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RC-Effects on the Oxide of SOI MOSFET under Off-State TDDB Degradation: RF Characterization and Modeling
Alan Otero-Carrascal1, Dora Chaparro-Ortiz1, Purushothaman Srinivasan2
1Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico.
Micromachines
|February 24, 2024
Summary
This study analyzes radio frequency (RF) impedance in gate oxides by examining charge trapping, dielectric loss, and leakage current. A new method accurately models these effects, even during device degradation.
Area of Science:
- Electrical Engineering
- Materials Science
- Semiconductor Physics
Background:
- Dynamic charge trapping/de-trapping in gate oxides affects device performance.
- Dielectric loss and leakage current are critical factors in radio frequency (RF) impedance.
- Understanding these effects is crucial for accurate device modeling and reliability assessment.
Purpose of the Study:
- To analyze the impact of dynamic trapping, dielectric loss, and leakage current on RF small-signal input impedance.
- To develop a methodology for extracting model parameters related to these effects.
- To investigate the evolution of these parameters under electrical stress and different bias conditions.
Main Methods:
- Utilized S-parameter measurements for RF analysis.
- Systematically extracted model parameters from single device measurements across various frequencies.
- Applied the methodology to devices under non-conducting electrical stress and varying gate-to-source bias.
Main Results:
- Accurate modeling of RF impedance up to 30 GHz achieved by incorporating additional resistive and capacitive components into the gate capacitance model.
- Successfully distinguished the contributions of different physical effects to the device's impedance.
- Demonstrated maintained correlation accuracy during off-state degradation and under different bias conditions.
Conclusions:
- The proposed methodology effectively analyzes and models dynamic effects influencing RF impedance in semiconductor devices.
- Enhanced gate capacitance models provide excellent correlation with experimental data.
- The approach is robust for assessing device degradation and performance under various operating conditions.
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