PhD - Leuven | More than two weeks ago
The high current and power density of GaN high electron mobility transistor (HEMT) suits applications in 5G RF, where free-space pass loss in telecommunication is high. With a GaN HEMT fabricated on Si wafers, the GaN-on-Si technology is a cost-efficient solution which has the potential to be upscaled to 8” and 12”. Imec has demonstrated GaN-on-Si HEMTs for 6 GHz and 28 GHz power amplifier applications. Next to that, we shall apply fundamental device physics towards further optimizing the GaN-on-Si HEMT performance. Physical modelling is necessary to evaluate GaN-on-Si weaknesses, namely self-heating and dislocation density impacts; it is also required to predict short-channel performance of extremely downscaled HEMT; it will also help correctly evaluate various HEMT technology options, like GaN-on-Si vs GaN-on-SiC, Ga-polar vs N-polar, and AlGaN vs InAlN vs AlN barrier devices.
In this PhD topic, you will construct physical and TCAD models based on electrical characterizations of GaN-on-Si transistors. You will update or innovate test routines to extract physical parameters and investigate key technological factors. DC and pulse based measurement will be frequent. GaN-on-Si transistors with various flavors will be fabricated in imec 200mm production line with teamwork. You will thus communicate frequently with different experts in integration, epitaxy, device physics and reliability domains. You will master strong semiconductor and RF physics and get familiar with III-N material properties. You will contribute your insights to device-technology co-optimization of imec GaN RF applications.
Required background: Master’s degree in Electrical Engineering, Nanoscience and Nanotechnology or equivalent, with a solid background in semiconductor physics and interest in RF/microwave techniques.
Type of work: Literature study: 25%, Characterization: 25%, TCAD: 25%, Theoretical modelling: 25%
Supervisor: Benoit Bakeroot
Co-supervisor: Bertrand Parvais
Daily advisor: Hao Yu
The reference code for this position is 2023-070. Mention this reference code on your application form.