyte solution with different K+ concentration has been investigated. It is found that by measuring the gate voltage changes, the K+ concentration in the electrolyte can be determined because of the interaction between the K+ ions and the gate. For prediction purpose, the artificial neural network has been employed to predict the I-V characteristic, and it demonstrated superior performance.