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Related Experiment Video

Updated: Oct 17, 2025

Use of Sacrificial Nanoparticles to Remove the Effects of Shot-noise in Contact Holes Fabricated by E-beam Lithography

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Efficient informatics-based source and mask optimization for optical lithography.

Yihua Pan, Xu Ma, Shengen Zhang

|October 6, 2021

Summary

This summary is machine-generated.

This study introduces an efficient informatics-based Source and Mask Optimization (SMO) method. The new approach enhances lithography system image fidelity and reduces patterning errors computationally.

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Last Updated: Oct 17, 2025

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Published on: January 25, 2021

Area of Science:

Computational lithography
Image fidelity enhancement
Semiconductor manufacturing

Background:

Source and Mask Optimization (SMO) is crucial for improving lithography system image fidelity.
Existing SMO methods can be computationally intensive.
Advanced techniques are needed to further reduce lithography patterning errors.

Purpose of the Study:

To develop an efficient informatics-based SMO (EISMO) method.
To enhance image fidelity in lithography systems.
To reduce lithography patterning error through computational refinement.

Main Methods:

Established a communication channel model for information transmission in SMO.
Optimized manufacturing-aware mask distribution for maximum mutual information.
Proposed an informatics-based refinement for mask optimization results.

Main Results:

Achieved a theoretical lower bound for lithography patterning error.
The EISMO method demonstrated computational efficiency.
Superior imaging performance compared to conventional SMO methods was observed.

Conclusions:

The developed EISMO method offers a computationally efficient approach to SMO.
EISMO significantly reduces lithography patterning errors.
This technique enhances overall imaging performance in lithography.