(690e) Model-Based Design and Optimisation of Trichlorosilane (TCS) Reactors for Polysilicon Production

The trichlorosilane (TCS) process is a key step in the production of polycrystalline silicon, the main raw material for the manufacture of solar panels. The current process has been established for many years but there is large scope for optimisation and scale up, particularly in light of the significant current increase in polysilicon demand.

At the heart of the TCS process is a fluidised bed reactor where silicon (usually of metallurgical grade) is reacted with chlorine to produce TCS. Silicon particles are fed to the bed in an intermittent fashion and are consumed during reaction. This establishes a distribution of particle sizes inside the unit at semi-steady state operation.

We present a comprehensive model which couples a complete description of the fluidisation phenomena with the solid particles being dissolved in the surrounding gas. The model combines a population-balance approach for reacting particles of silicon with distributed models of hydrodynamics of the dense and bubble phases co-existing in the fluidised bed. The reactions taking place both on the surface of each particle and in the gas phase, and the multicomponent heat and mass transfer between the gas phase and the particle surface are modelled in detail. Mass, energy and population balances of the reacting system are rigorously implemented in the model.

The model is of sufficient fidelity to predict key information for process and detailed engineering design, such as the effect of feed particle size on selectivity, optimal bed operating temperatures and pressures, tube bundle heat transfer area, inventory, reactor weight for different particle size, bed height and void fraction for different operations, and so on. The dynamic capability of the model allows simulation of start-up operation and emergency events.

It is demonstrated that a model-based optimisation approach can lead to significant benefits, including a substantial increase in selectivity to TCS as well as much better control of the temperature over the bed height.