Some mechanistic problems in the kinetic modeling of monosilane pyrolysis

Becerra, Rosa; Walsh, Robin

doi:10.1021/j100205a047

Cited by 64 publications

(71 citation statements)

References 19 publications

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“…The only molecule with double functionality that was allowed to form in the system was Si 2 H 2 , which was suggested to be the key component in the formation of silicon nanoparticles in the thermal CVD of silicon via silane. 29,30 It has been reported that Si 2 H 2 forms through the elimination of molecular hydrogen from disilene, H 2 SidSiH 2 , and it can insert into Si-H or H-H bonds in the same manner as silylenes. 31,32 Three isomers of Si 2 H 2 were found, and the most stable structure of Si 2 H 2 is reported to be Si(H 2 )Si.…”

Section: Model Developmentmentioning

confidence: 99%

“…31,32 Three isomers of Si 2 H 2 were found, and the most stable structure of Si 2 H 2 is reported to be Si(H 2 )Si. 30 Because this postulated structure does not conform to traditional valence rules for silicon, we implemented Si 2 H 2 as H 2 SidSi: in the automated mechanism generation software for convenience. However, the thermochemical properties of Si(H 2 )Si obtained from G3//B3LYP calculations were ascribed to it.…”

Section: Model Developmentmentioning

confidence: 99%

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Detailed Kinetic Modeling of Silicon Nanoparticle Formation Chemistry via Automated Mechanism Generation

Wong

Swihart

et al. 2004

J. Phys. Chem. A

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Thermal decomposition of silane can be used to produce silicon nanoparticles, which have attracted great interest in recent years because of their novel optical and electronic properties. However, these silicon nanoparticles are also an important source of particulate contamination leading to yield loss in conventional semiconductor processing. In both cases, a fundamental knowledge of the reaction kinetics of particle formation is needed to understand and control the nucleation of silicon particles. In this work, detailed kinetic modeling of silicon nanoparticle formation chemistry was carried out using automated reaction mechanism generation. Literature values, linear free-energy relationships (LFERs), and a group additivity approach were incorporated to specify the rate parameters and thermochemical properties of the species in the system. New criteria for terminating the mechanisms generated were also developed and compared, and their suitability for handling an unbounded system was evaluated. Four different reaction conditions were analyzed, and the models predicted that the critical particle sizes were Si 5 for an initial H 2 /SiH 4 molar ratio of 90:10 at 1023 K and Si 4 for the same initial composition at 1200 K. For an initial H 2 /SiH 4 molar ratio of 99:1, the critical particle size was larger than or equal to Si 7 for both temperatures, but it was not possible to determine the exact critical particle size because of limitations in computational resources. Finally, the reaction pathways leading to the formation of nanoparticles up to the critical size were analyzed, and the important species in the pathways were elucidated.

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Section: Model Developmentmentioning

confidence: 99%

Section: Model Developmentmentioning

confidence: 99%

Detailed Kinetic Modeling of Silicon Nanoparticle Formation Chemistry via Automated Mechanism Generation

Wong

Swihart

et al. 2004

J. Phys. Chem. A

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“…[1][2][3][4][5][6][7] There is also a substantial body of work on the kinetics of gas-phase reactions of small silicon hydrides. [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] On the basis of this body of research, models of thermal CVD of silicon from silane can now predict film growth rates and precursor utilization with reasonable accuracy and reliability, at least under conditions where particle formation is negligible. However, understanding of the processes that lead to gas-phase particle nucleation is still quite limited, and models for nucleation and growth of particles in this system do not have the level of predictive capability that has been achieved in modeling film growth rates and gas-phase chemical composition.…”

Section: Introductionmentioning

confidence: 99%

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

1998

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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.

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“…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).…”

Section: Cfd Simulationmentioning

confidence: 99%

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

Dang

Swihart

2009

Aerosol Science and Technology

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In this work, a two-dimensional model was developed for silicon nanoparticle synthesis by silane thermal decomposition in a sixway cross laser-driven aerosol reactor. This two-dimensional model incorporates fluid dynamics, laser heating, gas phase and surface phase chemical reactions, and aerosol dynamics, with particle transport and evolution by convection, diffusion, thermophoresis, nucleation, surface growth, coagulation, and coalescence processes. Because of the complexity of the problem at hand, the simulation was carried out via several sub-models. First, the chemically reacting flow inside the reactor was simulated in three dimensions in full geometric detail, but with no aerosol dynamics and with highly simplified chemistry. Second, the reaction zone was simulated using an axisymmetric two-dimensional CFD model, whose boundary conditions were obtained from the first step. Last, a twodimensional aerosol dynamics model was used to study the silicon nanoparticle formation using more complete silane decomposition chemistry, together with the temperature and velocities extracted from the reaction zone CFD simulation. A bivariate model was used to describe the evolution of particle size and morphology. The aggregates were modeled by a moment method, assuming a lognormal distribution in particle volume. This was augmented by a single balance equation for primary particles that assumed locally equal number of primary particles per aggregate and fractal dimension. The model predicted the position and size at which the primary particle size is frozen in, and showed that increasing the peak temperature was a more effective means of improving particle yield than increasing silane concentration or flowrate.

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Some mechanistic problems in the kinetic modeling of monosilane pyrolysis

Cited by 64 publications

References 19 publications

Detailed Kinetic Modeling of Silicon Nanoparticle Formation Chemistry via Automated Mechanism Generation

Detailed Kinetic Modeling of Silicon Nanoparticle Formation Chemistry via Automated Mechanism Generation

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

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

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