By exploiting the specific interactions between biomolecules and surface defects in hexagonal boron nitride (hBN), we discovered that small biomolecules—including lipids, nucleotides, amino acids, and glycans—can selectively activate photon emissions from defects on the hBN surface under aqueous conditions. These emissions are highly sensitive to the molecular structure, enabling us to extract distinct optical signatures specific to individual biomolecules.
Building on this discovery, we developed a novel label-free detection platform using sPAINT,. This approach captures spatial, spectral, and temporal information of the transient molecule-activated defect emissions. The integration of machine learning algorithms into the analysis pipeline allowed us to classify these emissions and identify different biomolecules with high precision. As a proof-of-concept, we successfully demonstrated the identification of five amino acids at the single-molecule level without requiring labeling or external modification.
It provides a powerful tool for advancing single-molecule biophysics by enabling the study of biomolecules in their native states. The label-free nature of the platform simplifies sample preparation, making it particularly valuable for biomedical diagnostics, environmental monitoring, and pharmaceutical research. Additionally, the work highlights the unique properties of hBN as a versatile and sensitive platform for advanced biomolecular sensing, opening new avenues for its application in cutting-edge research and diagnostics. This combination of innovative methodology and broad applicability positions the work as a transformative step in the field of molecular sensing.
