Mask Pattern Correction via Forced Grid Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Digital pattern transfer apparatuses face challenges in accurately transferring fine features onto semiconductor wafers due to mismatch between pixel sizes in phase masks and desired patterns, leading to inefficiencies in correction times and data storage requirements.
Innovation Solution
A method that evaluates desired workpiece patterns to identify repetitive step cells, adjusts their dimensions to match pixel sizes, and creates a mask stepping array for phase masks, allowing for precise alignment and reduced correction times through a forced grid method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the pixel size in the phase mask is fixed, then the manufacturing and operation of the phase mask is simplified, but the ability to accurately transfer arbitrary fine features is reduced
Solution Approach 1:
The method segments the desired pattern into repetitive step cells that can be systematically evaluated and adjusted. By dividing the pattern into discrete cells and mapping them to pixel grids, the system achieves both manufacturing simplicity and pattern accuracy through structured decomposition of the design space.
Solution Approach 2:
The invention changes the parameters of the step cells (dimensions, positioning) to achieve optimal alignment with the pixel grid. By adjusting step cell parameters rather than pixel parameters, the system maintains fixed pixel sizes while achieving accurate pattern transfer through parameter optimization at the pattern level.
2Adaptability or versatility
If the desired pattern dimensions do not align with pixel sizes, then pattern flexibility is maintained, but correction time and data storage requirements increase
Solution Approach 1:
The method performs preliminary evaluation and adjustment of step cell dimensions before final pattern generation. By pre-processing the pattern data to identify and adjust step cells that align with pixel boundaries, the system reduces correction time during actual pattern transfer while maintaining design flexibility through the evaluation和调整 process.
Solution Approach 2:
The invention creates a simplified copy or representation of the desired pattern in terms of step cells that map to pixel grids. This intermediate representation allows for efficient processing and reduced data storage requirements while preserving the essential features of the original design through systematic approximation.
3Adaptability or versatility
If arbitrary pattern dimensions are used, then design freedom is maximized, but data storage requirements and processing complexity increase
Solution Approach 1:
The pattern is segmented into standardized step cells that can be described by a limited set of parameters (dimensions, positioning, repetition). This segmentation reduces the overall data storage requirements compared to storing arbitrary pattern data, while maintaining design freedom through the ability to define diverse step cell configurations.
Solution Approach 2:
The step cell concept serves multiple functions: it defines pattern geometry, determines pixel mapping, and enables efficient data representation. By making the step cell a universal building block that can represent various pattern features through parameter variation, the system reduces processing complexity while maintaining design versatility.
Data Source
AI summary
A method for transferring an actual workpiece pattern (23) to a workpiece (24) using a pixelated phase mask (14) includes (i) evaluating a desired workpiece pattern (226) to identify a desired repetitive step cell (230) in the desired workpiece pattern (226), the desired repetitive step cell (230) having a desired step cell width (250), and a desired step cell length (252); (ii) evaluating if the desired step cell width (250) is equal to a first integer multiplied by a pixel width (28A) and an optical adjustment factor; and (iii) evaluating if the desired step cell length (252) is equal to a second integer multiplied by a pixel length (28B) and an optical adjustment factor.