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DMD digital lithography optimization based on a hybrid genetic algorithm and improved exposure model.

Shengzhou Huang, Yuanzhuo Tang, Bowen Ren

|November 22, 2024

Summary

A new hybrid genetic algorithm (GA) with an improved exposure model enhances digital micromirror device (DMD) lithography precision. This method significantly boosts imaging quality and reduces distortions in microelectronics fabrication.

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Area of Science:

Micro- and Nanofabrication
Optical Engineering
Computational Lithography

Background:

Digital Micromirror Device (DMD) lithography is crucial for microelectronics fabrication.
Traditional exposure models often lack the precision needed for complex patterns.
Optimization of lithographic processes is essential for improving yield and device performance.

Purpose of the Study:

To develop an efficient method for optimizing DMD lithography.
To enhance lithographic precision and imaging quality.
To reduce optical proximity distortions in microfabrication.

Main Methods:

Integration of a hybrid genetic algorithm (GA) with an improved exposure model.
The improved exposure model incorporates advanced parameters: cross-transfer coefficient, light source functions, and impulse response functions.
Optimization of micromirror configurations and light distribution for specific lithographic patterns.

Main Results:

Substantial improvements in lithographic precision achieved: up to 84% for hexagonal star patterns, 83% for arrow patterns, and 85% for embedded figure patterns.
Enhanced simulation accuracy of light-photoresist interactions.
Significant reduction in optical proximity distortions.

Conclusions:

The proposed hybrid GA and improved exposure model offer a highly efficient method for optimizing DMD lithography.
This approach leads to superior imaging quality and precision in microelectronics fabrication.
The findings provide valuable insights for advancing precision and efficiency in microfabrication processes.