Comparing models for the growth of silicon-rich oxides (SRO)
The relative advantages of several methods for modeling the growth of Silicon-Rich Oxide (SRO) films are compared. The methods are a response surface model, a physical model based on chemical kinetics, and neural network models. The physical model provides more insight and greater predictive ability. Neural network models provide better fits to complex response surfaces with minimal data and can be used successfully in the absence of a theoretical model. The risks of prediction by neural networks outside their training domain are demonstrated.