An ANFIS Based Approach for Prediction of Threshold Voltage Degradation in Nanoscale DG MOSFET Devices

Conference paper

Abstract

Nowadays, the tremendous shrinking of electronic devices has reduced their sizes to very low scales. However, this process has been accompanied unavoidably with many well-recognized reliability challenges basically for MOSFET devices. Our objective, in this work, is the proposition of an Adaptive Network based Fuzzy Inference System (ANFIS) to study the threshold voltage behavior caused by the interface traps generated by the ageing mechanism phenomenon. The consideration of a nanoscale DG MOSFET device makes the application of compact modeling tools a very hard task to carry out, due to approximations made during model development. The obtained results are in a good agreement with numerical simulations based on Atlas 2D-simulator. In addition, the comparison with a feed-forward artificial neural network shows that our fuzzy system provides higher accuracy performances. The proposed approach can be incorporated in Integrated Circuit modeling frameworks in order to support more complex degradation situations.

Keywords

DG MOSFET Functions Hot carrier Learning algorithm Membership Quantum confinement Short channel Threshold voltage 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Physics DepartmentUniversity of BatnaBatnaAlgeria
  2. 2.Electronics DepartmentUniversity of BatnaBatnaAlgeria

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