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As a result of demand for ever decreasing of feature sizes in photomasks, inspection has become more
important as a key element of manufacturing 32nm node and beyond. In order to provide a better solution for
it, we have developed a new method to create programmed defects having attributes very similar to those
seen in natural defects. We have named the new method as NLPD (Natural-Like Programmed Defect). One
of the noteworthy features of NLPD is that it is possible to make reticles with different heights which have
never been made by conventional method. Natural like defects are desirable for new inspection modes
including ones using shorter wavelength and aerial plane inspection technology. These new inspection
modes are equipped with recently released inspection tools. They are expected to meet the requirements
which are needed by future advanced masks, and these requirements have been inadequately fulfilled with
inspection tools for current generation masks. Those requirements include responding to currently dominant
reticle types for 32nm node: CoG: 6% EPSM: and OMOG (Opaque MoSi On Glass). Other possible reticle
types for 32nm node contain EUV, Enhancer, complex tri-tone, high transmission, and CPL. In the future,
aggressive model based OPC (Optical Proximity Correction) will be typically used which include jogs, serifs,
and SRAF (Sub-Resolution Assist Features) accompanying extremely small gaps between adjacent structures.
When those advanced technologies are adopted, NLPD definitely contributes to making inspection more
efficient and effective as evaluation method dealing with advanced inspection tools.
This paper provides NLPD results with comparison of newly released inspection tools equipped with new
inspection modes. The new inspection modes include hi-resolution inspection and aerial inspection which are
designed to fulfill the requirements of inspection for advanced masks. These results confirm that hi-resolution
inspection is suited for process development or improvement and aerial inspection is good for the volume
production.
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