Abstract
We present a method to characterize not only shape but also depth of defects in line and space mask patterns. Features in a mask are too fine for a conventional imaging system to resolve them and a coherent imaging system providing only the pattern diffracted by the mask is used. Then phase retrieval methods may be applied, but the accuracy is too low to determine the exact shape of the defect. Deterministic methods have been proposed to accurately characterize the defect, but this requires a reference pattern. We propose to use a phase retrieval algorithm to retrieve the general shape of the mask and then apply a deterministic approach to precisely characterize the defects detected.
Highlights
In extreme ultraviolet lithography (EUVL), it is important to detect and characterize mask defects since the presence of defects as small as a few tenths of nanometers is already a critical issue.[1]
It is difficult to quantify the accuracy in depth of the phase retrieval method because the result is strongly linked to the shape of the pupil of the recording system and the illumination beam
The deterministic approach was proposed for accurate characterization, but the theory derived can be applied only in restricted cases
Summary
In extreme ultraviolet lithography (EUVL), it is important to detect and characterize mask defects since the presence of defects as small as a few tenths of nanometers is already a critical issue.[1]. Coherent diffraction imaging methods[1,3] have been proposed for defect inspection. In this case, mask shape is not directly obtained. The hybrid input-output (HIO) algorithm developed by Fienup[4] is the most widely used method for reconstructing phase information from the Fourier transform modulus since it enables to avoid local minima. In the case of mask inspection for EUVL, periodic patterns can be reconstructed and defects’ widths can be estimated.[5] it was reported that conventional phase retrieval methods, such as HIO algorithm, were not robust to noise.[6,7] In practical applications, the noise is, limiting the accuracy
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