19 March 2015 Data refinement for robust solution to the inverse problem in optical scatterometry
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Abstract
Optical scatterometry is widely used in the process control of integrated circuits (IC) manufacturing due to its inherent advantages such as nondestruction, high sampling rate, large aerial coverage and low-cost. However, in the conventional inverse problem solvent of optical scatterometry, the measurement errors are usually excessively simplified as normally distributed errors, which deviate from the actual complex ones. In this work, we will demonstrate that there exist typical outlying measurement errors in the measurement signature, and these outlying measurement errors will notably affect the result of each iteration step in the conventional Gauss-Newton (GN) method. By performing a method based on the principle of least trimmed squared estimator (LTS) regression instead of each GN iteration step, the higher measurement accuracy of a nanostructure can be achieved. The remarkably improved reconstruction of a deep-etched multilayer grating has demonstrated the feasibility of the proposed method.
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Jinlong Zhu, Hao Jiang, Chuanwei Zhang, Xiuguo Chen, Shiyuan Liu, "Data refinement for robust solution to the inverse problem in optical scatterometry", Proc. SPIE 9424, Metrology, Inspection, and Process Control for Microlithography XXIX, 94240Y (19 March 2015); doi: 10.1117/12.2086058; https://doi.org/10.1117/12.2086058
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