State estimation approach for determining composition and growth rate of Si_{1− x} Ge _x chemical vapor deposition utilizing real-time ellipsometric measurements

Abstract

We present an algorithm that simultaneously deduces from real-time ellipsometric measurements both the growth rate and the composition of ${\mathrm{Si}}_{1-x}{\mathrm{Ge}}_x$ 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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