Mid-Infrared (Mid-IR) Silicon-Based Photonics

Fédéli, Jean-Marc; Nicoletti, S.

doi:10.1109/jproc.2018.2844565

Cited by 40 publications

(25 citation statements)

References 89 publications

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“…For applications in the 3-8 µm range, the waveguides are composed of a SiGe40% core surrounded by Si cladding. In the 8-12 µm range, the waveguides are composed of a pure epitaxial Ge surrounded by SiGe cladding [83]. The TRL is around 5 to 6.…”

Section: Long Wavelength Silicon Photonics Platformsmentioning

confidence: 99%

Open-Access Silicon Photonics Platforms in Europe

Rahim

Goyvaerts

Szelag

et al. 2019

IEEE J. Select. Topics Quantum Electron.

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102

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Offering open-access silicon photonics-based technologies has played a pivotal role in unleashing this technology from research laboratories to industry. Fabless enterprises rely on the open-access of these technologies for their product development. In the last decade, a diverse set of open-access technologies with medium and high technology readiness levels have emerged. This paper provides a review of the open-access silicon and silicon nitride photonic IC technologies offered by the pilot lines of European research institutes and companies. The

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Section: Long Wavelength Silicon Photonics Platformsmentioning

confidence: 99%

Open-Access Silicon Photonics Platforms in Europe

Rahim

Goyvaerts

Szelag

et al. 2019

IEEE J. Select. Topics Quantum Electron.

Self Cite

102

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“…Driven by data communication in the near-IR wavelength range, silicon photonics has experienced tremendous developments in the last few decades. The transposition of this scientific and industrial success to the mid-IR (wavelengths comprised between 3 µm and 12 µm) has been envisioned some time ago [21] and is currently under rapid progress, with noteworthy developments in materials, passive and active components, laser sources, photodetectors and sensors [6]. Due to the strong absorption bands situated in this wavelength range, applications are found, for instance, in trace gas sensing, spectroscopy and imaging of biological tissues [6].…”

Section: Introductionmentioning

confidence: 99%

“…To begin with, several dielectric materials commonly used in near-IR range are absorption limited in the mid-IR, in particular silica for wavelengths above 4 µm. This, together with the constraint of full compatibility with CMOS foundries, limits the possible choice to a handful of materials, such as silicon, germanium, silicon-germanium alloys and to a lesser extent chalcogenides [6]. Besides, no single material, except germanium, covers the whole mid-IR wavelength range.…”

mentioning

confidence: 99%

Shape optimization for the design of passive mid-infrared photonic components

et al. 2019

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Shape optimization techniques were first developed in the context of mechanical engineering and, more recently, applied to photonic components for data communication. Here, motivated by the growing application potential of mid-infrared photonics driven by chemical sensing and spectroscopy, we present the design by shape optimization of passive components operating in this wavelength range. A focus is placed on the creation of designs that are fabricable and robust to manufacturing uncertainties.Keywords shape optimization · level-set · mid-IR photonics IntroductionDriven by data communication in the near-IR wavelength range, silicon photonics has experienced tremendous developments in the last few decades. The transposition of this scientific and industrial success to the mid-IR (wavelengths comprised between 3 µm and 12 µm) has been envisioned some time ago [21] and is currently under rapid progress, with noteworthy developments in materials, passive and active components, laser sources, photodetectors and sensors [6]. Due to the strong absorption bands situated in this wavelength range, applications are found, for instance, in trace gas sensing, spectroscopy and imaging of biological tissues [6].In the last decades, shape optimization techniques, boosted by additive manufacturing technologies, have been successfully applied to mechanical engineering [2]. More recently, shape optimization appeared in the domain of silicon photonics, first with simulations and designs of passive devices [8,12] and then with micro-fabrication and experimental demonstrations [15,19,7].In the context of optimal design of photonic components, most contributions rely on density methods [8,12]. This popular paradigm, originally introduced in the context of structural mechanics as a heuristic approximation of mathematical homogenization, and known in this context as the SIMP method [3], amounts to trade the conventional "black-and-white" representation of a design for a "grayscale" density function, with continuous values in the whole interval [0, 1]. This considerably simplifies the optimization process, but raises the need for an approximate modeling of the physical equations, which have to be expressed in terms of the density function, as well as issues about the interpretation of the resulting design, and notably of its "grayscale" regions, where the density function takes intermediate values in (0, 1).On the other hand, more "geometric" methods, featuring a clear representation of the boundary of the optimized shape, have been considered, relying for instance on the concepts of shape and topological N. Lebbe Univ.

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“…Silicon photonics is attracting a lot of attention as a versatile platform for photonic integration, with applications ranging from high speed optical communications [1], to mid-infrared spectroscopy [2] and bio-sensing [3]. While CMOS compatibility is one of the advantages of this platform, it also restricts the materials, and hence refractive indexes, that can be employed.…”

Section: Introductionmentioning

confidence: 99%

“…1(d)] experience difference effective indices, i.e. the metamaterial behaves like a uniaxial crystal with a permittivity tensor n2…”

mentioning

confidence: 99%