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Novel Bottom‐Up SERS Substrates for Quantitative and Parallelized Analytics
Author(s) -
Strelau Katharina K.,
Schüler Thomas,
Möller Robert,
Fritzsche Wolfgang,
Popp Jürgen
Publication year - 2010
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.200900867
Subject(s) - nanotechnology , substrate (aquarium) , raman spectroscopy , nanostructure , materials science , surface enhanced raman spectroscopy , bioanalysis , nanoparticle , biosensor , raman scattering , oceanography , physics , optics , geology
Surface‐enhanced Raman spectroscopy (SERS) is an emerging technology in the field of analytics. Due to the high sensitivity in connection with specific Raman molecular fingerprint information SERS can be used in a variety of analytical, bioanalytical, and biosensing applications. However, for the SERS effect substrates with metal nanostructures are needed. The broad application of this technology is greatly hampered by the lack of reliable and reproducible substrates. Usually the activity of a given substrate has to be determined by time‐consuming experiments such as calibration or ultramicroscopic studies. To use SERS as a standard analytical tool, cheap and reproducible substrates are required, preferably with a characterization technique that does not interfere with the subsequent measurements. Herein we introduce an innovative approach to produce low‐cost and large‐scale reproducible substrates for SERS applications, which allows easy and economical production of micropatterned SERS active surfaces on a large scale. This approach is based on an enzyme‐induced growth of silver nanostructures. The special structural feature of the enzymatically deposited silver nanoparticles prevents the breakdown of SERS activity even at high particle densities (particle density >60 %) that lead to a conductive layer. In contrast to other approaches, this substrate exhibits a relationship between electrical conductivity and the resulting SERS activity of a given spot. This enables the prediction of the SERS activity of the nanostructure ensemble and therewith the controllable and reproducible production of SERS substrates of enzymatic silver nanoparticles on a large scale, utilizing a simple measurement of the electrical conductivity. Furthermore, through a correlation between the conductivity and the SERS activity of the substrates it is possible to quantify SERS measurements with these substrates.