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/Job opportunities/Development of reliable, high commutation speed GaN power devices, with applications in LIDAR for self-driving vehicles

Development of reliable, high commutation speed GaN power devices, with applications in LIDAR for self-driving vehicles

PhD - Leuven | More than two weeks ago

BEOL reliability for GaN power devices

Title: Development of reliable, high commutation speed GaN power devices, with applications in LIDAR for self-driving vehicles

 

GaN is an exciting new semi-conductor technology which promises a revolution in the distribution and control of electrical power, enabling the control of high power while at the same time wasting less energy. However, the potential for this technology goes beyond mere power control and at IMEC we are developing a new class of GaN power switches which have very high commutation speed. These switches are ideally suited for demanding applications such as LIDAR, which is an imaging technology used to enable self-driving vehicles. The novel GaN switches, will enable a breakthrough in LIDAR system design, enabling a much higher resolution imaging compared to what is currently possible with a comparable silicon component.

 

Your goals as a PhD. student is to help develop this technology and bring it to a level of maturity such that the GaN components can be used reliably in these novel applications. It will be your mission to study the reliability of these components, in particular related to the back-end-of-line. High power, fast commutating devices require a very particular cross-bar architecture for interconnecting and routing the power through the different levels of the components. Moreover the interconnect levels are used to distribute the electrical fields near the gate. You will study the impact of high currents on the degradation of the metal layers over time and the impact of high electrical fields on the degradation of the dielectrics over time. You will evaluate the validity of existing degradation models for the specific materials and structures and adapt these models where needed through modelling, accelerated testing and material investigation. This will be in strong interaction with the process integration engineer, such that jointly the technology can be developed, with you as a PhD. student making suggestions for experiments and improvements in the technology.

 

 

Typical techniques and tools which the candidate will need to apply during the course of the PhD. will be electromigration measurements, ramped voltage stresses and time dependent dielectric breakdown in different environments at high temperatures, during thermal cycles, in higher humidity,... Proficiency in scripting, needed for automatic data collection and analysis, is a strong plus for a successful candidate.



Required background: Material Science, Physics or electrical engineering

Type of work: Literature (10%). Modeling (20%), Technology (10%), Experimental (60%)

Supervisor: Ingrid De Wolf

Daily advisor: Olalla Varela Pedreira, Kristof Croes

The reference code for this position is 2021-072. Mention this reference code on your application form.

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