Capacitance Modeling With Charge Partitions Covering Full-Region Operations of TFETs

An accurate physics-based capacitance model is developed covering full-region operations of silicon TFET (Si-TFET) with all biasing conditions. The intrinsic and parasitic capacitances are modeled by the surface-potential-based method and justified by calibrated TCAD simulations. To address the challenges of a classical physics-based model in calculating the charge partitions, an artificial neural network (ANN)-enhanced method is proposed to capture the terminal partition strategy, which features good smoothness and high accuracy. The results show a source terminal partition of the ambipolar region in the range of 90%–100%, and the drain partition of the normal region is in the range of 85%–100%, with in-between partitions of the transition regions. This ANN-enhanced physics-based model addresses the requirements of a TFET channel charge partition strategy and has been verified in circuit simulations with improved accuracy.