Multi-Die Mask Defect Detection Using Hybrid Reference Images
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Solution Overview
Problem
Current mask inspection methods for EUV masks face challenges in reliably detecting defects due to limitations in die-to-database and die-to-die inspection techniques, particularly with complex optical proximity correction designs and focus control issues, which affect sensitivity and accuracy.
Innovation Solution
A system and method combining aspects of die-to-database and die-to-die inspection by generating a design-based reference image and a die-equivalent reference image, using EUV and DUV wavelengths, along with charged particle beams, to accurately detect defects on multi-die masks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If die-to-database inspection is used, then defect detection can be performed using design reference, but rendering errors from complex OPC designs reduce detection sensitivity
Solution Approach 1:
The patent merges die-to-database inspection with die-to-die inspection by generating a composite reference image that combines design-based reference data with actual measured data from multiple dies. This hybrid approach eliminates rendering errors from complex OPC designs while maintaining the ability to detect systematic writer errors, thereby resolving the contradiction between using design reference and avoiding rendering errors.
Solution Approach 2:
The patent introduces an intermediary step of measuring multiple actual dies and generating a composite reference image that serves as a mediator between the design database and defect detection. This intermediary composite reference eliminates the direct rendering error path while preserving the reference function, allowing accurate defect detection without the harmful rendering errors from complex OPC.
2Ease of manufacture
If die-to-die inspection is used, then inspection can be performed without design database, but systematic writer errors cannot be detected and performance is impacted by photomask quality and focus control
Solution Approach 1:
The patent combines the simplicity of die-to-die inspection with the reliability of design-based reference by measuring multiple actual dies and creating a composite reference image. This merged approach maintains ease of manufacture by using only actual measurements while improving reliability by enabling detection of systematic writer errors through the multi-die comparison methodology.
Solution Approach 2:
The patent makes the inspection system multi-functional by enabling it to detect both random defects and systematic writer errors using the same die-to-die measurement approach. The composite reference image generated from multiple dies serves multiple purposes: it provides a reference for defect detection, compensates for focus variations, and enables systematic error detection, thereby improving reliability without sacrificing process simplicity.
3Manufacturing precision
If mask patterns are substantially sensitive to focus, then high precision patterning is achieved, but reliable defect detection becomes significantly challenging
Solution Approach 1:
The patent segments the focus variation problem by measuring multiple dies at potentially different focus conditions and then processing these segmented measurements to create a composite reference image. This segmentation allows the system to handle focus variations in sensitive mask patterns while maintaining defect detection reliability through the multi-die comparison approach.
Solution Approach 2:
The patent implements feedback by using the measured data from multiple dies to refine and update the composite reference image, which is then used for defect detection. This feedback loop compensates for focus variations and aberrations in sensitive mask patterns, maintaining both patterning precision and defect detection reliability by continuously improving the reference based on actual measurements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances defect detection sensitivity and reliability by overcoming focus and aberration errors, enabling the detection of systematic writer errors and improving the accuracy of defect identification on EUV masks.
Implementation Method 1
using EUV and DUV wavelengths
Implementation Method 2
charged particle beams
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
Methods and systems for detecting defects on a mask are provided. One method includes generating a database reference image for a multi-die mask by simulation and detecting first defects on the mask by comparing the database reference image to images of the mask generated by an imaging subsystem for a first of the multiple dies. The method also includes generating a die reference image for the first of the multiple dies by applying one or more parameters of the imaging subsystem learned by generating the database reference image to the images generated by the imaging subsystem of one or more of the multiple dies other than the first multiple die. In addition, the method includes detecting second defects on the mask by comparing the die reference image to the images of the mask generated by the imaging subsystem for the first of the multiple dies.