Physics-Based Nonlinear Capacitance Model Considering Velocity Saturation Effect
Accurate modeling of nonlinear capacitance is significant for physics-based compact modeling of GaN high-electric-mobility transistor (HEMT). For conventional methods, physical modeling of the electron velocity saturation effect (VSE) is often hard to realize in nonlinear capacitance models due to the lack of an effective boundary potential model. In this article, an improved capacitance modeling method that incorporates the VSE within the drift-diffusion regime is proposed, based on the quasi-physical zone division (QPZD) model theory. First, a bias-dependent equivalent length model for the saturation region in the channel induced by VSE, is derived. This model is then integrated into the boundary potential calculation to fully account for VSE. Next, the nonlinear capacitance model is developed by comprehensively considering the VSE in both the effective gate length model and the integral boundary, calculated using the proposed boundary potential model. This approach contributes to the accuracy improvement for the intrinsic capacitance characteristics in the saturation region. Finally, the nonlinear capacitance model, incorporating VSE, is validated using nonlinear capacitance data extracted from multi-bias <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i>-parameters. The verification results demonstrate that the proposed method provides an average accuracy improvement of over 11.5% in nonlinear capacitance characterization.
Authors
- Xiang Su
- Shuman Mao (ORCID: https://orcid.org/0000-0003-1247-2446)
- Bo Yan (ORCID: https://orcid.org/0000-0003-0256-9682)
- Min Tang (ORCID: https://orcid.org/0000-0002-0716-912X)
- Yuehang Xu (ORCID: https://orcid.org/0000-0003-1706-2681)
- Ruimin Xu
Institutions
- University of Electronic Science and Technology of China (CN)
- Shanghai Jiao Tong University (CN)
Publication Details
- Journal
- IEEE Transactions on Electron Devices
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1109/ted.2025.3573302
- Citations
- 1
- Primary Topic
- GaN-based semiconductor devices and materials
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- National Natural Science Foundation of China
- Tianjin Science and Technology Program