The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
High-yield, wafer-scale fabrication of ultralow-loss, dispersion-engineered silicon nitride photonic circuits
Open accessAbstract
Low-loss photonic integrated circuits and microresonators have enabled a wide range of applications, such as narrow-linewidth lasers and chip-scale frequency combs. To translate these into a widespread technology, attaining ultralow optical losses with established foundry manufacturing is critical. Recent advances in integrated Si 3 N 4 photonics have shown that ultralow-loss, dispersion-engineered microresonators with quality factors Q > 10 × 10 6 can be attained at die-level throughput. Yet, current fabrication techniques do not have sufficiently high yield and performance for existing and emerging applications, such as integrated travelling-wave parametric amplifiers that require meter-long photonic circuits. Here we demonstrate a fabrication technology that meets all requirements on wafer-level yield, performance and length scale. Photonic microresonators with a mean Q factor exceeding 30 × 10 6, corresponding to 1.0 dB m−1 optical loss, are obtained over full 4-inch wafers, as determined from a statistical analysis of tens of thousands of optical resonances, and confirmed via cavity ringdown with 19 ns photon storage time. The process operates over large areas with high yield, enabling 1-meter-long spiral waveguides with 2.4 dB m−1 loss in dies of only 5 × 5 mm 2 size. Using a response measurement self-calibrated via the Kerr nonlinearity, we reveal that the intrinsic absorption-limited Q factor of our Si 3 N 4 microresonators can exceed 2 × 10 8. This absorption loss is sufficiently low such that the Kerr nonlinearity dominates the microresonator’s response even in the audio frequency band. Transferring this Si 3 N 4 technology to commercial foundries can significantly improve the performance and capabilities of integrated photonics.
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Thomson, D., Zilkie, A., Bowers, J. E., Komljenovic, T., Reed, G. T., Vivien, L., Marris-Morini, D., Cassan, E., Virot, L., Fédéli, J.-M., et al. (2016) · Journal of Optics · doi:10.1088/2040-8978/18/7/073003 · Cited by 1,363
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Metadata
- Authors
- Liu, J., Huang, G., Wang, R. N., He, J., Raja, A. S., Liu, T., Engelsen, N. J., & Kippenberg, T. J.
- Venue
- Nature Communications
- Published
- 2021-04-16
- Volume
- 12
- Issue
- 1
- Pages
- 2236-2236
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3029584541
- Cited by
- 419
- References
- 79
- FWCI
- 17.93
- Type
- journal article
- Language
- en
- Open access
- gold
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- Liu, J., Huang, G., Wang, R. N., He, J., Raja, A. S., Liu, T., Engelsen, N. J., & Kippenberg, T. J. (2021). High-yield, wafer-scale fabrication of ultralow-loss, dispersion-engineered silicon nitride photonic circuits. Nature Communications. https://doi.org/10.1038/s41467-021-21973-z
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