| Project Detail |
With the proposed research project, I aim to revolutionize optical metasurface design leveraging surrogate modelling techniques (OBJ1) towards the development of 3D-printed, achromatic, high numerical aperture (NA) metalens-enhanced fibres, called metafibres (OBJ2). The proposed methodology consists of three interconnected phases: firstly (WP1), constructing a supercell meta-atom library consisting of three-dimensional metaatoms through iterative optimization. The simulated designs will be 3D-printed and the simulation model updated based on the results of the experimental characterization, ensuring precise and realistic control of meta-atom responses. Secondly (WP2), a Gaussian Process Regression (GPR) will be implemented as a versatile surrogate model using the established supercell library. This machine learning technique enables the efficient prediction of complex optical meta supercell responses, facilitating rapid prototyping and customization with reduced computational overhead. Notably, GPR models allow to consider fabrication tolerances straight-forward in combination with data augmentation techniques. Lastly (WP3), I will exploit the GPR model for the design of high-performing achromatic metafibres, utilizing 3D-printing technology to directly print the metalenses on the tip of optical fibres.
I have chosen a top research centre, Leibniz Institute of Photonic Technology/ Jena, Germany, to develop my MSCA project under supervision of a world-leading expert in optical fiber photonics. Using my knowledge in engineering, photonics and numerical simulation tools, this MSCA project will pave the way for metafibres promising versatile and broadband optical solutions with the potential to transform fields like microscopy, telecommunications and medical imaging. This research aligns with sustainability goals by minimizing material waste and energy consumption in the fabrication process, marking a significant advancement in metasurface and optical system design. |
