Asymmetric Nanobowl Confinement-Engineered “Plasmonic Storms” for Machine Learning-Assisted Ultrasensitive Immunochromatographic Assay of Pathogens

作者：Yuechun Li, Zhaowen Cui, Longhua Shi, Qinyuan Bao, Rui Shu, Wenxin Zhu, Wentao Zhang, Yanwei Ji, Yizhong Shen, Jie Cheng, Jianlong Wang · 发表于：Analytical Chemistry · 年份：2024 · DOI：10.1021/acs.analchem.4c03417 · 被引用次数：25 · 研究领域：Biosensors and Analytical Detection、Advanced Biosensing Techniques and Applications、Advanced biosensing and bioanalysis techniques

Efficient field enhancement effects through plasmonic chemistry for ultrasensitive biosensing still face a great challenge. Herein, nanoconfinement engineering accumulation and synergistic effects are used to develop a “plasmonic storms” strategy with a high field enhancement effect, and gold nanoparticles (AuNPs) are used as active sites for a proof of concept because of their distinctive localized surface plasmon resonance and neighborly coupled electromagnetic field. Briefly, a large number of AuNPs are selectively and accurately stacked in the confined nanocavity of the bowl-like nanostructure through an in situ-synthesized strategy, which provides a space for strong coupling of electromagnetic fields between these adjacent AuNPs, forming “plasmonic storms” with an enhanced field that is 3 orders of magnitude higher than that of free AuNPs. The proposed nanoconfinement-engineered “plasmonic storms” are demonstrated by surface-enhanced Raman scattering (SERS) and photothermal experiments and theoretically visualized by finite element simulation. Finally, the proposed “plasmonic storms” are used for enhanced colorimetric/SERS/photothermal immunochromatographic assay to detect Salmonella typhimurium with the help of a machine learning algorithm, achieving a low limit of detection of 142 CFU mL –1, highlighting the potential of nanoconfinement in biosensing.