Simultaneous and Accurate Quantification of Multiple Antibiotics in Aquatic Samples by Surface-Enhanced Raman Scattering Using a Ti3C2Tx/DNA/Ag Membrane Substrate.
Zhongning YuLu HuangZhuomin ZhangGongke LiPublished in: Analytical chemistry (2021)
Rapid and accurate analysis of multiple targets in complex samples is still a big challenge in the fast detection field. Herein, we developed a rapid and accurate strategy for simultaneous quantification of trace multiple antibiotic residues in complex aquatic samples by surface-enhanced Raman scattering (SERS) using a Ti3C2Tx/DNA/Ag membrane substrate. This membrane substrate was proven to have good uniformity, reproducibility, stability, and SERS activity by a series of characterizations. Also, this substrate combined excellent electromagnetic enhancement and chemical enhancement effects, which endowed it with good sensitivity and selectivity during SERS analysis. It achieved the integration of multitarget separation, enrichment, and in situ detection, which significantly improved the selectivity, sensitivity, accuracy, and detection throughput by membrane substrate coupling with SERS for real-sample analysis. Finally, this rapid SERS analysis strategy was successfully applied to the simultaneous quantification of trace nitrofurantoin (NFT) and ofloxacin (OFX) in aquatic samples. It was observed that trace NFT and OFX were actually detected and simultaneously quantified to be 8.0-13.7 and 42.6-49.1 μg/kg in aquatic samples, respectively, with good recoveries of 88.0-107% and relative standard deviations of 0.3-5.5%. The results were verified by a traditional high-performance liquid chromatography method with relative errors of -9.8 to 5.3%. This strategy provided a methodological reference for accurate SERS quantification of multiple targets in complex samples.
Keyphrases
- loop mediated isothermal amplification
- sensitive detection
- gold nanoparticles
- label free
- risk assessment
- raman spectroscopy
- high performance liquid chromatography
- quantum dots
- high resolution
- structural basis
- heavy metals
- single molecule
- machine learning
- big data
- cell free
- high frequency
- highly efficient
- tandem mass spectrometry
- quality improvement