Exposure Condition Calculation via Singular Value Decomposition
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Solution Overview
Problem
Current methods for optimizing exposure conditions in projection exposure apparatuses for semiconductor fabrication are time-consuming and costly, particularly in improving the resolution of projection exposure systems, as they require repeated experiments and complex calculations for determining exposure conditions.
Innovation Solution
A calculation method that divides the effective light source into point sources, shifts pupil functions, and performs singular value decomposition to quickly calculate light intensity distributions and transmission cross coefficients, enabling faster optimization of exposure conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If repeated experiments are conducted to optimize exposure conditions, then exposure optimization accuracy is improved, but time consumption and cost increase
Solution Approach 1:
The patent creates a virtual copy of the exposure process through computer simulation. Instead of physically repeating experiments on actual semiconductor wafers, the system simulates exposure conditions, light intensity distributions, and pattern formation on a computer. This virtual copying allows multiple optimization iterations without consuming physical materials or significant time, while still achieving accurate exposure condition optimization.
Solution Approach 2:
The patent replaces the mechanical/experimental exposure optimization system with a computational system. Rather than physically adjusting exposure parameters and measuring results through repeated experiments, the system uses computer algorithms to calculate light intensity distributions, simulate pattern formation, and determine optimal exposure conditions. This substitution eliminates the time-consuming iterative experimental process while maintaining optimization accuracy.
2Measurement precision
If complex calculations are performed to determine exposure conditions, then exposure optimization accuracy is improved, but calculation time increases
Solution Approach 1:
The patent segments the complex exposure calculation process into distinct computational steps: dividing the illumination aperture into multiple zones, calculating diffraction patterns for each zone separately, and combining results through superposition. This segmentation allows the use of efficient algorithms for each sub-problem rather than attempting a single complex calculation, significantly reducing total computation time while maintaining accuracy.
Solution Approach 2:
The patent changes the computational parameters and approach by using analytical solutions for diffraction patterns rather than numerical methods. By transforming the calculation into the frequency domain and using Fourier transform techniques, the system achieves faster computation. The patent also introduces approximation parameters that maintain sufficient accuracy for practical purposes while dramatically reducing calculation complexity.
3Manufacturing precision
If conventional exposure optimization methods are used, then manufacturing accuracy is maintained, but productivity decreases
Solution Approach 1:
The patent performs preliminary calculation and optimization of exposure conditions before actual manufacturing. The computer simulation system pre-determines optimal exposure parameters, focus settings, and illumination conditions for specific pattern geometries. This preliminary action eliminates the need for time-consuming trial exposures during production, allowing manufacturers to directly implement optimized parameters and significantly improve fabrication throughput while maintaining pattern formation accuracy.
Data Source
AI summary
A generation method of generating, by a computer, data of a pattern of a mask used for an exposure apparatus including a projection optical system. The method includes dividing an effective light source formed on a pupil plane of the projection optical system into a plurality of point sources; generating a plurality of shifted pupil functions by shifting a pupil function corresponding to each of the plurality of point sources by a shift amount in accordance with a position of each point source; defining a matrix by arranging each of the plurality of shifted pupil functions in each row or each column of the matrix; calculating an eigenvalue and an eigenfunction by performing singular value decomposition of the matrix; calculating a map representing, when elements of a target pattern are inserted on an object plane of the projection optical system, an influence the elements inflict on each other.


