Abstract
In this letter, we present a physics-based compact SPICE model to predict statistical time-dependent dielectric breakdown (TDDB) in nanoscale circuits. In our model, an increase in the gate leakage current (I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G_B D</sub> ) induced by TDDB is estimated using a quantum point contact (QPC) model depending on temperature. In addition, I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G_B D</sub> is based on the statistics of time to breakdown (BD) (t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">BD</sub> ) and location of percolation path (x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">BD</sub> ) in the channel considering third successive BDs. We show that the model can be easily implemented to circuit simulators to predict the degradation of circuit lifetime. With the proposed model, we validated post-BD I-V characteristics with experimental data in ultrathin oxide technology.
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