Computational Study on Cluster Formation of Colloidal Nanoparticles: A Kinetic Monte Carlo Simulation and Rate Theory Modeling on Scaling Behaviors of Clusters
- Computational Study on Cluster Formation of Colloidal Nanoparticles: A Kinetic Monte Carlo Simulation and Rate Theory Modeling on Scaling Behaviors of Clusters
- 권석준; T. Alan Hatton
- Issue Date
- Materials Research Society
- An understanding of the statistical and time-dependent features of cluster formation is essential for the application and control of the dispersion quality of colloidal nanoparticles (CNPs). We performed computational and theoretical studies on the formation of clusters in CNPs, focusing on the scaling behavior of the growth of the cluster size and size distribution, with analysis of the fractal dimension. For the study, we employed a kinetic Monte Carlo (KMC) algorithm in which NPs are moved by selfavoiding diffusive jumping with a random walk. To describe diffusion of the NPs in a colloidal environment, the diffusivity was modeled as a configuration-dependent function of the interacting potential of the clusters. To verify the computational analysis, a kinetic model based on rate theory (RT) was used to analyze the temporal evolution of the concentrations of the monomer and clusters. The KMC simulations agreed well with the predictions from RT in terms of the description of the scaling behaviors. In particular, we observed that the scaling exponents for the average cluster size and weight are smaller than the conventional predictions, although the fractal dimension of the cluster was comparable to that observed in the typical reaction-limited aggregation of particles. We provided a semi-empirical explanation of how the scaling exponent of the cluster size and weight should be reduced depending on the scaling behavior of the monomer concentration. We also provided a model to explain the dependence of the induction time for cluster formation on the initial monomer concentration; the model is supported by the KMC simulation and RT calculation. The results of this study can be used to design and control the colloidal quality of NP dispersions by understanding the cluster growth behavior and its dynamics.
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