PhD - Leuven | More than two weeks ago
Electro-wetting technologies for dielectric microfluidic devices are very appealing for life science applications, as they provide solutions to control microdroplets containing biological cells in an efficient way enabling early detection of specific cells. There is a huge gain to bring this platform to larger glass substrates, enabling light-field imaging and integration of thin-film transistor smart pixels.
Integrated circuits based on flexible thin-film transistors have received lots of attention due to recent progress in literature and the pioneering option to realize multi-project wafers in thin-film transistor foundries. Low temperature polycrystalline silicon (LTPS) transistors are very attractive due to the possibility of having a full complementary CMOS flow on flexible substrate, having charge carrier mobilities exceeding 50 cm²/Vs for p-type devices. The main applications for those transistors cover a broad range from are to be employed in-pixel switches, drivers and/or amplifiers, to peripheral circuits as found in displays and imagers.
The goal of this PhD topic is to analyze several electro-wetting architectures for life science applications, whereby droplet-driving and -controlling is an important aspect next to the detection of the droplet inside a pixel, e.g. by adding local impedance measurements in the array. The PhD student will perform detailed system-level study of thin-film transistor-based electro-wetting devices. Moreover, several design solutions have to be elaborated for different available technologies, ranging from amorphous Silicon towards LTPS. It will be important to also understand the challenges of each technology and design the specific circuit and array architecture. In addition to design, the PhD student will also be responsible for the measurements, comparison of experiments and modelling. Designs will be processed in the available foundry technologies.
Required background: Electronic Engineering, Circuit Design, Affinity to technology and physics
Type of work: 10% literature study, 10% modeling, 40% design and layout, 40% characterization
Supervisor: Kris Myny
Co-supervisor: Jan Genoe
Daily advisor: Kris Myny
The reference code for this position is 2022-106. Mention this reference code on your application form.