Multiple Mask Data Preparation for Photolithography
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Solution Overview
Problem
As integrated circuits become smaller, photolithographic printing systems face challenges in accurately reproducing patterns on silicon wafers due to optical and process distortions, leading to mismatches between mask patterns and printed circuit elements, which existing resolution enhancement techniques like OPC and phase shifting masks struggle to address effectively, particularly for tightly packed features.
Innovation Solution
A method is developed to prepare data for photolithographic masks by dividing a desired layout pattern into two or more data layers using a coloring algorithm, where features within a predetermined distance are grouped and potentially broken into smaller features with cutting boxes to ensure proper printing, allowing for improved resolution in multiple mask photolithographic processes like double patterning and double exposure techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If features are tightly packed to increase circuit density, then productivity and circuit integration are improved, but manufacturing precision deteriorates due to optical distortions and printing fidelity loss
Solution Approach 1:
The patent divides the layout pattern into multiple data layers or groups, where each group is printed on a separate mask. This segmentation allows each mask to handle a subset of features with adequate spacing, avoiding the optical distortions that occur when all features are printed together on a single mask. The coloring algorithm assigns features to different groups based on spatial relationships, ensuring that tightly packed features are distributed across multiple masks rather than forced onto one mask where they would print with poor fidelity.
2Manufacturing precision
If resolution enhancement techniques like OPC and phase shifting masks are used to improve printing fidelity, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
Instead of applying complex resolution enhancement techniques to a single dense pattern, the patent segments the pattern into multiple groups that can be printed with simpler processes. Each group contains features spaced far enough apart to be printed with standard photolithography techniques, eliminating the need for OPC or phase shifting masks and thereby reducing process complexity.
Solution Approach 2:
The patent moves the problem from a two-dimensional printing challenge (fitting all features on one mask) to a three-dimensional solution by adding the dimension of multiple masks or data layers. This allows features that would be too close together on a single mask to be distributed across multiple masks, solving the printing fidelity problem without requiring complex enhancement techniques on any single mask.
3Manufacturing precision
If features are divided into smaller features with cutting boxes to maintain spacing, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The coloring algorithm performs preliminary grouping of features into multiple data layers before the actual mask fabrication process. By pre-organizing features into groups based on their spatial relationships and spacing requirements, the system avoids the need for complex real-time adjustments during printing. The cutting boxes are automatically generated as part of this preliminary data preparation, extending polygons to overlap in the cutting box region to ensure proper printing, which simplifies the overall process despite the additional data manipulation steps.
Data Source
AI summary
A method for preparing data to create two or more masks required to print a desired feature pattern with a multiple mask technique. In one embodiment of the invention, a target feature pattern is separated into two or more groups or data layers with a coloring algorithm. Coloring conflicts or adjacent features that are within a predetermined distance of each other and are assigned to the same group or data layer are identified. Cutting boxes are added to a feature to divide a feature into two or more smaller features. A coloring algorithm is re-applied to the layout including the cutting boxes to assign the features into different groups or data layers. Data in each group or data layer is used to define a mask to print the target feature pattern.