Abstract:
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[EN] In this paper, we present a systematic design for manufacturing analysis for thermo-optic phase tuners, framed within the process modules available on a silicon nitride platform. Departing from an established technology ...[+]
[EN] In this paper, we present a systematic design for manufacturing analysis for thermo-optic phase tuners, framed within the process modules available on a silicon nitride platform. Departing from an established technology platform, the heat distribution in various micro-structures was analyzed, both in steady and transient states, employing a 2D heat transfer model solved numerically. Multi-parametric simulations were performed on designs combining trenches and substrate undercut, by varying their position and dimensions. The simulation results were compared to a reference conventional fully-clad cross-section. Deep air-filled trenches are shown to reduce the power consumption up to 70%, alongside a thermal crosstalk phase shift reduction of more than one order of magnitude (0.045 pi rad/mm), at the expense of a slightly lower bandwidth (11.8 kHz). The design with trenches and substrate undercut lowers the power consumption up to 97%, decreases two orders of magnitude the crosstalk (0.006 pi rad/mm), at the cost of less than one order of magnitude in bandwidth (0.9 kHz). In the works, we selected three different heater materials (Cr/Au, Al, poly-silicon) offered by the fab and four different heater widths (2.5 to 7 mu m). Their combinations are related to performance, reliability and durability of the devices, strongly linked to temperature, current density, and Omegaic resistance. The different figures of merit defined, and the methodology followed, can be mimicked by future designers to take design decisions at bird's eye.
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Thanks:
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Funding This research was funded by Ministry of Economy, Industry and Competitiveness grants numbers TEC2016-80385-P SINXPECT and PID2019-110877GB-I00 BHYSINPICS, Generalitat Valenciana grant number PROMETEO/2017/103, ...[+]
Funding This research was funded by Ministry of Economy, Industry and Competitiveness grants numbers TEC2016-80385-P SINXPECT and PID2019-110877GB-I00 BHYSINPICS, Generalitat Valenciana grant number PROMETEO/2017/103, Ministry of Science, Innovation and Universities grant number MCIU-RTI2018-100773-B-C31 and by H2020 Marie Sklodowska Curie Innovative Training Network grant number MICROCOMB (GA 812818).
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