/Wide bandgap Integrated Photonics Platform from UV to NIR

Wide bandgap Integrated Photonics Platform from UV to NIR

PhD - Leuven | More than two weeks ago

AlxGa1-xN complete material system for active and tunable integrated photonics from UV to NIR

Photonics, the science of generating and/or processing light waves on a micrometer-scale, is enabling evermore applications, including LED-lighting, fiber-to-the-home internet, solar panels, displays and image sensors. Recent progress in nano-fabrication now also allow to produce large-scale photonic circuits on wafer-scale with CMOS-compatible processes, providing cost-effective high-quality optical systems. Imec is playing a crucial role in the development of wafer-scale photonics, and already developed state-of-the-art integrated photonics platforms in visible and near infrared for high-speed optical communication and sensing. However, these advanced platforms still miss key capabilities like gain for defining light sources or are limited in reach towards short wavelengths for example.

This PhD will focus on the definition of an optimal material stack based on AlxGa1-xN material system for integrated photonics from UV to NIR. Combining AlN-to-GaN performant layers in advanced monolithic wafer-scale integration scheme allows indeed the definition of low loss waveguiding, modulation, mixing and source functions at wavelengths between UV and NIR. The candidate will assess multiple stack combinations from a numerical point of view taking processability considerations into account before moving towards the actual processing of basic waveguiding and modulation structures. These early results will seed the development of further advanced stacks and the demonstration of integrated sources combined with their modulator.

The ideal candidate should have:

  • an understanding of non-linear optics
  • a good understanding of numerical methods and programming
  • solid knowledge of photonic integration circuits and technology
experience with optical experiments

Required background: Engineering technology, material science, physics or equivalent

Type of work: 40% processing, 30% characterisation , 20% modeling, 10% literature

Supervisor: Pol Van Dorpe

Co-supervisor: Xavier Rottenberg

Daily advisor: Sandeep Seema Saseendran

The reference code for this position is 2023-064. Mention this reference code on your application form.

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