Initiative global NILS control in source and mask optimization for process window enhancement.

Area of Science:

• Semiconductor manufacturing
• Photolithography
• Integrated circuit fabrication

Background:

• Semiconductor processing faces challenges with shrinking integrated circuit dimensions.
• Source and Mask Optimization (SMO) is vital for ensuring pattern fidelity.
• Process Window (PW) and Normalized Image Log Slope (NILS) are critical lithography parameters, with NILS strongly correlated to PW.

Purpose of the Study:

• To actively incorporate NILS into the inverse lithography model of SMO.
• To improve the control over NILS during optimization, moving beyond its passive use as a forward lithography metric.
• To enhance the Process Window (PW) and exposure latitude in semiconductor lithography.

Main Methods:

• Introduced NILS into the inverse lithography model for SMO.
• Utilized a penalty function to ensure continuous increase of initial NILS.
• Simulated the method using two typical 45-nm-node masks.

Main Results:

• The proposed method effectively enhances the Process Window (PW).
• NILS increased by 16% and 9% for the two mask layouts, respectively.
• Exposure latitudes increased by 21.5% and 21.7% while maintaining pattern fidelity.

Conclusions:

• Actively controlling NILS within the inverse SMO framework significantly improves lithographic performance.
• The method offers a predictable enhancement of PW and exposure latitude.
• This approach is beneficial for advanced semiconductor manufacturing requiring high pattern fidelity.