Paper
9 May 2012 Ultra-thin layer chromatography and surface enhanced Raman spectroscopy on silver nanorod array substrates prepared by oblique angle deposition
Jing Chen, Justin Abell, Yao-wen Huang, Yiping Zhao
Author Affiliations +
Abstract
We demonstrate the potential use of silver nanorod (AgNR) array substrates for on-chip separation and detection of chemical mixtures by ultra-thin layer chromatography (UTLC) and surface enhanced Raman spectroscopy (SERS). The capability of the AgNR substrates to separate different compounds in a mixture was explored using a mixture of the food colorant Brilliant Blue FCF and lactic acid, and the mixtures of Methylene Violet and BSA at various concentrations. After the UTLC process, spatially-resolved SERS spectra were collected along the mobile phase development direction and the intensities of specific SERS peaks from each component were used to generate chromatograms. The AgNR substrates demonstrate the capability of separating Brilliant Blue from lactic acid, as well as revealing the SERS signal of Methylene Violet from the massive BSA background after a simple UTLC step. This technique may have significant practical implications in actual detection of small molecules from complex food or clinical backgrounds.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Chen, Justin Abell, Yao-wen Huang, and Yiping Zhao "Ultra-thin layer chromatography and surface enhanced Raman spectroscopy on silver nanorod array substrates prepared by oblique angle deposition", Proc. SPIE 8366, Advanced Environmental, Chemical, and Biological Sensing Technologies IX, 836605 (9 May 2012); https://doi.org/10.1117/12.918763
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Surface enhanced Raman spectroscopy

Silver

Molecules

Raman spectroscopy

Nanorods

Chromatography

Statistical analysis

Back to Top