| Title: | Interpreting convolutional neural network for real-time volatile organic compounds detection and classification using optical emission spectroscopy of plasma |
| Address: | "Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan. Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan. Electronic address: chsu@ntu.edu.tw" |
| DOI: | 10.1016/j.aca.2021.338822 |
| ISSN/ISBN: | 1873-4324 (Electronic) 0003-2670 (Linking) |
| Abstract: | "This study presents the investigation of optical emission spectroscopy of plasma using interpretable convolutional neural network (CNN) for real-time volatile organic compounds (VOCs) classification. A microplasma-generation platform was developed to efficiently collect 64 k spectra from various types of VOCs at different concentrations, as training and testing sets for machine learning. A CNN model was trained to classify VOCs with accuracy of 99.9%. To interpret the CNN model and its predictions, the spectral processing mechanism of the CNN was visualized by feature maps and the critical spectral features were identified by gradient-weighted class activation mapping. Such approaches brought insights on how CNN analyzes the spectra and enables the CNN operation to be explainable. Finally, the CNN model was incorporated with the microplasma platform to demonstrate the application of real-time VOC monitoring. The type of VOCs can be identified and reported via messages within 10 s once the microplasma is ignited. We believe that using CNN brings a novel route for plasma spectroscopy analysis for VOC classification and impacts the fields of plasma, spectroscopy, and environmental monitoring" |
| Keywords: | "Neural Networks, Computer Spectrum Analysis *Volatile Organic Compounds Grad-CAM Machine learning Microplasma Optical emission spectroscopy;" |
| Notes: | "MedlineWang, Ching-Yu Ko, Tsung-Shun Hsu, Cheng-Che eng Netherlands 2021/09/19 Anal Chim Acta. 2021 Sep 22; 1179:338822. doi: 10.1016/j.aca.2021.338822. Epub 2021 Jul 3" |
