Technical Report 67, c4e-Preprint Series, Cambridge

Authors: Markus Sander, Richard H. West, Matthew S. Celnik, and Markus Kraft*

Reference: Technical Report 67, c4e-Preprint Series, Cambridge, 2009

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In this study the coagulation, condensation and sintering of nanoparticles is investigated using a stochastic particle model. Each stochastic particle consists of interacting polydisperse primary particles which are connected to each other. In the model sintering occurs between each individual pair of neighboring primary particles. This is important for particles in which the range of the size of the primary particles varies significantly. The sintering time is obtained form the viscous flow model. The model is solved using a stochastic particle algorithm. The particles are represented in a binary tree which contains the connectivity as well as the degree of sintering information. Particles are formed, coagulate, sinter and experience condensation according to known rate laws. The particle binary tree, along with it the degree of sintering, is updated after each time step according to the rates of the different processes. The stochastic particle method uses the technique of fictitious jumps and linear process deferrment. The theoretical results are validated against experimental values for the formation of SiO2 nanoparticles and computer generated TEM pictures are presented and compared to experiments.

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