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TDDB in HfSiON/SiO2 dielectric stack: Büttiker probe based NEGF modeling, prediction and experiment

HfO2 based high-κ metal gate (HKMG) transistors offer low leakage current and high integration density. However, they are vulnerable to defect formation. In this paper, we have demonstrated a Büttiker probe based leakage current model [1][2] for determining the gate leakage current in a HKMG transi...

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Main Authors: Reza, Ahmed Kamal, Hassan, Mohammad Khaled, Roy, Kaushik, Patra, Devyani, Bansal, Ankita, Yu Cao
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creator Reza, Ahmed Kamal
Hassan, Mohammad Khaled
Roy, Kaushik
Patra, Devyani
Bansal, Ankita
Yu Cao
description HfO2 based high-κ metal gate (HKMG) transistors offer low leakage current and high integration density. However, they are vulnerable to defect formation. In this paper, we have demonstrated a Büttiker probe based leakage current model [1][2] for determining the gate leakage current in a HKMG transistor due to defects in the gate dielectric layer. These defects can be pre-existing defects (PEDs) as well as the stress induced defects in the gate dielectric stack. The model was also used to determine the post breakdown gate current characteristics. We have verified our model with experimentally measured data from 28nm planar devices with HfSiON/SiO 2 gate dielectric layer. In addition, we have integrated the Büttiker probe method and percolation model [3] to predict the time to failure (t BD ) of the device. The proposed simulation methodology can also be used to determine the required stress condition (SC) to observe breakdown in a device within a certain period of time.
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source IEEE Xplore All Conference Series
subjects Breakdown Prediction
Büttiker probe
Dielectrics
Electric breakdown
HfSiON
high-κ metal gate (HKMG)
Logic gates
Non-equilibrium Green's function (NEGF)
Probes
Stress
Stress Induced Leakage Current (SILC)
Temperature
Temperature Stress
Time dependent Dielectric Breakdown (TDDB)
Tunneling
Voltage Stress
Weibull
title TDDB in HfSiON/SiO2 dielectric stack: Büttiker probe based NEGF modeling, prediction and experiment
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