(218g) Optimal Portfolio of Products in a Polycrystalline Silicon Refinery
In this work, a silicon based refinery is conceptually designed using surrogate models for the major units to evaluate the portfolio of products. The modelling of the carboreduction reactor was developed by means of a experimental based subrogated model . The second section is the reactor of the hydrogenation of silicon tetrachloride, that is modelled based on Gibbs free energy minimization . The surrogate models for the purification of the chlorosilanes obtained from the previous reactor as well as the TEOS columns are developed from rigorous simulations using a stochastic optimization approach . Finally, the conversion of trichlorosilane into polysilicon in a Siemens deposition reactor is modelled based on the work of Del Coso et al. . The entire process is modeled in GAMS as an NLP model for the optimization of the operating conditions.
The optimal silicon refinery produces tetraethoxysilane and chlorosilanes in addition to the production of polysilicon. The proposed design reduces the cost for polycrystalline silicon to 6.86 $/kg, compared to a cost of 8.93 $/kg of polycrystalline silicon if the plant does not generate high value-added by-products, both below the commercial price, which is estimated at 10 $/kg. Therefore, the refinery is not only capable of meeting the market share requirements, but in a way the generation of different high added value by-products increases the plant profit compared to that of the net income earned by traditional polysilicon single-product plants.
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