Supramolecular Plasmonic Nanogap Engineering for Machine Learning Decoded Multiplex Chiral Amino Acid SERS Analysis

Area of Science:

• Analytical Chemistry
• Supramolecular Chemistry
• Nanotechnology

Background:

• Chiral recognition sensing is crucial for pharmaceuticals and biomedicine.
• Existing methods face challenges in high-resolution enantiomer identification, mechanistic understanding, and complex mixture analysis.
• Developing effective chiral sensing platforms remains a significant scientific pursuit.

Purpose of the Study:

• To develop a supramolecular plasmonic nanoparticle-on-mirror (NPoM) platform for enhanced surface-enhanced Raman scattering (SERS) chiral sensing.
• To enable high-resolution identification and characterization of enantiomers, including in complex mixtures.
• To elucidate the molecular mechanisms of chiral recognition and improve analytical efficacy.

Main Methods:

• Fabrication of a supramolecular plasmonic nanoparticle-on-mirror (NPoM) platform using sulfhydryl-functionalized β-cyclodextrin (β-CD) and gold nanoparticles (AuNPs) on a gold film (AuF).
• Utilizing the platform for selective capture of chiral amino acids and generation of plasmonic nanogap hotspots for SERS signal enhancement.
• Employing density functional theory (DFT) calculations to investigate chiral recognition mechanisms and integrating machine learning (ML) algorithms for data analysis and prediction.

Main Results:

• The NPoM platform achieved high-resolution identification and enantioselective discrimination of aromatic amino acid enantiomers.
• DFT calculations revealed diastereomeric complex formation and differential binding affinities as the chiral recognition mechanism.
• Integration with ML algorithms enabled rapid, accurate enantiomer classification and robust blind prediction, even for complex mixtures.

Conclusions:

• The developed supramolecular plasmonic NPoM platform offers a powerful strategy for advanced chiral analysis.
• The platform overcomes key challenges in enantiomer identification, mechanistic understanding, and complex mixture analysis.
• This approach significantly advances the capabilities of chiral sensing in various scientific and industrial applications.