Lithographic Source and Mask Optimization for Low k1 Imaging
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Solution Overview
Problem
Current lithographic processes face challenges in optimizing the illumination source and design layout to achieve precise imaging of small features on substrates, particularly in low k1 lithography, where traditional methods struggle with resolution and radiation intensity, and require complex iterative processes that are not always effective.
Innovation Solution
A computer-implemented method that optimizes the lithographic process by obtaining source shapes and mask defocus values, using three-dimensional mask models to simulate aerial images, and adjusting illumination sources and design layouts to achieve optimal dose and focus, while incorporating assist features and stochastic variation considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional lithographic methods are used for low k1 lithography, then manufacturing process is simpler, but imaging precision and resolution deteriorate
Solution Approach 1:
The patent applies preliminary action by performing source and mask optimization calculations before the actual lithographic exposure process. The method pre-determines optimal illumination source parameters and mask design modifications using computational models, then applies these pre-optimized parameters in the physical lithography process. This allows traditional lithographic equipment to achieve enhanced imaging precision without requiring complex real-time adjustments during exposure.
Solution Approach 2:
The patent employs parameter changes by systematically varying illumination source parameters (such as angular distribution, spectral content, and spatial coherence) and mask parameters (such as phase shifts and amplitude modulations) to optimize the lithographic process. The method calculates optimal parameter sets that maximize imaging precision for low k1 conditions, then implements these parameter changes in the lithographic apparatus without fundamental process redesign.
2Manufacturing precision
If iterative optimization processes are used to improve imaging precision, then manufacturing precision improves, but processing time increases
Solution Approach 1:
The patent resolves this contradiction by performing all iterative optimization calculations in advance, before production lithography runs. The source and mask optimization is completed during mask fabrication or process setup, using computational models to converge on optimal parameters. Once optimized, these parameters are fixed and applied consistently in production, eliminating the need for repeated iterative adjustments during manufacturing while maintaining high pattern transfer fidelity.
Solution Approach 2:
The patent uses computational models and simulations as copies of the physical lithographic process to perform iterative optimization. Instead of repeatedly running physical experiments to optimize parameters, the method creates virtual copies of the lithographic process through mathematical models, performs iterative optimization in the computational domain, then applies the resulting parameters to the physical process. This dramatically reduces processing time while maintaining optimization quality.
3Measurement precision
If illumination source and design layout are optimized together, then imaging accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the source and mask optimization problem into separate, independently solvable sub-problems. The method first optimizes illumination source parameters while holding mask parameters fixed, then optimizes mask parameters while holding source parameters fixed, and iterates between these two optimization steps. This segmented approach reduces the computational complexity of each individual optimization step compared to simultaneous optimization of all parameters, while still achieving high feature imaging accuracy through the coupled optimization process.
Data Source
AI summary
A method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus having an illumination system and projection optics, the method including: obtaining an illumination source shape and a mask defocus value; optimizing a dose of the lithographic process; and optimizing the portion of the design layout for each of a plurality of slit positions of the illumination source.