{"title":"利用光捕获辅助二次谐波产生和激光诱导等离子体的高灵敏度生物气溶胶检测:协同表面和内部分析","authors":"Chen Niu, Yifan Cheng, Kai Wang, Chao Guan, Mengsheng Zhang, Jianjun Song, Yuanchao Liu, Zhenlin Hu, Zhiyong Ouyang, Lianbo Guo","doi":"10.1021/acsphotonics.4c02239","DOIUrl":null,"url":null,"abstract":"Laser probes have tremendous potential in biological aerosol, and laser-induced plasma probes (LIPP) underpin the recent development of real-time biological aerosol detection, enabling the tracing of aerosol species information. However, laser probes suffer from low hit rates and accuracy due to the weak signals of aerosols and their susceptibility to interference. Specifically, LIPP analyzes aerosols by breaking them down to obtain elemental information, often ignoring the inherent surface information. Herein, optical trapping-assisted second harmonic generation (SHG) was utilized to investigate small amounts of aerosols. The results demonstrate that optical trapping effectively controlled the aerosol count, from a few tens to single particles. Additionally, the adsorption free energy of trans-4-[(4-dimethylamino)styryl]-1-methylpyridinium iodide molecules on the bioaerosol surface was determined. Furthermore, optical trapping-assisted LIPP detected principal elements (K, Ca, Na, and Mg) in the bioaerosol. The homologous heterogeneous information (spectra, sound (shock wave images), and plasma images) of the plasma was analyzed, and multiple signals were complementarily corrected to enhance the classification accuracy of LIPP analysis. Finally, to enhance LIPP and SHG data mining, we proposed an artificial intelligence (AI)-driven adaptive multimodal attention fusion network, which improved the classification accuracy of 13 bioaerosols from 83% to 96%. This work establishes a highly sensitive laser probe detection platform that synergistically analyzes surface adsorption and internal element components, paving the way for future single-bioaerosol detection and alarm systems.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"24 1","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-Sensitivity Bioaerosol Detection via Optical Trapping-Assisted Second Harmonic Generation and Laser-Induced Plasma: Synergistic Surface and Internal Analysis\",\"authors\":\"Chen Niu, Yifan Cheng, Kai Wang, Chao Guan, Mengsheng Zhang, Jianjun Song, Yuanchao Liu, Zhenlin Hu, Zhiyong Ouyang, Lianbo Guo\",\"doi\":\"10.1021/acsphotonics.4c02239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Laser probes have tremendous potential in biological aerosol, and laser-induced plasma probes (LIPP) underpin the recent development of real-time biological aerosol detection, enabling the tracing of aerosol species information. However, laser probes suffer from low hit rates and accuracy due to the weak signals of aerosols and their susceptibility to interference. Specifically, LIPP analyzes aerosols by breaking them down to obtain elemental information, often ignoring the inherent surface information. Herein, optical trapping-assisted second harmonic generation (SHG) was utilized to investigate small amounts of aerosols. The results demonstrate that optical trapping effectively controlled the aerosol count, from a few tens to single particles. Additionally, the adsorption free energy of trans-4-[(4-dimethylamino)styryl]-1-methylpyridinium iodide molecules on the bioaerosol surface was determined. Furthermore, optical trapping-assisted LIPP detected principal elements (K, Ca, Na, and Mg) in the bioaerosol. The homologous heterogeneous information (spectra, sound (shock wave images), and plasma images) of the plasma was analyzed, and multiple signals were complementarily corrected to enhance the classification accuracy of LIPP analysis. Finally, to enhance LIPP and SHG data mining, we proposed an artificial intelligence (AI)-driven adaptive multimodal attention fusion network, which improved the classification accuracy of 13 bioaerosols from 83% to 96%. This work establishes a highly sensitive laser probe detection platform that synergistically analyzes surface adsorption and internal element components, paving the way for future single-bioaerosol detection and alarm systems.\",\"PeriodicalId\":23,\"journal\":{\"name\":\"ACS Photonics\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2025-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Photonics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1021/acsphotonics.4c02239\",\"RegionNum\":1,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Photonics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1021/acsphotonics.4c02239","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
High-Sensitivity Bioaerosol Detection via Optical Trapping-Assisted Second Harmonic Generation and Laser-Induced Plasma: Synergistic Surface and Internal Analysis
Laser probes have tremendous potential in biological aerosol, and laser-induced plasma probes (LIPP) underpin the recent development of real-time biological aerosol detection, enabling the tracing of aerosol species information. However, laser probes suffer from low hit rates and accuracy due to the weak signals of aerosols and their susceptibility to interference. Specifically, LIPP analyzes aerosols by breaking them down to obtain elemental information, often ignoring the inherent surface information. Herein, optical trapping-assisted second harmonic generation (SHG) was utilized to investigate small amounts of aerosols. The results demonstrate that optical trapping effectively controlled the aerosol count, from a few tens to single particles. Additionally, the adsorption free energy of trans-4-[(4-dimethylamino)styryl]-1-methylpyridinium iodide molecules on the bioaerosol surface was determined. Furthermore, optical trapping-assisted LIPP detected principal elements (K, Ca, Na, and Mg) in the bioaerosol. The homologous heterogeneous information (spectra, sound (shock wave images), and plasma images) of the plasma was analyzed, and multiple signals were complementarily corrected to enhance the classification accuracy of LIPP analysis. Finally, to enhance LIPP and SHG data mining, we proposed an artificial intelligence (AI)-driven adaptive multimodal attention fusion network, which improved the classification accuracy of 13 bioaerosols from 83% to 96%. This work establishes a highly sensitive laser probe detection platform that synergistically analyzes surface adsorption and internal element components, paving the way for future single-bioaerosol detection and alarm systems.
期刊介绍:
Published as soon as accepted and summarized in monthly issues, ACS Photonics will publish Research Articles, Letters, Perspectives, and Reviews, to encompass the full scope of published research in this field.