Plasmonic Mid-Infrared Filter Array-Detector Array Chemical Classifier Based on Machine Learning,ACS Photonics

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Plasmonic Mid-Infrared Filter Array-Detector Array Chemical Classifier Based on Machine Learning
ACS Photonics ( IF 6.5 ) Pub Date : 2021-02-02 , DOI: 10.1021/acsphotonics.0c01786
Jiajun Meng ₁ , Jasper J. Cadusch ₁ , Kenneth B. Crozier _{1,

2,

3}

Affiliation

Numerous applications exist for chemical detection, ranging from the industrial production of chemicals to pharmaceutical manufacturing, environmental monitoring, and hazardous risk control. For many applications, infrared absorption spectroscopy is the favored technique, due to attributes that include short response time, high specificity, minimal drift, in situ operation, negligible sample disruption, and reliability. The workhorse instrument for infrared absorption is the Fourier transform infrared (FTIR) spectrometer. While such systems are suitable for many purposes, new applications would be enabled by small, lightweight, low power and low cost infrared microspectrometers. Here we perform a detailed study on a microspectrometer chemical classifier comprising an array of plasmonic mid-infrared spectral filters used with a photodetector array, whose outputs are analyzed by a machine learning algorithm. We conduct simulations (including noise), demonstrating the identification of six gas-phase and six liquid-phase chemicals. We study the performance of our method at detecting the concentration of acetylene.

中文翻译：

基于机器学习的等离子中红外滤光片-检测器阵列化学分类器

从化学工业生产到制药生产，环境监测和危险风险控制，化学检测有许多应用。对于许多应用，红外吸收光谱法是首选的技术，因为其属性包括响应时间短，特异性高，漂移最小，原位操作，样品破坏可忽略以及可靠性。红外吸收的主要工具是傅立叶变换红外（FTIR）光谱仪。尽管这样的系统适用于许多目的，但小型，轻便，低功耗和低成本的红外显微光谱仪将可以实现新的应用。在这里，我们对显微光谱仪化学分类器进行了详细的研究，该化学分类器包括与光电探测器阵列配合使用的等离激元中红外光谱滤光片阵列，其输出由机器学习算法进行分析。我们进行模拟（包括噪声），演示了六种气相和六种液相化学品的鉴定。我们研究了检测乙炔浓度的方法的性能。

更新日期：2021-02-17

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