A particle-based microfluidic molecular separation integrating surface-enhanced Raman scattering sensing for purine derivatives analysis
Autor: | Kai-Wei Chang, Jessie Shiue, Yuh-Lin Wang, Nien-Tsu Huang, Juen-Kai Wang, Ho-Wen Cheng, Yi-Ying Wang |
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Rok vydání: | 2019 |
Předmět: |
Analyte
Materials science 010401 analytical chemistry Microfluidics Substrate (chemistry) Nanotechnology 02 engineering and technology 021001 nanoscience & nanotechnology Condensed Matter Physics 01 natural sciences Fluorescence 0104 chemical sciences Electronic Optical and Magnetic Materials symbols.namesake Reagent Materials Chemistry symbols Particle Molecule 0210 nano-technology Raman scattering |
Zdroj: | Microfluidics and Nanofluidics. 23 |
ISSN: | 1613-4990 1613-4982 |
Popis: | Based on its highly specific and non-invasive features, surface-enhanced Raman scattering (SERS) has been applied for analytical chemistry or biological applications, such as identification of chemical compositions, cells or bacteria. However, if the targeted sample consists of multiple compounds, the corresponded SERS spectra would be quite difficult to analyze. To address above problems, we developed a particle-based microfluidic molecular separation (PMMS) integrating SERS substrate to separate complicate molecule mixture followed by in situ SERS detection. The platform consists of an automatic microfluidic control system to precisely control the sample and reagent flow in the PMMS–SERS device, composed of a 5-µm particle-packed separation column followed by a two-dimensional Ag nanostructural substrate. To proof-of-concept, we first tested the molecule separation functionality using the mixture of fluorescent FITC and R6G dyes. Later, we introduced the hypoxanthine and adenine mixture—main purine metabolites of E. coli—into the system for on-chip separation, identification, and quantification based on acquired SERS signatures. Overall, the miniaturized PMMS–SERS system enables an easy-to-use and sensitive analyte detection, which could be beneficial in applications requiring bacteria identification and quantification, such as environmental monitoring, AST, and drug development. |
Databáze: | OpenAIRE |
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