Abstract
The properties of gold nanoparticles strongly depend on their three-dimensional atomic structure, leading to an increased emphasis on controlling and predicting nanoparticle structural evolution during the synthesis process. In order to provide this atomistic-level insight and establish a link to the experimentally-observed growth behavior, a kinetic Monte Carlo simulation (KMC) approach is developed for capturing Au nanoparticle growth characteristics. The advantage of this approach is that, compared to traditional molecular dynamics simulations, the atomistic nanoparticle structural evolution can be tracked on time scales that approach the actual experiments. This has enabled several different comparisons against experimental benchmarks, and it has helped transition the KMC simulations from a hypothetical toy model into a more experimentally-relevant test-bed. The model is initially parameterized by performing a series of automated comparisons of Au nanoparticle growth curves versus the experimental observations, and then the refined model allows for detailed structural analysis of the nanoparticle growth behavior. Although the Au nanoparticles are roughly spherical, the maximum/minimum dimensions deviate from the average by approximately 12.5%, which is consistent with the corresponding experiments. Also, a surface texture analysis highlights the changes in the surface structure as a function of time. While the nanoparticles show similar surface structures throughout the growth process, there can be some significant differences during the initial growth at different synthesis conditions.
Highlights
The current applications of gold nanoparticles span a broad variety of technical platforms, ranging from optical and catalytic systems[1,2,3,4,5,6] to data storage and biomedical applications.[7,8,9,10,11] As the applications for nanomaterials continue to steadily expand, there has been an increased emphasis on controlling and predicting nanoparticle formation
While quantitative predictability is not expected at this stage, we provide the first example of applying atomistic kinetic Monte Carlo simulation (KMC) to mimic the experimental behavior of Au nanoparticle growth from solution
We report the effects of synthesis temperature and precursor concentration on the Au nanoparticle growth behavior, and we find that our model can be trained to adequately reproduce the experimental growth curves at the same conditions
Summary
The current applications of gold nanoparticles span a broad variety of technical platforms, ranging from optical and catalytic systems[1,2,3,4,5,6] to data storage and biomedical applications.[7,8,9,10,11] As the applications for nanomaterials continue to steadily expand, there has been an increased emphasis on controlling and predicting nanoparticle formation (size, morphology, and composition) This fundamental interest is motivated by the fact that many of the unique nanomaterial properties are strongly correlated to subtle changes in the nanoparticle structure and surface termination.[12] there is much to be gained by developing experimental protocols for reliably producing specific nanoparticle morphologies. We focus on modeling the solution-phase growth of Au nanoparticles, due to their diverse applications and the availability of relevant experimental synthesis details
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