SmartSERS

SmartSERS is a laser-structured silicon substrate for sensitive and reproducible surface-enhanced Raman spectroscopy (SERS). Its precisely structured surface provides a versatile platform for detecting and identifying traces of chemical and biological substances by Raman spectroscopy, across a wide range of analytical applications.

SmartSERS combines laser-induced periodic surface structures (LIPSS) with plasmonic gold nanostructures to enhance the Raman signal. The enhancement results from the combined effect of surface plasmon polaritons and localized surface plasmon resonances. The structure’s periodicity of 798 nm is closely matched to the excitation wavelength of 785 nm and promotes coupling to surface plasmon polaritons along the structured surface. In addition, gold nanoparticles on the LIPSS generate strongly confined electromagnetic fields and dense “hot spots” for Raman detection.

Technical data

• Structure: 1D LIPSS (laser-induced periodic surface structures)
• Periodicity: 798 nm, depth: 850 nm
• Coating: 50 nm gold (e-beam evaporation)
• Excitation: optimized for 785 nm, suitable for red and near-infrared excitation (633–830 nm)
• Enhancement: > 10⁵ (thiophenol, 785 nm)
• Active area: entire surface
• Chip size: custom sizes and shapes on request (round, square, rectangular or custom-designed), up to 3-inch wafer, laser dicing

SERS performance was evaluated using thiophenol (1 mM in ethanol) as a probe molecule. The solution was drop-cast onto the substrate and dried under ambient conditions, and the Raman spectra were recorded at 785 nm excitation using a 100× objective (NA 0.9). The spectrum shows the characteristic thiophenol peaks at 419, 998, 1022, 1073 and 1574 cm⁻¹ on SmartSERS compared to a commercial gold SERS substrate.

For enquiries about sizes, shapes and quantities, please contact us.

The further development of SmartSERS is funded by the Federal Ministry for Economic Affairs and Energy (BMWE) within the Central Innovation Programme for SMEs (ZIM), project “Laser-BioMNP” (funding reference 16KN127120).