Collaborative Research: 2D Chiral Fingerprint Metasensor Empowered by Machine Learning for — NSF Award to SUNY at Stony Brook (NY,
Nontechnical description: Chiral molecule sensing plays an important role in many areas such as pharmaceutical industry, biomedical diagnostics, and food analysis. It is challenging to accurately quantify the chirality of chiral medium due to the weak intrinsic circular dichroism signal of chiral molecules. Recently, c
| Award title | Collaborative Research: 2D Chiral Fingerprint Metasensor Empowered by Machine Learning for |
|---|---|
| Award ID | 2529077 |
| Awardee | SUNY at Stony Brook |
| City | STONY BROOK |
| State | NY |
| Amount obligated | $267,520 |
| Principal investigator | Jie Gao |
| Program | EPMD-ElectrnPhoton&MagnDevices |
| Start date | 10/15/2025 |
| Abstract | Nontechnical description: Chiral molecule sensing plays an important role in many areas such as pharmaceutical industry, biomedical diagnostics, and food analysis. It is challenging to accurately quantify the chirality of chiral medium due to the weak intrinsic circular dichroism signal of chiral molecules. Recently, chiral metasurfaces have been used to amplify the circular dichroism signal and improve the sensitivity in circular dichroism spectroscopy for the vibrational transitions of chiral |
| Source | NSF Awards |
$799/mo
Try NSFGrants →