Modelling of radiation propagation in a photonic integrated circuit based on a polymer waveguide and phasechange material nanoparticles
V.V. Ionin, V.A. Mikhalevsky, A.A. Burtsev, A.V. Kiselev, A.A. Nevzorov, N.N. Eliseev, A.A. Lotin
National Research Centre «Kurchatov Institute»
DOI: 10.26456/pcascnn/2024.16.351
Original article
Abstract: This paper presents the results of numerical modelling of optical radiation propagation in a SU-8 polymer waveguide and signal modulation at different phase states of an array of nanoparticles of the phase-change material Ge2Sb2Te5 (GST). It is shown how the transmitted radiation is modulated for different numbers of nanoparticles when placed on the top and at the edge of the waveguide. The simulation results show that in addition to the influence of the phase states (crystalline or amorphous) on the properties of the transmitted signal, in the case of nanoparticles not only reflection and absorption but also scattering of the material play a prominent role. The basic possibility of controlling the optical signal of telecommunication range passing through the interface by switching the optical active element based on nanoparticles of phase-change material is demonstrated. The concept of developing photonic integrated circuits proposed in this work is the cheapest of all known planar technologies of developing waveguide devices and allows realizing computing elements andarchitectures on its basis with a high degree of heterogeneous integration.
Keywords: photonic integrated circuits, optical waveguides, polymers, phase-change materials, chalcogenides, nanoparticles
- Vitaly V. Ionin – Researcher, National Research Centre «Kurchatov Institute»
- Vladimir A. Mikhalevsky – Researcher, National Research Centre «Kurchatov Institute»
- Anton A. Burtsev – Researcher, National Research Centre «Kurchatov Institute»
- Alexey V. Kiselev – Ph. D., Researcher, National Research Centre «Kurchatov Institute»
- Alexey A. Nevzorov – Ph. D., Researcher, National Research Centre «Kurchatov Institute»
- Nikolay N. Eliseev – Junior Researcher, National Research Centre «Kurchatov Institute»
- Andrey A. Lotin – к.ф.-м.н., заместитель руководителя отделения, National Research Centre «Kurchatov Institute»
Reference:
Ionin, V.V. Modelling of radiation propagation in a photonic integrated circuit based on a polymer waveguide and phasechange material nanoparticles / V.V. Ionin, V.A. Mikhalevsky, A.A. Burtsev, A.V. Kiselev, A.A. Nevzorov, N.N. Eliseev, A.A. Lotin // Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials. — 2024. — I. 16. — P. 351-360. DOI: 10.26456/pcascnn/2024.16.351. (In Russian).
Full article (in Russian): download PDF file
References:
1. Zhang W., Mazzarello R., Wuttig M., Ma E. Designing crystallization in phase-change materials for universal memory and neuro-inspired computing, Nature Reviews Materials, 2019, vol. 4, issue 3, pp. 150-168. DOI: 10.1038/s41578-018-0076-x.
2. Phase change materials: science and applications, ed. by S. Raoux and M. Wutting. New York, Springer Science+Business Media, LLC, 2009, 450 p. DOI: 10.1007/978-0-387-84874-7.
3. Guo P., Sarangan A. M., Agha I. A review of germanium-antimony-telluride phase change materials for non-volatile memories and optical modulators, Applied Sciences, 2019, vol. 9, issue 3, art. no. 530, 26 p. DOI: 10.3390/app9030530.
4. Ovshinsky S.R. Optical cognitive information processing–a new field, Japanese Journal of Applied Physics, 2004, vol. 43, issue 7B, pp. 4695-4699. DOI: 10.1143/JJAP.43.4695.
5. Lian C., Vagionas C., Alexoudi T. et al. Photonic (computational) memories: tunable nanophotonics for data storage and computing, Nanophotonics, 2022, vol. 11, issue 17, pp. 3823-3854. DOI: 10.1515/nanoph-2022-0089.
6. Abdollahramezani S., Hemmatyar O., Taghinejad H. et al. Tunable nanophotonics enabled by chalcogenide phase-change materials, Nanophotonics, 2020, vol. 9, issue 5, pp. 1189-1241. DOI: 10.1515/nanoph-2020-0039.
7. Han S.-T., Zhou Y. Photo-electroactive non-volatile memories for data storage and neuromorphic computing, Duxford: Woodhead Publishing, 2020, 352 p. DOI: 10.1016/C2019-0-00530-4.
8. Feldmann J., Youngblood N., Wright C.D. et al. All-optical spiking neurosynaptic networks with self-learning capabilities, Nature, 2019, vol. 569, pp. 208-214. DOI: 10.1038/s41586-019-1157-8.
9. Yu T., Ma X., Pastor E., et al. All-chalcogenide programmable all-optical deep neural networks, arXiv:2102.10398, 2021, 18 p. DOI: 10.48550/arXiv.2102.10398.
10. Sokolov V.I., Mishakov G.V., Panchenko V.Y., Tsvetkov M.Y. Routes to polymer-based photonics, Optical Memory and Neural Networks, 2007, vol. 16, issue 2, pp. 67-74. DOI: 10.3103/S1060992X07020026
11. Ramirez J.C., Schianti J.N., Almeida M.G. et al. Low-loss modified SU-8 waveguides by direct laser writing at 405 nm, Optical Materials Express, 2017, vol. 7, issue 7, pp. 2651-2659. DOI: 10.1364/OME.7.002651.
12. Suzdalev I.P. Nanotekhnologiya: Fiziko-khimiya nanoklasterov, nanostruktur i nanomaterialov [Nanotechnology: Physical chemistry of nanoclusters, nanostructures and nanomaterials], Moscow, URSS, 2017, 592 p. (In Russian).
13. Casarin B., Caretta A., Chen B. et al. Ultralow-fluence single-shot optical crystalline-to-amorphous phase transition in Ge–Sb–Te nanoparticles, Nanoscale, 2018, vol. 10, issue 35, pp. 16574-16580. DOI: 10.1039/c8nr04350g.
14. Caretta A., Casarin B., Chen B., et al. Ultrafast response of Ge2Sb2Te5 nanoparticles: The benefits of low energy amorphization switching with the same read/write speed of bulk memories, APL Materials, 2023, vol. 11, art. no. 071117, pp. 071117-1-071117-5. DOI: 10.1063/5.0156207.
15. Ionin V.V., Kiselev A.V., Burtsev A.A., et al. An optical synapse based on a polymer waveguide with a GST225 active layer, Applied Physics Letters, 2021, vol. 119, issue 8, art. no. 081105, 5 p. DOI: 10.1063/5.0063349.
16. Burtsev A.A., Ionin V.V., Kiselev A.V. Lotin A.A., Minaev N.V. Opticheskii sinaps [Optical synapse]. Patent RF, no. 2788438, 2023. (In Russian).
17. Abdelghfar A., Mousa M.A., Fouad B.M. et al. Electrostatically tuned optical filters based on hybrid plasmonic-dielectric thin films for hyperspectral imaging, Micromachines, 2021, vol. 12, issue 7, art. № 767, 14 p. DOI: 10.3390/mi12070767.