Abstract

An intelligent mid-infrared (mid-IR) integrated photonic device was demonstrated applying a machine learning (ML) algorithm. The design model and the estimation model of mid-IR micro-rings were trained by the artificial neural network (ANN) to create the performance-structure relationships. The sensing devices were then designed to align the micro-ring resonance with the characteristic mid-IR absorption wavelengths according to the gases of interest. Further applying the cascade micro-ring structures enables the device to monitor several gas analytes simultaneously. The ML-based mid-IR device provides a miniaturized sensing platform for remote and precise environmental monitoring.

© 2021 Optical Society of America

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Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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