Work

High-precision misalignment sensing for lithography using a joint space-frequency regression network

Year: 2025

Type: article

Abstract: In the realm of lithography misalignment sensing, achieving sub-0.2 nm precision is fraught with significant obstacles, largely due to the exacting demands placed on regression algorithms tasked with analyzing moiré fringes. These challenges stem from the inherent limitations of convolutional networks that process information from only one domain, often resulting in a deficit of critical feature data necessary for high-precision regression. To overcome these hurdles, we have engineered a groundbreaking convolutional regression network that synthesizes both spatial and frequency domain information from fringe patterns. This holistic approach has successfully recorded misalignment measurements with remarkable accuracy, achieving 0.12 nm at a 3σ confidence level. The method has shown considerable robustness against both system errors and environmental noise, bolstering its suitability for critical applications.

Source: Optics Express

DOI: 10.1364/oe.545315

Authors: Nan Wang, Wei Jiang

Institution: Chengdu Technological University

Language: English

Topic: Optical measurement and interference techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,270

Funder: National Natural Science Foundation of China