Compensation of EUV lithography mask blank defect based on an advanced genetic algorithm

Area of Science:

• Semiconductor Manufacturing
• Optical Lithography
• Materials Science

Background:

• Mask blank defects significantly degrade image quality in extreme ultraviolet (EUV) lithography.
• These defects can lead to substantial yield loss in semiconductor manufacturing.
• Accurate compensation for amplitude and phase distortions is crucial for high-fidelity lithography.

Purpose of the Study:

• To develop an advanced algorithm for optimizing mask absorber patterns to compensate for EUV mask blank defects.
• To enhance the efficiency and accuracy of defect compensation in EUV lithography.
• To improve the fidelity of lithography print images and increase manufacturing yield.

Main Methods:

• A successive approximation correction method is employed for initial compensation of mask blank defect effects.
• An advanced genetic algorithm with adaptive coding and a specialized fitness function is utilized for precise optimization.
• The algorithm considers the normalized image log slope for improved lithography image quality.

Main Results:

• The proposed method effectively mitigates the impact of mask defects on aerial images.
• Simulation results demonstrate improved fidelity of the lithography print image after optimization.
• The genetic algorithm approach shows higher convergence efficiency and ensures mask manufacturability.

Conclusions:

• The developed algorithm successfully compensates for EUV mask blank defects by optimizing absorber patterns.
• This approach enhances lithographic performance, leading to better image quality and yield.
• The method offers an efficient and manufacturable solution for defect compensation in EUV lithography.