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基于聚焦离子束铣削的用于折射率传感的学习增强型光纤散斑图传感器的演示。

Demonstration of a Learning-Empowered Fiber Specklegram Sensor Based on Focused Ion Beam Milling for Refractive Index Sensing.

作者信息

Gu Liangliang, Gao Han, Hu Haifeng

机构信息

School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Zhangjiang Laboratory, 100 Haike Road, Shanghai 201204, China.

出版信息

Nanomaterials (Basel). 2023 Feb 18;13(4):768. doi: 10.3390/nano13040768.

Abstract

We report a simple and robust fiber specklegram refractive index sensor with a multimode fiber-single mode fiber-multimode fiber structure based on focused ion beam milling. In this work, a series of fluid channels are etched on the single-mode fiber by using focused ion beam milling to enhance the interaction between light and matter, and a deep learning model is employed to demodulate the sensing signal according to the speckle patterns collected from the output end of the multimode fiber. The feasibility and effectiveness of the proposed scheme were verified by rigorous experiments, and the test results showed that the demodulation accuracy and speed could reach 99.68% and 4.5 ms per frame, respectively, for the refractive index range of 1.3326 to 1.3679. The proposed sensing scheme has the advantages of low cost, easy implementation, and a simple measurement system, and it is expected to find applications in various chemical and biological sensing.

摘要

我们报道了一种基于聚焦离子束铣削的具有多模光纤-单模光纤-多模光纤结构的简单且稳健的光纤散斑图折射率传感器。在这项工作中,通过聚焦离子束铣削在单模光纤上蚀刻出一系列流体通道,以增强光与物质之间的相互作用,并采用深度学习模型根据从多模光纤输出端收集的散斑图案来解调传感信号。通过严格的实验验证了所提方案的可行性和有效性,测试结果表明,对于1.3326至1.3679的折射率范围,解调精度和速度分别可达99.68%和每帧4.5毫秒。所提传感方案具有成本低、易于实现且测量系统简单的优点,有望在各种化学和生物传感中得到应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4336/9958950/c531378e2e20/nanomaterials-13-00768-g001.jpg

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