| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 13005 | |
| Number of page(s) | 2 | |
| Section | Focused Sessions (FS) 4- Machine Learning and Photonic Artificial Intelligence / Optical Neural Networks and Neuromorphic Computing | |
| DOI | https://doi.org/10.1051/epjconf/202328713005 | |
| Published online | 18 October 2023 | |
https://doi.org/10.1051/epjconf/202328713005
(3+1)D printing towards the scalable and efficient integration of high-performance hybrid platforms
1 Institut FEMTO-ST, Université de Franche-Comté, CNRS UMR6174, Besançon, France.
2 Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow G1 1RD, UK
* e-mail: adria.grabulosa@femto-st.fr
Published online: 18 October 2023
We employ one-and two-photon polymerizatin, i.e. flash-TPP printing, which is compatible with metal-oxid-semiconductor (CMOS) technology, to fabricate polymer-cladded and single-mode 3D pho-tonic waveguides and adiabatic splitters. Our 3D technology is a major step forward towards the highly-interconnection required in optical neural networks, which removes the high energy dissipation of electronics and where 3D integration enables scalability that is challenging to realize in 2D.
© The Authors, published by EDP Sciences, 2023
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