Application of Automated Data Collection to Surface-Enhanced Raman Scattering (SERS)

Significance of the Topic

Surface-enhanced Raman scattering (SERS) extends Raman spectroscopy to trace and complex samples by enhancing signal via metal nanoparticles. Automating data acquisition is crucial to leverage SERS for high throughput screening in biomedical, forensic, and industrial applications. This approach reduces analyst workload and improves reproducibility.

Objectives and Overview of the Study

The goal was to demonstrate automated SERS data collection and analysis using the Thermo Scientific DXR Raman microscope coupled with Array Automation software. Two applications were explored: profiling microRNA sequences and discriminating inks on paper for forensic analysis.

Methodology and Instrumentation

Samples were prepared on gold-coated slides (DXR/SERS Analysis Kit) or paper templates with silver colloid. MicroRNA solutions (1 µg/µL) were mixed with 70 nm gold colloid, deposited, and air-dried. Ink samples were treated with silver colloid via multiple aliquots.

Instrumentation:

• Thermo Scientific DXR Raman microscope
• 780 nm and 532 nm lasers with laser power control
• Motorized stage for 12-spot or grid collection (up to 13×13 points)
• Thermo Scientific OMNIC and Array Automation software
• TQ Analyst chemometric software

Main Results and Discussion

MicroRNA Analysis:

• SERS spectra averaged over 169 points per spot revealed distinct spectral patterns correlating with nucleotide arrangement.
• Library matching achieved >98% correct identification of unknown microRNA samples.

Ink on Paper Analysis:

• SERS treatment boosted Raman signal by orders of magnitude compared to untreated inks.
• Principal component analysis of untreated Raman data misclassified 44% of spectra, whereas SERS data reduced misclassification to 3%.

Benefits and Practical Applications

The automated workflow enables:

• High throughput screening of up to 12 samples per slide with minimal operator intervention.
• Collection of thousands of spectra to improve statistical robustness.
• Applications in disease marker detection and forensic document examination.

Future Trends and Possibilities

Advances may include integration with LIMS for streamlined data handling, expanded SERS substrate chemistries for broader analyte compatibility, and real-time chemometric feedback for guided sampling. Emerging microfluidic and lab-on-a-chip designs could further accelerate automated SERS workflows.

Conclusion

Combining DXR Raman microscopy with Array Automation transforms SERS into a reproducible high throughput technique. The demonstrated microRNA identification and ink discrimination highlight its potential in biomedical diagnostics and forensic science.

References

1. Lee P.C., Meisel D. J. Phys. Chem. 1982, 86, 3391.
2. Thermo Fisher Scientific Technical Note and Application Note archives on SERS and microRNAs.