Compact Modeling of Static and Transient Effects of Buffer Traps in GaN HEMTs
We propose a physics-based analytical model that accurately captures the effects of buffer traps on dc characteristics of gallium nitride (GaN)-based high-electron-mobility transistors (HEMTs). The model is then semi-analytically extended to additionally include the transient behavior. Analytical fo...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on electron devices 2022-03, Vol.69 (3), p.999-1005 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | We propose a physics-based analytical model that accurately captures the effects of buffer traps on dc characteristics of gallium nitride (GaN)-based high-electron-mobility transistors (HEMTs). The model is then semi-analytically extended to additionally include the transient behavior. Analytical formulations for the shift in the threshold voltage {(}{V}_{\text {OFF}}{)} and two-dimensional electron gas (2-DEG) density due to the presence of buffer traps in the steady state are presented. In pulsed operation, technology computer-aided design (TCAD) simulations indicate that a time-dependent negative potential (NP) is developed under the gate, resulting in a modified {V}_{\text {OFF}} and current collapse (CC). An expression for the modified {V}_{\text {off}} helps capture the pulsed current-voltage characteristics. The model captures the dependence of bias, time, temperature, trap concentration, capture cross section area, and activation energy of traps on the steady-state and transient characteristics. The model is implemented in Verilog-A in an existing compact model framework using a diode and RC sub-circuit and validated using measured data and TCAD simulations. The modeling results are in excellent agreement with the experimental data and TCAD simulations. Since the model is physics-based, it requires fewer number of parameters compared to that in the existing models. |
---|---|
ISSN: | 0018-9383 1557-9646 |
DOI: | 10.1109/TED.2022.3145334 |