Reactor Models for Silane Pyrolysis in Fluid Bed Reactors: A Brief Review of Past Work

1. Reactor Models for Silane Pyrolysis in Fluid Bed Reactors: A Brief Review of Past Work P.A.Ramachandran M.P.Dudukovic Chemical Reaction Engineering Laboratory Chemical Engineering Department Washington University in St Louis MO 63130. Email: rama@wuche.wustl.edu

2. Outline • Review progress in the phenomenological models for Silane pyrolysis • Backmixed Reactor Model • Two phase fluid bed model • Two phase with grid zone • Effect of operating and design parameters

3. Advantages of Fluid Bed reactors • Traditionally Siemens reactor is used where deposition occurs over hot rods. This is both capital and operating cost intensive. • Fluid beds have a number of advantages. • Continuous operation • Higher production rates • Lower energy consumption. • More Uniformity in Product However, Design of FBR is complex (Role of CREL).

4. Reaction Chemistry • Overall Reaction: SiH4Si + 2H2 • Homogeneous Decomposition RHD=2x 1013 * exp(-26000/T) CVD growth (Heterogenoues reaction) RHT=2.79 x108 e(-19530/T) • More complex Langmuir type of models have also been proposed*. SiH4(g)Si(s) + 2H2(s)

5. Two Step Kinetics • SiH2 is postulated as an intermediate. • Formed SiH2 then adosrbs on the Surface. • SiH2 is postulated as an intermediate.

6. Si Vap SiH4 Si Clusturs Growing Seed Si Particles Si nuclei dPL>100mm dPF<2mm Reaction Pathways of Silane Pyrolysis in Fluid Bed Reactor • Homogeneous nucleation • Growth of nuclei to produce fines • Capture of fines by seeds • Heterogenous nucleation on existing particles.

7. Gas Adsorption of gas Nucleation Agglomeration Molecular Modeling and Plausible Chemical Reaction Mechanisms Coagulation Aerosol Dynamic Modeling, Method of Moments, Particle Distribution Surface Reaction Coalescence and Breakup Particle Size Distribution Individual Particle Growth Rate Diffusion Schematic of pathways and Modeling Approaches • Reactor Scale Modeling • Grid Region • Bubble Phase • Emulsion Phase • CFD Modeling Reactor Hydrodynamics

8. Backmixed Reactor Model • Reactor models as a backmixed reactor. • Provides a simple framework to identify the effect of various pathways. • Lower bound on the fines formed since the whole reactor is full of seeds which capture the fines. • Upper bound for silane conversion. (production rate) since there is no by-passing of the gas phase

9. Backmixed Reactor: Model Equations • Mass Balance on Silane: • Mass Balance on Silicon Vapor • Energy Balance • Growth Rate of Large Seed Particles Lai S., M. P. Dudukovic and P. A. Ramachandran, Chemical Vapor deposition and Homogeneous Nucleation in Fluidized Bed Reactor, Chem. Eng. Sci. 41(4), 633, (1986).

10. Backmixed Reactor: Particle size distribution model • Population Balance For Fines • Mass Balance Over Fines

11. Elutriation VIrHD 0.488(kg/h) SiH4 Si Vap ATFrDF= 0.124kg/sec) ATFrDL 0.035(kg/h) vIrHN=3.97x10-5 kg/sec ATLrHT=2.824 kg/h ATLrDL 0.364(kg/h) Si Clusturs Growing Seed Si Particles Melu=0.0477 kg/h msca 0.111(kg/h) Ff=1.4% Si nuclei Sample Results for Backmixed Reactor Model

12. Two phase model • Reactor is assumed to consist of an emulsion and a bubble (slug) phase. • Heterogeneous reaction occurs in the emulsion phase. • Fine formation occurs in both phases but to a large extent in the slug phase. • Upper bound on the fines formation. • Lower bound on reactor productivity.

13. Modeling Approach Main features in Fluidized Bed Reactors Two Phase Model

14. Importance of Grid Zone • In beds of large particles, jets are observed near the distributor (the grid zone) • Gas phase flows in plug flow here • The grid zone exists up to a ‘’jet penetration height” which is calculated from empirical correlations

15. Grid Region Effects: Equations • Spout • Bubble Phase • Emulsion Phase

16. Results for Fluid bed reactor model with Grid zone Effect of enhanced contacting Efficiency Near Distributor for Slow and Fast Reactions Comparison of Two Phase Model Results with Experimental Data

17. Results for Fluid bed reactor model with Grid zone Effect of Silane Inlet Concentration on Performance of Reactor (Operating Conditions)

18. Reduction of fines: current model predictions • Exchange coefficient plays a significant role. Larger the exchange coefficients lower the fines. • Improve grid to emulsion mass transfer • Reduce holdup of the bubble phase • Particle temperature should be larger than the bubble phase temperature.

19. Summary • Previous Work of CREL on Silane Pyrolysis is Reviewed • Literature over last 20 years identified • Needs to be reviewed carefully

20. Some Recent Studies • Mechanism Nucleation Growth • Girshick S. L., M. T. Swihart, S.-M. Suh, M. R. Mahajan, and S. Nijhawan, Numerical Modeling of Gas-Phase Nucleation and Particle Growth during Chemical Vapor Deposition of Silicon, Journal of The Electrochemical Society, 147 (6) 2303-2311 (2000). • Mirko Peglowa, Jitendra Kumar, Gerald Warnecke, Stefan Heinrich, Lothar Mörl, A new technique to determine rate constants for growth and agglomeration with size- and time-dependent nuclei formation, Chem. Engg. Sci. 61, 282 – 292 (2006). • Silicon Deposition From Silane or Disilane in a Fluidized Bed-Part-I : Experimental Study, Caussat B., Hemati M. and J. P. Couderc, Chem. Eng. Sci. 50(22), 3615 (1995). • Silicon Deposition From Silane or Disilane in a Fluidized Bed-Part-II : Theoriticle Analysis and Modeling, Caussat B., Hemati M. and J. P. Couderc, Chem. Eng. Sci.50(22), 3622 (1995). • Tajero-Ezpeleta MP, Buchholz S and Mleczko L, Optimization of Reaction Conditions in a Fluidized Bed for Silane Pyrolysis, Can. Jou. of Chem. Engg., 82(3), 520, 2004. • Ruvalcaba JRR, Caussat B, Hemati, M, Influence of Principle Operating Parameters on Chemical Vapor Deposition of Silicon from Silane in a Fluidized bed to Limit Agglomeration Problems, Can. Jou. of Chem. Engg., 87(5), 955-963 (2000). • Nan Xie1, Francine Battaglia and Rodney O Fox Combust. Simulations of multiphase reactive flows in fluidized beds using in situ adaptive tabulation, Combustion Theory Modelling, 8 195–209 (2004). • O’Brien T. J., Madhava Syamlal, Chris Guenther, Computational Fluid dynamic Simulation of Chemically Reactive Fluidized Bed Processes, 3rd International Conference on CFD in the Minerals and Process Industries, CSIRO, Melbourne, Australia, 10-12 December 2003. • Experiments and Modeling • Process Design • CFD Modeling Issues