Abstract
We present an algorithm that simultaneously deduces from real-time
ellipsometric measurements both the growth rate and the composition of
films deposited via chemical vapor deposition. The heart of the algorithm
is a dynamic, first-principles model of the deposition system and the
ellipsometric sensor. The model predicts the ellipsometric parameters Ψ and
Δ during film growth. An extended Kalman filter is developed that utilizes the
sensor model and infers both the growth rate and the Ge composition
of the deposited film in real time. Two simulations demonstrating the effectiveness
of the algorithm are evaluated.
© 2006 Optical Society of America
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