About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Functional Nanomaterials: Functional Low-Dimensional (0D, 1D, 2D) Materials 2026
|
| Presentation Title |
Ultra-Sensitive SERS Analysis for PFOA Degradation Based on Femtosecond Laser-Processed Probes and Machine Learning |
| Author(s) |
Anming Hu, Unmanaa Dewanjee, David Fieser |
| On-Site Speaker (Planned) |
Anming Hu |
| Abstract Scope |
We present a SERS substrate fabricated using femtosecond (fs) lasers for ultra-sensitive detection and real-time monitoring of perfluorooctanoic acid (PFOA) degradation. A 1 mm groove was accurately ablated on a microscope glass slide with fs laser pulses, followed by drop-casting of silver nanoparticles synthesized via fs laser ablation in liquid. The groove was filled, and a confined, highly SERS-active area was generated. The substrate showed stable detection of methylene blue at concentrations as low as 10⁻¹3 M with an estimated enhancement factor of ~108. Post-fabrication temperature treatment at 140 °C yielded the greatest SERS activity, while higher temperatures (e.g., 160 °C) caused lower hotspot density due to nanoparticle coalescence, which was confirmed by nanoscopic analysis and hotspot mapping. The enhanced substrate was further used to trace the photocatalytic degradation of PFOA of varying concentrations. Machine learning data analysis combined with density functional theory (DFT) calculations enabled the identification of several intermediate species. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Nanotechnology, Environmental Effects, Machine Learning |