Back to results
US 12,669,446 B2Granted
System and method for inspecting a mask for EUV lithography
AssigneeCarl Zeiss SMT GmbH
InventorRenzo Capelli
Life of this patent
Estimating the term…
Abstract
A pre-classification of potential mask defects on the basis of machine learning is provided during the inspection of a mask for EUV lithography.
Claims23
A system for inspecting a mask for EUV lithography, comprising
- 1.1. a first partial system for optical inspection of a mask for identifying and/or localizing potential mask defects, wherein the first partial system comprises a first optical system for generating at least one first image of at least a portion of the mask, wherein the first optical system comprises an illumination device for generating radiation for illuminating the at least a portion of the mask, a projection device for projecting radiation from the at least a portion of the mask, and an imaging device for capturing the at least one first image of the at least a portion of the mask, wherein the first partial system is configured to identify and/or localize the potential mask defects based on the at least one first image of the mask generated by the first optical system,
- 1.2. a second partial system for pre-classification of the potential mask defects, wherein the second partial system comprises a second optical system for generating at least one second image of at least a portion of the mask, wherein the second optical system comprises an illumination device for generating radiation for illuminating the at least a portion of the mask, a projection device for projecting radiation from the at least a portion of the mask, and an imaging device for capturing the at least one second image of the at least a portion of the mask, wherein the second partial system is configured to pre-classify the potential mask defects based at least in part on the at least one second image of the mask generated by the second optical system, and
- 1.3. a third partial system for checking the potential mask defects,
- 1.4. wherein the second partial system is embodied in such a way that it assigns to the potential mask defects identified and/or localized by the first partial system a confidence parameter for characterizing the reliability of the identification and/or for characterizing the relevance of the defect to subsequent applications, and
- 1.5. wherein the third partial system is controllable in such a way that a subset of the mask defects identified and/or localized by the first partial system is checked on the basis of the confidence parameter assigned to the potential mask defects by the second partial system;
- wherein the second partial system has a classification speed v2 and the third partial system has a checking speed v3, wherein the following applies:
- v2>v3.
4 more elements
A method for inspecting a mask for EUV lithography, comprising the following steps:
- 8.1. providing a mask for EUV lithography,
- 8.2. a first inspection step for recording a first image of the provided mask and for identifying and/or localizing potential mask defects in the provided mask, including using a first optical system to generate the first image, wherein the first optical system comprises an illumination device for generating radiation for illuminating the provided mask, a projection device for projecting radiation from the provided mask, and an imaging device for recording the first image of the provided mask, wherein the identifying and/or localizing potential mask defects comprises identifying and/or localizing potential mask defects based on the first image,
- 8.3. a second inspection step for pre-classifying the potential mask defects into at least two nonempty subsets, including using a second optical system to generate a second image of the provided mask, wherein the second optical system comprises an illumination device for generating radiation for illuminating the provided mask, a projection device for projecting radiation from the provided mask, and an imaging device for recording the second image of the provided mask, wherein the pre-classifying the potential mask defects comprises pre-classifying the potential mask defects based on the second image, and
- 8.4. a third inspection step for checking the potential mask defects in one of the subsets ascertained in the second inspection step,
- 8.5. wherein the second inspection step for pre-classifying the potential mask defects comprises a method based on machine learning,
- wherein the second inspection step has a classification speed v2 and the third inspection step has a checking speed v3, wherein the following applies:
- v2>v3.
4 more elements
Dependencies are inferred from the claim text.