Population Balance-Monte Carlo Simulation for Gas-to-Particle Synthesis of Nanoparticles

Abstract

The process simulation of nanoparticle synthesis via the gas-phase method is essential to understanding the detailed dynamic evolution of nanoparticles within a very short time period under high temperature. The task is, however, very challengeable up to now as the conversion of the gaseous precursor to the end-use nanoparticle is a complex physicochemical process involving nucleation of the particulate phase, agglomeration between particles and sintering under industrial production conditions. In this article, we extended the differentially weighted Monte Carlo method for population balance to simulate the dynamic evolution of titania (TiO2) nanoparticles synthesized by gas-to-particle conversion in a single aerosol reactor, considering simultaneous nucleation, agglomeration, and sintering. The simulated size distribution of TiO2 agglomerate and primary particles produced by the thermal decomposition of titanium tetraisoproxide agreed well with the experimental data. In the simulation, the fast population balance-Monte Carlo method was utilized to accelerate the process simulation on a desktop PC. Results were obtained up to 178 times faster than that of a normal Monte Carlo method. The inhomogeneous internal structure of primary particles was considered through solving population balance of polydisperse primary particles within agglomerate. It was found the polydisperse model could predict the primary particle size distribution better. Simulation results revealed a complex competition relation among nucleation, agglomeration and sintering. Copyright 2013 American Association for Aerosol Research