RESUMEN
In this work we describe a very fast and flexible method for fabrication of plasmon-supporting substrates with micro-patterning capability, which is optimized for plasmonic sensing. We combined a wet chemistry approach to synthesize metallic nanoparticles with a piezo-dispensing system enabling deposition of nanoparticles on the substrates with micrometer precision. In this way, an arbitrary pattern consisting of 200 µm small spots containing plasmonic nanostructures can be produced. Patterns with various nanoparticles exhibiting different plasmonic properties were combined, and the surface density of the particles could be easily varied via their solution concentrations. We showed that under controlled conditions the dispensing process caused no aggregation of the particles and it enabled full transfer of the colloidal solutions onto the substrate. This is an important condition, which enables these substrates to be used for reliable plasmonic sensing based on monitoring the spectral shift of the nanoparticles. We demonstrated the functionality of such substrates by detection of small protein adsorption on the spots based on plasmon label-free sensing method.
RESUMEN
In this research we introduce a plasmonic nanoparticle based optical biosensor for monitoring of molecular binding events. The sensor utilizes spotted gold nanoparticle arrays as sensing platform. The nanoparticle spots are functionalized with capture DNA sequences complementary to the analyte (target) DNA. Upon incubation with the target sequence, it will bind on the respectively complementary functionalized particle spot. This binding changes the local refractive index, which is detected spectroscopically as the resulting changes of the localized surface plasmon resonance (LSPR) peak wavelength. In order to increase the signal, a small gold nanoparticle label is introduced. The binding can be reversed using chemical means (10 mM HCl). It is demonstrated that multiplexed detection and identification of several fungal pathogen DNA sequences subsequently on one sensor array are possible by this approach.