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Understanding Time-Dependent Surface-Enhanced Raman Scattering from Gold Nanosphere Aggregates Using Collision Theory
Hoa T Phan1, Thomas S Heiderscheit1, Amanda J Haes1
1Department of Chemistry, University of Iowa, Iowa City, Iowa 52242, United States.
The Journal of Physical Chemistry. C, Nanomaterials and Interfaces
|September 18, 2020
Summary
Cluster formation mechanisms significantly impact surface-enhanced Raman scattering (SERS) signals over time. This study reveals SERS signals from gold nanosphere clusters are predictable based on concentration and size, following collision theory.
Area of Science:
- Nanotechnology
- Plasmonics
- Spectroscopy
Background:
- Metal nanoparticle aggregates are crucial for surface-enhanced Raman scattering (SERS) due to localized electric fields.
- Time-dependent variations in SERS signals are observed, but the underlying cluster formation mechanisms are less understood.
Purpose of the Study:
- To investigate the impact of cluster formation mechanisms on time-dependent SERS signals from gold nanosphere aggregates.
- To experimentally and theoretically analyze the kinetics and dynamics of cluster formation.
Main Methods:
- Utilized dynamic light scattering (DLS), localized surface plasmon resonance (LSPR) spectroscopy, and SERS measurements.
- Employed theoretical calculations including interaction pair potential and collision theory.
- Systematically varied gold nanosphere concentration and diameter under diffusion-limited conditions.
Main Results:
- Gold nanosphere aggregates formed reproducibly in a diffusion-limited regime, adhering to a self-limiting cluster size model.
- The rate of cluster formation was explained by collision theory and interaction pair potential calculations.
- Time-dependent SERS signals were found to be predictable based on nanosphere concentration and size.
Conclusions:
- Cluster formation dynamics in the diffusion-limited regime are governed by principles of collision theory.
- Predictable SERS signals can be achieved by controlling gold nanosphere concentration and size.
- Understanding these formation mechanisms is key to optimizing SERS measurements.

