AFM-IR and s-SNOM-IR measurements of chemically addressable monolayers on Au nanoparticles.
Lihi RikanatiShahar DeryElad GrossPublished in: The Journal of chemical physics (2021)
The performance of catalysts depends on their nanoscale properties, and local variations in structure and composition can have a dramatic impact on the catalytic reactivity. Therefore, probing the localized reactivity of catalytic surfaces using high spatial resolution vibrational spectroscopy, such as infrared (IR) nanospectroscopy and tip-enhanced Raman spectroscopy, is essential for mapping their reactivity pattern. Two fundamentally different scanning probe IR nanospectroscopy techniques, namely, scattering-type scanning near-field optical microscopy (s-SNOM) and atomic force microscopy-infrared spectroscopy (AFM-IR), provide the capabilities for mapping the reactivity pattern of catalytic surfaces with a spatial resolution of ∼20 nm. Herein, we compare these two techniques with regard to their applicability for probing the vibrational signature of reactive molecules on catalytic nanoparticles. For this purpose, we use chemically addressable self-assembled molecules on Au nanoparticles as model systems. We identified significant spectral differences depending on the measurement technique, which originate from the fundamentally different working principles of the applied methods. While AFM-IR spectra provided information from all the molecules that were positioned underneath the tip, the s-SNOM spectra were more orientation-sensitive. Due to its field-enhancement factor, the s-SNOM spectra showed higher vibrational signals for dipoles that were perpendicularly oriented to the surface. The s-SNOM sensitivity to the molecular orientation influenced the amplitude, position, and signal-to-noise ratio of the collected spectra. Ensemble-based IR measurements verified that differences in the localized IR spectra stem from the enhanced sensitivity of s-SNOM measurements to the adsorption geometry of the probed molecules.
Keyphrases
- atomic force microscopy
- single molecule
- high speed
- density functional theory
- high resolution
- raman spectroscopy
- molecular dynamics simulations
- living cells
- molecular dynamics
- optical coherence tomography
- magnetic resonance
- air pollution
- magnetic resonance imaging
- sensitive detection
- energy transfer
- machine learning
- biofilm formation
- crystal structure
- convolutional neural network
- reduced graphene oxide
- solid state
- cystic fibrosis
- mass spectrometry
- walled carbon nanotubes