Abstract
Prediction and adjustment of point defect (vacancies and self-interstitials) distribution in silicon crystals is of utmost importance for microelectronic applications. The simulation of growth processes is widely applied for process development and quite a few different sets of point defect parameters have been proposed. In this paper the transient temperature, thermal stress and point defect distributions are simulated for 300 mm Czochralski growth of the whole crystal including cone and cylindrical growth phases. Simulations with 12 different published point defect parameter sets are compared to the experimentally measured interstitial–vacancy boundary. The results are evaluated for standard and adjusted parameter sets and generally the best agreement in the whole crystal is found for models considering the effect of thermal stress on the equilibrium point defect concentration.
Highlights
The Czochralski (Cz) process is the method of choice for the production of silicon (Si) crystals for microelectronics applications
Later simulation of the point defect distribution in the crystal domain was added [2,3,4,9,10]. Transient modeling of both the heat transfer and point defects (PD) distribution is necessary since the Cz process is transient in reality, and the start and end cones are a considerable part of the whole growth process
While the pull rate oscillations are much stronger in the experiment during the cone phase, it practically does not influence the heat transfer, as verified by performing a simulation with non-smoothed experimental data as the pull rate setpoint; this holds for the point defect distribution
Summary
The Czochralski (Cz) process is the method of choice for the production of silicon (Si) crystals for microelectronics applications. Later simulation of the point defect distribution in the crystal domain was added [2,3,4,9,10] Transient modeling of both the heat transfer and PD distribution is necessary since the Cz process is transient in reality, and the start and end cones are a considerable part of the whole growth process. 12 different PD parameter sets using the same thermal conditions; (iii) compare simulation results with the experimental PD distribution in the whole crystal, including start and end cones; (iv) adjust PD parameters for 1 position in the crystal and find the parameter sets with the best agreement to experiment
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
