For second consecutive year two students of the Master program of Biomedical Engineering won the IE-net Awards. Florence Muller took the first place of the nominated Flemish students of the faculties engineering sciences, bio- engineering sciences, industrial engineering sciences and applied engineering sciences, Kristýna Holková won the 3rd price.

Each graduate of one of these faculties needs to belong to the top 20 % of the faculty. The best 45 candidates (15 bio-engineers, 15 civil engineers and 15 industrial engineers) are allowed to the final round after a quotation of the jury. The engineers with the highest score win the ie-net-prizes. 

Congratulations to our alumni Florence Muller and Kristýna Holková!

https://www.ugent.be/ea/nl/actueel/nieuws/ie-net-prijzen-florence-muller

On October 6th 2023 at 17.00, Rana ElKashlan will defend her PhD entitled “GAN-ON-SI TECHNOLOGY FOR MODERN WIRELESS COMMUNICATION SYSTEMS: OPTIMISATION INSIGHT USING RF CHARACTERISATION”.

Everybody is invited to attend the presentation at the Room D.2.01, or digitally via this link.

The increasing complexity of modern communication systems has resulted in optimising several different technologies for each specific function. Hence, such communication systems comprise many chips. The downscaling of Si CMOS technology has allowed for a large-scale integration level that includes the integration of high-speed transceivers on the chips. Nevertheless, the low-voltage operation of CMOS technology cannot meet the requirements of high-power, high-efficiency power amplifiers. Thus, alternate materials are of interest for power amplifier applications. GaN is one promising candidate based on its ability to operate at high frequency and power levels. However, RF Front-End Modules (RF-FEMs) include high-performance switches fabricated on semi-insulating substrates. Therefore, realising the next generations of power and cost-efficient RF systems depends highly on the co-integration of the different device technologies.

The main target of this work is the optimisation of GaN-on-Si HEMTs for use in such high-performance communication systems. This thesis tackles that by first enhancing AlCu-based gate-metal stacks in a gate-first process to mitigate the plausibility of the gate resistance becoming a limitation to the cut-off frequency of the unilateral gain (fmax). The procedure of optimising the gate-metal stack utilises small-signal RF characterisation and modelling in addition to developing a gate resistance model, which accounts for the Tshape geometry of the gate. Such modelling is necessary, given that gate resistance models and extraction methods for CMOS devices do not account for the asymmetric nature of the T-gate in GaN HEMTs. After optimising the gate-metal stack, nonlinear and large-signal characterisation, combined with small-signal equivalent circuit modelling, provide insight into the linearity trade-offs associated with varying T-gate geometries. A substantial portion of this work focuses on the compromises related to different vertical layers, namely the channel thickness and the top barrier layer. Downscaling the gate lengths below 150nm enables a higher gain, which thus facilitates superior high-frequency operation. However, shorter gate lengths may increase short-channel effects. Investigating various thinned-down barrier materials, using RF small- and large-signal characterisation, reveals the necessity of improving the device linearity for thinner top barriers by lowering the source access resistance and suppressing the gate leakage. Examining the impact of thinner channel thicknesses, in the presence of a cGaN back-barrier, on the large-signal device performance clarifies a significant trade-off between short-channel effect suppression and efficient power performance, since the rise in current collapse and dispersion negatively impacts the large-signal metrics by increasing the knee voltage and reducing the maximum current. Carefully designing a composite backbarrier can alleviate some of the on-resistance, thus enhancing the output power of thin-channel downscaled devices.

Finally, the findings of this thesis provide guidelines for GaN-on-Si technology optimisation depending on the target frequency band of operation.

1. If it is the intention, to apply for a FWO travel grant, then DO NOT use the VUB OMNIA travel platform to book your trip!
   Otherwise, if FWO approves your travel grant, it won’t be possible anymore to get reimbursement for your travel, because if booked via the VUB travel platform, OMNIA will send an invoice to VUB and FWO only pays invoices directly to OMNIA, and addressed to FWO.
   OMNIA is not willing to make a credit note for the VUB invoice and charges a fee for re-issuing an invoice.

Here you find the way to book a research travel via OMNIA, if you want to apply for a FWO ‘Travel Grant’:
Financien – RESERVERING DIENSTREIS indien gefinancierd met FWO REISKREDIET (service-now.com)
https://vub.service-now.com/sp/?id=kb_article_view&sysparm_article=KB0014417 => English

2. OMNIA is one of the VUB official travel agencies! VUB has a framework contract with OMNIA Travel. (Which you better not use in the above mentioned condition!)
   Financien – Dienstreizen: voordelen gebruik raamovereenkomst dienstreizen (service-now.com)

Lucas Moura Santana won the 2022-2023 IEEE SSCS Predoctoral Achievement Award

On June 23rd 2025 at 16:00, Adnan Al Baba will defend their PhD entitled “mm-Wave Imaging with Forward-Looking SAR: Algorithms and System Optimization”.

Everybody is invited to attend the presentation in room I.2.02 or online via this link.

This doctoral dissertation explores millimeter-wave (mm-wave) imaging for forward-looking synthetic aperture radar (FL-SAR), focusing on advancing algorithms and system design to meet the demands of autonomous applications. The research addresses critical challenges in achieving high angular resolution with FL-SAR for ground vehicles by leveraging platform motion to synthesize larger apertures and enhance imaging performance. Key contributions include novel methodologies for signal modeling, SAR image reconstruction, and computational complexity reduction. The dissertation examines advanced aspects such as multiple-input, multiple-output FL-SAR (FL-MIMO-SAR), theoretical angular resolution limits, radar-network odometry integration, motion parameter estimation, and SAR autofocus algorithms. Innovative solutions are proposed to mitigate common imaging artifacts such as sidelobes, grating lobes, and Doppler left-right ambiguities. Additionally, advanced FL-SAR processing techniques, including sequential spatial masking and decimated backprojection, are introduced to enhance image quality and computational efficiency. The proposed methodologies are quantitatively evaluated using simulation scenarios, controlled experimental data from an anechoic chamber, and real-world test data from robotics and automotive applications. These evaluations demonstrate the effectiveness of FL-SAR imaging with sparse MIMO arrays in delivering high-resolution radar images while relaxing constraints on the real aperture length. This dissertation significantly contributes to the practical realization of mm-wave FLSAR imaging systems, paving the way for their adoption in diverse fields such as automotive, robotics, aviation, security, and industrial applications.

Sarah Al Omari got awarded a PhD Fellowship fundamental research for her research “Exploring Neuromuscular Fatigue in Stroke Survivors: Central-Peripheral Interplay and the Potential of Transcranial Alternating Current Stimulation (tACS)” under supervision of Eva Swinnen, David Beckwée, Mahyar Firouzi and Bart Jansen.