journal article·2019-12-01Open access

Femtosecond laser additive and subtractive micro-processing: enabling a high-channel-density silica interposer for multicore fibre to silicon-photonic packaging

Gligor Djogo, Jianzhao Li, Stephen Ho, Moez Haque, Erden Ertorer, Jun Liu, Xiaolu Song, Jing Suo, Peter R Herman

Abstract

Abstract Great strides have been made over the past decade to establish femtosecond lasers in advanced manufacturing systems for enabling new forms of non-contact processing of transparent materials. Research advances have shown that a myriad of additive and subtractive techniques is now possible for flexible 2D and 3D structuring of such materials with micro- and nano-scale precision. In this paper, these techniques have been refined and scaled up to demonstrate the potential for 3D writing of high-density optical packaging components, specifically addressing the major bottleneck for efficiently connecting optical fibres to silicon photonic (SiP) processors for use in telecom and data centres. An 84-channel fused silica interposer was introduced for high-density edge coupling of multicore fibres (MCFs) to a SiP chip. Femtosecond laser irradiation followed by chemical etching was further harnessed to open alignment sockets, permitting rapid assembly with precise locking of MCF positions for efficient coupling to laser written optical waveguides in the interposer. A 3D waveguide fanout design provided an attractive balancing of low losses, mode-matching, high channel density, compact footprint, and low crosstalk. The 3D additive and subtractive processes thus demonstrated the potential for higher scale integration and rapid photonic assembly and packaging of micro-optic components for telecom interconnects, with possible broader applications in integrated biophotonic chips or micro-displays.
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Research context

OpenAlex topics: Laser Material Processing Techniques · Advanced Surface Polishing Techniques · Optical Coherence Tomography Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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