High-Sensitivity Bioaerosol Detection via Optical Trapping-Assisted Second Harmonic Generation and Laser-Induced Plasma: Synergistic Surface and Internal Analysis

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.