Label-Free Spectroscopic SARS-CoV-2 Detection on Versatile Nanoimprinted Substrates

Area of Science:

• Nanotechnology
• Spectroscopy
• Machine Learning
• Virology

Background:

• Effective viral outbreak management relies on widespread testing and isolation.
• The COVID-19 pandemic highlighted the need for rapid and accurate diagnostic tools.

Purpose of the Study:

• To develop a large-area, label-free testing platform for rapid and accurate detection of SARS-CoV-2.
• To demonstrate the platform's capability in detecting virus signatures in complex biological matrices.

Main Methods:

• Utilized surface-enhanced Raman spectroscopy (SERS) combined with machine learning.
• Fabricated metal-insulator-metal nanostructures using nanoimprint lithography and transfer printing.
• Analyzed spectroscopic signatures from virus samples for identification.

Main Results:

• Achieved rapid (25 min) and accurate detection of SARS-CoV-2.
• Successfully distinguished between different respiratory and nonrespiratory viruses.
• Demonstrated detection of virus signatures in human saliva without sample preparation.
• Developed a large-area nanopatterning approach for flexible and wearable sensors.

Conclusions:

• The developed platform offers a versatile, portable, and label-free solution for virus detection.
• This technology can significantly contribute to virus detection strategies and future outbreak preparedness.
• The flexible sensor fabrication enables diverse applications, including wearable devices.