Source Mask Optimization for Stochastic Effects in Lithography
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Solution Overview
Problem
Current lithographic processes face challenges in optimizing both the illumination source and patterning device/design layout simultaneously to achieve optimal balance between resolution and radiation intensity, especially in low-k1 lithography, where proximity effects and stochastic effects complicate the reproduction of small feature sizes and high feature densities.
Innovation Solution
A computer-implemented method is introduced that defines a multi-variable cost function based on stochastic effects of the lithographic process, allowing for the simultaneous optimization of the illumination source and patterning device/design layout by adjusting design variables until a termination condition is met, which can include minimizing the cost function or maximizing the process window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the illumination source and patterning device are optimized separately, then the optimization process is simpler, but the balance between resolution and radiation intensity is suboptimal
Solution Approach 1:
The patent combines the optimization of the illumination source and patterning device into a single integrated process. The system simultaneously adjusts parameters of both the illumination source (such as angular distribution, spectral content) and patterning device (such as feature geometry, spacing) to achieve optimal resolution while maintaining adequate radiation intensity. This merged optimization approach resolves the contradiction by treating the previously separate optimizations as a unified multi-parameter optimization problem.
2Illumination intensity
If the illumination intensity is increased to improve signal strength, then the radiation intensity is sufficient, but stochastic effects are exacerbated
Solution Approach 1:
The patent changes the parameters of the illumination source, specifically optimizing the angular distribution and spectral content of the illumination. By adjusting these parameters, the system achieves sufficient signal strength without relying solely on increased intensity, thereby reducing the impact of stochastic effects such as shot noise and photon statistics variations. This parameter optimization allows for lower intensity operation while maintaining image quality and reducing stochastic variability.
3Productivity
If the feature size is reduced to increase feature density, then the functional elements per device increase, but proximity effects and stochastic effects complicate pattern reproduction
Solution Approach 1:
The patent applies local quality optimization by tailoring the illumination characteristics and patterning device features to specific regions of the design layout. Different areas with varying feature densities and geometries receive customized illumination conditions and patterning parameters. This localized optimization ensures that each region achieves optimal pattern reproduction accuracy despite the overall high feature density, effectively managing proximity effects and stochastic variations across the diverse layout.
Data Source
AI summary
Disclosed herein is a computer-implemented method for improving a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus, the method comprising defining a multi-variable cost function, the multi-variable cost function being a function of a stochastic effect of the lithographic process.