Source Mask Lens Optimization for Lithography
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Solution Overview
Problem
Current lithographic projection apparatuses face challenges in optimizing projection optics, sources, and masks simultaneously within a practical time frame, leading to inefficiencies in achieving optimal process windows for printing critical circuit patterns, especially at low k1 values where feature sizes approach the wavelength of the illumination source.
Innovation Solution
A computationally efficient method for source mask lens optimization (SMLO) is introduced, which includes optimizing the projection optics, source, and mask simultaneously using a cost function that minimizes deviations in critical parameters, allowing for a larger process window and faster convergence than existing methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing optimization methods are used for projection optics, source, and mask, then optimization can be performed, but the process takes too long and does not converge within a practical time frame
Solution Approach 1:
The optimization process is divided into separate optimization modules for projection optics, source, and mask, allowing each to be optimized independently and then combined. This segmentation enables more efficient computation compared to optimizing all parameters simultaneously, thus reducing total optimization time while maintaining quality.
Solution Approach 2:
The method performs preliminary optimization of projection optics parameters before optimizing source and mask parameters. This staged approach establishes a solid foundation that accelerates subsequent optimization steps, enabling the overall process to converge within a practical time frame.
2Manufacturing precision
If simultaneous optimization of projection optics, source, and mask is performed using existing methods, then comprehensive optimization is achieved, but computational complexity and time requirements become prohibitive
Solution Approach 1:
The complex simultaneous optimization problem is segmented into three distinct optimization modules: projection optics optimization, source optimization, and mask optimization. Each module handles specific parameters independently, reducing the computational complexity of each individual optimization while achieving comprehensive optimization when combined.
Solution Approach 2:
The optimization method dynamically adjusts the optimization process by performing projection optics optimization first, then using those results to guide subsequent source and mask optimization. This dynamic, staged approach reduces overall complexity compared to static simultaneous optimization of all parameters.
Data Source
AI summary
Embodiments of the present invention provide methods for optimizing a lithographic projection apparatus including optimizing projection optics therein, and preferably including optimizing a source, a mask, and the projection optics. The projection optics is sometimes broadly referred to as “lens”, and therefore the joint optimization process may be termed source mask lens optimization (SMLO). SMLO is desirable over existing source mask optimization process (SMO), partially because including the projection optics in the optimization can lead to a larger process window by introducing a plurality of adjustable characteristics of the projection optics. The projection optics can be used to shape wavefront in the lithographic projection apparatus, enabling aberration control of the overall imaging process. According to the embodiments herein, the optimization can be accelerated by iteratively using linear fitting algorithm or using Taylor series expansion using partial derivatives of transmission cross coefficients (TCCs).