Combining density functional theory and CFD-PBM model to predict TiO2 nanoparticle evolution during chemical vapor deposition

Abstract

Preparation of TiO2 nanoparticles by TiCl4 hydrolysis during chemical vapor deposition (CVD) is one of the effective techniques for producing TiO2 nanoparticles, while the mechanisms of TiO2 nanoparticle evolution are not well understood. This paper uses computational fluid dynamics (CFD) population balance model (PBM) to predict particle size distribution during CVD, and density functional theory (DFT) calculations to explore reaction mechanisms. DFT calculations reveal that the gas phase hydrolysis reaction can be simplified into two processes, the hydrolysis of TiCl4 to form TiO(OH)2 and the decomposition of TiO(OH)2 to TiO2. During the surface reactions, the energy barriers of TiO(OH)2 decomposition reactions on the surfaces of (TiO2)n nanoclusters (n = 1–8) are generally lower than those in the gas phase reactions, and the largest energy barrier of the surface reaction occurs on the surface of (TiO2)6 nanoclusters. Simulations using a perfect stirred reaction model indicate that Ti(OH)4 is the dominant hydrolysis products when the temperature is lower than 548 K, while TiO2 production starts at ∼610 K, indicating reaction temperature is a crucial factor that governs the products of TiCl4 hydrolysis. CFD-PBM model predict the evolution of Particle Size Distribution (PSD) of nanoparticles in a CVD reactor, which is agreed with experimental measurements in the literature. Increasing the reaction temperature results in an increase of the peak of the PSD of nanoparticles in the reactor. This study provides atomic insights into the nanoparticle evolution and a practical model to predict the nanoparticle evolution during the CVD process.