Hierarchical Geometric Partitioning for Multiple Patterning
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Solution Overview
Problem
Current microdevice designs face challenges in manufacturing closely packed structures due to limitations in conventional mask writing tools, which can only write basic polygons, leading to difficulties in properly forming adjacent structures in a single lithographic process, and multiple patterning techniques struggle with correctly partitioning geometric elements without conflicts.
Innovation Solution
The implementation of a computer system using constraint generation tools to determine the placement of geometric elements for complementary lithographic masks, employing advanced constraint rules and hierarchical cell analysis to effectively partition and color geometric elements, allowing for accurate assignment to different masks in multiple patterning schemes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional mask writing tools are used to write basic polygons, then the manufacturing process is simple, but the ability to form closely packed adjacent structures is limited
Solution Approach 1:
The layout design data is decomposed into multiple decomposition sets, where each set contains a portion of the geometric elements to be formed. This segmentation allows closely packed structures to be distributed across multiple masks, enabling formation of dense patterns that would be impossible with a single conventional mask writer.
Solution Approach 2:
The system performs preliminary decomposition and assignment of geometric elements to different masks before the actual lithographic process. By pre-processing the layout data and determining the optimal distribution of elements across multiple masks, the system prepares the necessary information in advance to guide the formation of closely packed structures.
2Manufacturing precision
If multiple patterning techniques are used to form closely packed structures, then manufacturing precision improves, but processing time increases from minutes to days
Solution Approach 1:
The system performs preliminary decomposition and constraint analysis on the layout design data before manufacturing. By pre-processing the geometric elements, generating decomposition sets, and assigning elements to masks in advance, the system eliminates time-consuming iterative adjustments during production, reducing processing time from days to minutes while maintaining high precision.
Solution Approach 2:
The system creates multiple decomposition sets that are copies or variations of the original layout, each optimized for specific manufacturing constraints. These decomposition sets serve as pre-prepared templates that can be quickly applied during manufacturing without requiring real-time computation, thus accelerating the process.
3Productivity
If geometric elements are densely packed to increase device density, then productivity improves, but manufacturing precision deteriorates due to conflicts in partitioning
Solution Approach 1:
The system applies different decomposition strategies and constraints to different regions of the layout based on local characteristics. By analyzing the specific spatial relationships and density requirements of each region, the system optimizes the decomposition locally, ensuring that densely packed areas receive specialized handling that maintains manufacturing precision while achieving high device density.
Solution Approach 2:
The decomposition and assignment process is made dynamic and adaptive, allowing the system to adjust the distribution of geometric elements across masks based on real-time analysis of spatial relationships and manufacturing constraints. This dynamic optimization ensures that densely packed structures are correctly partitioned without conflicts, maintaining precision even at high device densities.
Data Source
AI summary
A method of identifying elements in a design layout having multiple levels of hierarchical cells, each cell having one or more geometric elements, may include selecting a cell from a list of candidate cells for a level of a hierarchy; applying a local rule to the selected cell; identifying each selected cell that includes a geometric element that passes the local rule; building a list of candidate cells for a next-higher level of the hierarchy according to the identified cells; repeating the selecting, identifying, and building operations for each higher level of the hierarchy; and when a highest level of the hierarchy has been processed, returning and storing the list of candidate cells as the global solution for the applied local rule.