Thermochemistry and Kinetics of Silicon Hydride Cluster Formation during Thermal Decomposition of Silane

Abstract

Product contamination by particles nucleated within the processing environment often limits the deposition rate during chemical vapor deposition processes. A fundamental understanding of how these particles nucleate could allow higher growth rates while minimizing particle contamination. Here we present an extensive chemical kinetic mechanism for silicon hydride cluster formation during silane pyrolysis. This mechanism includes detailed chemical information about the relative stability and reactivity of different possible silicon hydride clusters. It provides a means of calculating a particle nucleation rate that can be used as the nucleation source term in aerosol dynamics models that predict particle formation, growth, and transport. A group additivity method was developed to estimate thermochemical properties of the silicon hydride clusters. Reactivity rules for the silicon hydride clusters were proposed based on the group additivity estimates for the reaction thermochemistry and the analogous reactions of smaller silicon hydrides. These rules were used to generate a reaction mechanism consisting of reversible reactions among silicon hydrides containing up to 10 silicon atoms and irreversible formation of silicon hydrides containing 11-20 silicon atoms. The resulting mechanism was used in kinetic simulations of clustering during silane pyrolysis in the absence of any surface reactions. Results of those simulations are presented, along with reaction path analyses in which key reaction paths and rate-limiting steps are identified and discussed.

Aerosol dynamics modeling of silicon nanoparticle formation during silane pyrolysis: a comparison of three solution methods

“…The gas-phase species equations were also fully coupled to the particle growth by properly accounting for species depletion as a result of surface reactions (Girshick et al, 2000). Chemical nucleation of particles is based on a chemical clustering model (Swihart & Girshick, 1999), in which the basic mechanism includes reversible chemical reactions between silicon/hydrogen molecules containing up to ten silicon atoms. The nucleation rate is taken to be the rate at which these chemical reactions irreversibly produce molecules containing more than ten silicon atoms.…”

“…A detailed chemical clustering model was previously developed for chemical nucleation of silicon hydrides containing up to ten silicon atoms (Swihart & Girshick, 1999), and that model was used here. The clustering model includes detailed information regarding the thermodynamic properties and reactivities of silicon hydride clusters.…”

Computational Modeling of Silicon Nanoparticle Synthesis: II. A Two-Dimensional Bivariate Model for Silicon Nanoparticle Synthesis in a Laser-Driven Reactor Including Finite-Rate Coalescence

“…Numerous studies of silane decomposition kinetics have been reported (Becerra and Walsh 1992;Ho et al 1994;Moffat et al 1992a, b;Purnell and Walsh 1984;Wong et al 2004). As in Dang and Swihart (2008), this work used an extensive chemical kinetic mechanism for silicon hydride cluster formation during silane pyrolysis (Swihart and Girshick 1999). This reaction mechanism includes 133 gas phase species with a critical size of 10 silicon atoms.…”

“…Second, the reaction zone was simulated using an axisymmetric two-dimensional MPSalsa model, whose boundary conditions were obtained from the first step. Last, a two-dimensional aerosol dynamics model, with boundary layer approximations, was used to study the silicon nanoparticle formation using more complete silane decomposition chemistry (Swihart and Girshick 1999), together with the temperature and velocities extracted from the 2D reaction zone CFD simulation. A bivariate moment model with finite coalescence rate was applied, allowing realistic predictions of particle morphology.…”

“…Simulations of the tubular aerosol reactor have been done to check the effect of chemistry and aerosol dynamics on the temperature and velocity. It was found that the maximum differences in temperature and velocity between a simulation with reaction (3) only and a simulation with more complex chemistry (Swihart and Girshick 1999) and aerosol dynamics were less than 1.5%. That validates the one-way coupling of the temperature and velocity data from the CFD model to the aerosol simulation of the reaction zone for the silane concentrations and other conditions considered in this work.…”