Project Details
Physics-based microwave GaN HEMT statistical modeling
Applicant
Professor Dr.-Ing. Matthias Rudolph
Subject Area
Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
Communication Technology and Networks, High-Frequency Technology and Photonic Systems, Signal Processing and Machine Learning for Information Technology
Communication Technology and Networks, High-Frequency Technology and Photonic Systems, Signal Processing and Machine Learning for Information Technology
Term
since 2024
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 535764088
The design of integrated microwave circuits relies on numerical circuit simulation, where the quality of the transistor model is the key factor to obtain highly precise simulation results. Usually, so-called compact transistor models are used, that describe the transistor's electrothermal behavior based on a nonlinear equivalent circuit. The equivalent circuit elements are defined through parameterized functions. This approach allows for a general physics-based definition of a transistor model, which can be adapted to a specific transistor process by parameter fitting. But in reality, not two transistors are identical. There are, for example, systematic parameter spreads depending on where the transistor is positioned on the waver, and stochastic variations in epitaxy and process technology. If a transistor model ignores these variations and only describes the ideal transistor, the designer will miss any information on how the transistor parameter spread impacts integrated circuit performance and yield will be below optimum. Hence, it is imperative to treat the compact transistor model's parameters as stochastic variables. Such a model will be called a statistical model in the following. It is the goal of this project, to define a statistical model for GaN HEMTs. By considering the physical effects governing the electrical performance, we aim at minimizing the number of independent stochastic variables. In this respect, it poses a specific scientific challenge that physics-based compact models for GaN devices were formulated only recently. Not only are these models younger than their silicon transistor counterparts, they also rely more often on physics-motivated fitting formulae. Another significant challenge is the presence of deep traps in GaN HEMTs, leading to dispersion in the electrical behavior, and modeling of GaN HEMT dispersion is in itself still a matter of ongoing research.
DFG Programme
Research Grants
International Connection
Israel
Co-Investigator
Dr. Oliver Hilt
Cooperation Partner
Professor Dan Ritter, Ph.D.