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Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates
Published on: March 20, 2015
Calixarene-Based Magnetic Nanosponge Decorating AgNPs for Rapid and Selective Surface-Enhanced Raman Scattering
Wenyao Hu1, Ling Xia1, Yufei Hu1
1School of Chemistry, Sun Yat-sen University, Guangzhou 510006, China.
None:
Rapid and accurate analysis of trace targets in complex samples remains an enormous challenge. Herein, the calix[x]arene-based magnetic cross-linked polymer decorating AgNPs, abbreviated Fe3O4-CXA-DAB@AgNPs nanosponge, was developed for fast surface-enhanced Raman scattering (SERS) analysis in complex samples. The Fe3O4-CXA-DAB@AgNPs nanosponge surface was constructed by high-density CXA units with special cavity size and structure, which could selectively recognize and enrich targets to the sensing surface by the host-guest effect and molecule interactions. The Fe3O4-C4A-DAB@AgNPs showed significant SERS enhancement to choline chloride (ChCl) and succinylcholine chloride (SCC) with an enhancement factor (EF) of 2.9 × 107 and 6.3 × 106, respectively. The Fe3O4-C6A-DAB@AgNPs exhibited high SERS activity to thiabendazole with an EF of 7.6 × 106. Introducing recognition-enrichment-separation with SERS sensing, the nanosponge could achieve rapid enrichment sensing of targets within 6-8 min. Also, the Fe3O4-CXA-DAB@AgNPs nanosponge exhibited good stability for rapid detection with relative standard deviations less than 6.3% for intra-batch (n = 25) and 6.8% for inter-batch (n = 15). Benefiting from these merits, the Fe3O4-C4A-DAB@AgNPs was employed for fast SERS analysis of ChCl and SCC in real samples. The limits of detection were 0.62 μg/L for ChCl and 2.0 μg/L for SCC. ChCl was found in feed sample with recoveries of 85.3-108%, and SCC was found in serum samples with recoveries of 85.7-111%. The methods provided a significant reference for the selective analysis of targets by regulating the calix[x]arenes cavity size to satisfy different molecules and rapid quantification strategy by integrating sample pretreatment technology with sensing detection all-in-one.

