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Empirical analysis of metrological data fusion for dose control on nano scale lithography

M.M. Chu and J.H. Chou
National Cheng Kung University, TW

Keywords:
immersion lithography, dose control, metrology, data fusion, extended Kalman filter

Abstract:
Recently, the immersion lithography has added extra disturbing factor, such as bubbles, particles which directly impact on current in-line metrology and dose control performance. Several works has reported the potential bubble effect.This study concentrates the effort on metrological fidelity for accurate and stable dose control. We present a methodology and characterize the dose metrological data which are collected under immersion condition. The tendency shows the confidence area of metrological feedbacks. Then, the 2nd order data fusion from both in-situ and in line metrological channels is employed to generate a statistical significance of critical external perturbation. This external perturbation is most likely due to random bubble effect in measurement and has to be removed. To improve the dose control reliability, a Extended Kalman Filter (EKM) is implemented to integrate the knowledge based autonomous calibration controller. This controller is aim to optimize tool metrological calibration cycle and retains the metrological fidelity and will be discussed in the final paper.

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