级联
红外线的
计算机科学
人工智能
算法
光子学
吸收(声学)
人工神经网络
戒指(化学)
材料科学
光电子学
工程类
光学
物理
化学
化学工程
复合材料
有机化学
作者
Jinghao Yang,Austin Caruso,Zhihai Lin,Junyan Li,Pao Tai Lin
出处
期刊:Journal of The Optical Society of America B-optical Physics
[The Optical Society]
日期:2021-09-07
卷期号:38 (11): 3292-3292
被引量:1
摘要
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.
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