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Multi-objective and multi-solution source mask optimization using NSGA-II for more direct process window enhancement
Optics Express
|March 5, 2024
Summary
This study introduces NSGA-SMO, a new method for source and mask optimization (SMO) in photolithography. It enhances process window (PW) performance, improving lithography robustness and imaging quality for advanced critical dimensions (CD).
Area of Science:
- Semiconductor Manufacturing
- Optical Engineering
- Computational Lithography
Background:
- Source and Mask Optimization (SMO) is crucial for photolithography resolution enhancement as critical dimensions (CD) shrink.
- Traditional SMO methods focus on in-focus imaging quality, neglecting the Process Window (PW), which includes Depth of Focus (DOF) and Exposure Latitude (EL), vital for lithography robustness.
- Evaluating PW is computationally intensive and challenging for gradient-based SMO algorithms.
Purpose of the Study:
- To develop a novel SMO method that directly optimizes Process Window (PW) performance.
- To enhance the robustness of SMO results in advanced technology nodes by considering lithographic process variations.
- To maintain high in-focus image quality while improving lithographic process margins.
Main Methods:
- Proposed a novel Process Window enhancement SMO method, termed NSGA-SMO, utilizing the Nondominated Sorting Genetic Algorithm II (NSGA-II).
- Employed the Variational Lithography Model (VLIM), a fast focus-variation aerial image model, for direct PW optimization.
- Implemented a multi-objective optimization approach to balance in-focus imaging quality and PW performance.
Main Results:
- NSGA-SMO demonstrated significant improvements in Depth of Focus (DOF) and Exposure Latitude (EL) compared to conventional multi-objective SMO.
- Simulations showed over 20% improvement in DOF and EL for typical patterns.
- For complicated patterns, NSGA-SMO achieved results up to four times superior to single-objective SMO.
Conclusions:
- The proposed NSGA-SMO method effectively optimizes Process Window (PW) performance in photolithography.
- This approach enhances lithographic process robustness, crucial for advanced critical dimensions (CD).
- NSGA-SMO offers a viable solution for improving imaging quality and process margins in high-volume manufacturing.
