Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water
Abstract This study presents a dual-functional thin film, known as Ag nanoparticles decorated, ZnO nanorods coated silica nanofibers (AgNP-ZnONR-SNF), which demonstrates remarkable capabilities in both water purification and organic pollutants sensing. The 3D fibrous structure of ZnONR-SNF provides...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-01-01
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| Series: | npj Clean Water |
| Online Access: | https://doi.org/10.1038/s41545-023-00292-4 |
| _version_ | 1797350157137739776 |
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| author | Junhu Zhou Ziqian Wu Congran Jin John X. J. Zhang |
| author_facet | Junhu Zhou Ziqian Wu Congran Jin John X. J. Zhang |
| author_sort | Junhu Zhou |
| collection | DOAJ |
| description | Abstract This study presents a dual-functional thin film, known as Ag nanoparticles decorated, ZnO nanorods coated silica nanofibers (AgNP-ZnONR-SNF), which demonstrates remarkable capabilities in both water purification and organic pollutants sensing. The 3D fibrous structure of ZnONR-SNF provides a large surface-area-to-volume ratio for piezo- and photo-catalytic degradation of organic pollutants under UV irradiation, achieving over 98% efficiency. Ag nanoparticles decorated on ZnONR-SNF form “hot-spot” that significantly enhance the surface-enhanced Raman spectroscopy (SERS) signal, resulting in an enhancement factor of 1056 and an experimental detection limit of 1 pg mL−1. Furthermore, a machine learning algorithm is developed for the qualitative and quantitative detection of multiple contaminants, achieving high accuracy (92.3%) and specificity (89.3%) without the need for preliminary processing of Raman spectra. This work provides a promising nanoengineering solution for water purification and sensing with improved detection accuracy, purification efficiency, and cost-effectiveness. |
| first_indexed | 2024-03-08T12:41:43Z |
| format | Article |
| id | doaj.art-c495bcf7625a4f2283563594b109c4da |
| institution | Directory Open Access Journal |
| issn | 2059-7037 |
| language | English |
| last_indexed | 2024-03-08T12:41:43Z |
| publishDate | 2024-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Clean Water |
| spelling | doaj.art-c495bcf7625a4f2283563594b109c4da2024-01-21T12:08:31ZengNature Portfolionpj Clean Water2059-70372024-01-017111110.1038/s41545-023-00292-4Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in waterJunhu Zhou0Ziqian Wu1Congran Jin2John X. J. Zhang3Thayer School of Engineering, Dartmouth CollegeThayer School of Engineering, Dartmouth CollegeThayer School of Engineering, Dartmouth CollegeThayer School of Engineering, Dartmouth CollegeAbstract This study presents a dual-functional thin film, known as Ag nanoparticles decorated, ZnO nanorods coated silica nanofibers (AgNP-ZnONR-SNF), which demonstrates remarkable capabilities in both water purification and organic pollutants sensing. The 3D fibrous structure of ZnONR-SNF provides a large surface-area-to-volume ratio for piezo- and photo-catalytic degradation of organic pollutants under UV irradiation, achieving over 98% efficiency. Ag nanoparticles decorated on ZnONR-SNF form “hot-spot” that significantly enhance the surface-enhanced Raman spectroscopy (SERS) signal, resulting in an enhancement factor of 1056 and an experimental detection limit of 1 pg mL−1. Furthermore, a machine learning algorithm is developed for the qualitative and quantitative detection of multiple contaminants, achieving high accuracy (92.3%) and specificity (89.3%) without the need for preliminary processing of Raman spectra. This work provides a promising nanoengineering solution for water purification and sensing with improved detection accuracy, purification efficiency, and cost-effectiveness.https://doi.org/10.1038/s41545-023-00292-4 |
| spellingShingle | Junhu Zhou Ziqian Wu Congran Jin John X. J. Zhang Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water npj Clean Water |
| title | Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water |
| title_full | Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water |
| title_fullStr | Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water |
| title_full_unstemmed | Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water |
| title_short | Machine learning assisted dual-functional nanophotonic sensor for organic pollutant detection and degradation in water |
| title_sort | machine learning assisted dual functional nanophotonic sensor for organic pollutant detection and degradation in water |
| url | https://doi.org/10.1038/s41545-023-00292-4 |
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