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Silver oxide model surface improves computational simulation of surface-enhanced Raman spectroscopy on silver
Scott G Harroun1, Yaoting Zhang2, Tzu-Heng Chen3
1Laboratory of Biosensors & Nanomachines, Département de Chimie, Université de Montréal, Montréal, QC H3C 3J7, Canada. sg.harroun@umontreal.ca a.vallee-belisle@umontreal.ca.
Physical Chemistry Chemical Physics : PCCP
|July 15, 2021
Summary
Density functional theory (DFT) simulations of surface-enhanced Raman spectroscopy (SERS) are more accurate when using silver oxide (Ag2O) as the model surface, rather than simple silver atoms or clusters.
Area of Science:
- Surface Science
- Computational Chemistry
- Spectroscopy
Background:
- Surface-enhanced Raman spectroscopy (SERS) combined with density functional theory (DFT) is a powerful tool for determining molecular adsorption orientation on nanoparticle surfaces.
- Current DFT simulations of SERS on silver typically model the surface using isolated silver atoms (Ag), ions (Ag+), or small clusters (Agx, Agx+).
Purpose of the Study:
- To investigate the impact of different silver surface models on the accuracy of DFT-simulated SERS spectra.
- To determine if alternative silver surface models can quantitatively improve SERS simulation accuracy.
Main Methods:
- Simulated SERS spectra using DFT for the nucleobase 2,6-diaminopurine (2,6-DAP) adsorbed on different silver surface models.
- Compared simulation results using silver atoms, ions, and clusters against simulations using silver oxide (Ag2O).
- Extended the strategy to three additional molecules to generalize the findings.
Main Results:
- Employing silver oxide (Ag2O) as the model surface for DFT simulations significantly improves the quantitative accuracy of simulated SERS spectra.
- This improvement was demonstrated first for 2,6-diaminopurine and subsequently validated for three other molecules.
Conclusions:
- Silver oxide (Ag2O) represents a more accurate and quantitatively reliable model surface for DFT-based SERS simulations compared to traditional silver atom, ion, or cluster models.
- This refined modeling approach enhances the predictive power of SERS-DFT for understanding molecular adsorption on silver surfaces.
