We develop a kinetic Monte Carlo algorithm to describe the growth of nanoparticles by particle–particle collision and subsequent coalescence. The unique feature of the model is its ability to account for the exothermic nature of particle coalescence events and to show how the resulting nonisothermal behavior can be used to change the primary particle size and the onset of aggregation in a growing nanoaerosol. The model shows that under certain conditions of gas pressure, temperature, and particle volume loadings, the energy release from two coalescing nanoparticles is sufficient to cause the particle to exceed the background gas temperature by many hundreds of degrees. This in turn results in an increase in the microscopic transport properties (e.g., atomic diffusivity) and drive the coalescence process even faster. The model compares the characteristic times for coalescence and collision to determine what conditions will lead to enhanced growth rates. The results, which are presented for silicon and titania as representative nanoparticle systems, show that increasing volume loading and decreasing pressure result in higher particle temperatures and enhanced sintering rates. In turn, this results in a delay for the onset of aggregate formation and larger primary particles. These results suggest new strategies for tailoring the microstructure of nanoparticles, through the use of process parameters heretofore not considered as important in determining primary particle size.
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Mukherjee et al. (2003) studied this question.
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