Reticle Defect Detection via Virtual Process Window Simulation
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Solution Overview
Problem
Current methods for detecting defects in reticle design data are inadequate as they do not examine the full range of process window conditions, leading to missed potential defects and incomplete optimization of design, particularly in integrated circuit manufacturing where precise pattern formation is critical.
Innovation Solution
The implementation of a virtual process window qualification (vPWQ) method that generates simulated images of how a reticle design will be printed on a wafer at different values of process parameters, allowing for the detection of defects across a range of focus and exposure conditions before actual fabrication, and optimizing the design for the largest possible process window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional defect detection methods are used at nominal process conditions only, then detection simplicity is maintained, but defect detection completeness deteriorates
Solution Approach 1:
The patent applies preliminary action by performing defect detection simulations at multiple process conditions (focus, exposure, and other parameters) before actual reticle fabrication. The method pre-identifies potential defects by comparing simulated images across a matrix of process conditions, allowing designers to correct issues before manufacturing, thus improving detection completeness without requiring complex physical inspection equipment.
Solution Approach 2:
The patent uses copying by creating simulated images that replicate the expected wafer print outcomes under various process conditions. Instead of physically testing at multiple conditions, the method generates virtual copies of the printed pattern through simulation, comparing these copies to identify defects. This approach maintains simplicity while achieving comprehensive defect detection across the process window.
2Measurement precision
If full process window simulation is performed, then defect detection accuracy is improved, but computational time increases
Solution Approach 1:
The patent applies segmentation by dividing the full process window into discrete focus and exposure condition levels, creating a matrix of simulation points. Rather than continuously simulating all possible conditions, the method segments the parameter space into manageable discrete steps (e.g., focus levels from -0.5 to +0.5 micrometers in 0.1 micrometer increments), reducing computational burden while maintaining detection accuracy.
Solution Approach 2:
The patent systematically varies process parameters (focus, exposure, and other lithography conditions) across defined ranges to perform simulations. By changing parameters in controlled discrete steps rather than continuously, the method achieves comprehensive defect detection across the process window while managing computation time through structured parameter exploration.
3Manufacturing precision
If reticle design is optimized for narrow process window, then manufacturing precision at nominal conditions is improved, but process adaptability deteriorates
Solution Approach 1:
The patent applies dynamics by evaluating reticle design performance across dynamic variations in process conditions rather than at a fixed nominal point. The simulation methodology dynamically adjusts focus, exposure, and other parameters to observe how the design responds to process variations, enabling identification of designs that maintain precision across the full process window rather than only at nominal conditions.
Solution Approach 2:
The patent performs preliminary optimization by identifying and correcting design marginalities before fabrication through multi-condition simulation. By pre-testing the design across the process window and identifying patterns that fail under varying conditions, the method enables design modifications to achieve both nominal precision and process adaptability before the reticle is manufactured, avoiding the need to choose between the two objectives.
Data Source
AI summary
Computer-implemented methods for detecting defects in reticle design data are provided. One method includes generating a first simulated image illustrating how the reticle design data will be printed on a reticle using a reticle manufacturing process. The method also includes generating second simulated images using the first simulated image. The second simulated images illustrate how the reticle will be printed on a wafer at different values of one or more parameters of a wafer printing process. The method further includes detecting defects in the reticle design data using the second simulated images. Another method includes the generating steps described above in addition to determining a rate of change in a characteristic of the second simulated images as a function of the different values. This method also includes detecting defects in the reticle design data based on the rate of change.