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◆ Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy2026-09-07

Hydrophobicity-induced self-assembly of nano-tipped dendritic gold SERS substrates for machine-learning-assisted sensitive antibiotic sensing.

Xinyu Chang, Min Liao, Shujuan Meng, Chenchen Meng, Lingling Chen, Meng Zhang

原始摘要(英文原文)· Original abstract
Antibiotics are widely used in medicine, livestock farming, and agriculture, yet their overuse leads to severe environmental contamination, threatening ecosystems and human health. Surface-Enhanced Raman Scattering (SERS) holds great promise for highly sensitive detection, but its widespread practical implementation is impeded by the lack of substrates that simultaneously possess high reproducibility, ultra-sensitivity, and fabrication economy. Here, we present a hydrophobicity-induced self-assembly strategy to prepare dendritic gold nanoparticles (Au NPs) substrates, overcoming the fundamental trade-off between facile, low-cost preparation and ultrahigh detection sensitivity. By combining diffusion-limited aggregation with an enhanced non-uniform flow field on hydrophobic surfaces, tightly packed dendritic Au NPs are formed. These create ultrahigh-density electromagnetic hot spots with a local field about four times stronger than that of isolated Au NPs pairs. The resulting substrate allows label-free, rapid, and highly sensitive detection of antibiotics, achieving a detection limit of 100 ng L-1 for norfloxacin, 1-2 orders of magnitude better than existing methods. It also discriminates mixtures of norfloxacin and oxytetracycline at 10 μg L-1 via machine-learning-assisted spectral classification, and detecting antibiotic residues down to 1 μg L-1 in river water. Overall, this work offers a simple, cost-effective, and ultrasensitive SERS substrate strategy, providing a practical tool for environmental monitoring, water safety assessment, and biomedical diagnostics.
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Hydrophobicity-induced self-assembly of nano-tipped dendritic gold SERS substrates for machine-learning-assisted sensitive antibiotic sensing. — 科研速览 Science Skim