Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Region selective super-resolution imaging lithography for 3D via fabrication.

Optics express·2026
Same author

Plasmonic lithography fast imaging model based on the decomposition machine learning method under arbitrary illumination system.

Optics express·2026
Same author

A Two-Stage Unet Framework for Sub-Resolution Assist Feature Prediction.

Micromachines·2025
Same author

Target recognition and grasping strategies for soft robotic manipulators in unstructured environments.

The Review of scientific instruments·2025
Same author

Fast simulation method of lithography latent image on non-planar wafer for large area mask.

Optics express·2025
Same author

Technique of mask optimization for achieving the maximal effective litho-CPW.

Optics express·2025

Related Experiment Video

Updated: Jul 16, 2025

In situ Grazing Incidence Small Angle X-ray Scattering on Roll-To-Roll Coating of Organic Solar Cells with Laboratory X-ray Instrumentation
06:49

In situ Grazing Incidence Small Angle X-ray Scattering on Roll-To-Roll Coating of Organic Solar Cells with Laboratory X-ray Instrumentation

Published on: March 2, 2021

6.3K

Fast diffraction model of an EUV mask based on asymmetric patch data fitting.

Ziqi Li, Xuyu Jing, Lisong Dong

    Applied Optics
    |September 14, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a fast diffraction near field (DNF) model for extreme ultraviolet (EUV) masks. The novel method significantly reduces computation time for EUV lithography modeling while maintaining accuracy.

    More Related Videos

    Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene
    08:44

    Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

    Published on: August 22, 2017

    7.8K
    Atomically Traceable Nanostructure Fabrication
    12:35

    Atomically Traceable Nanostructure Fabrication

    Published on: July 17, 2015

    8.8K

    Related Experiment Videos

    Last Updated: Jul 16, 2025

    In situ Grazing Incidence Small Angle X-ray Scattering on Roll-To-Roll Coating of Organic Solar Cells with Laboratory X-ray Instrumentation
    06:49

    In situ Grazing Incidence Small Angle X-ray Scattering on Roll-To-Roll Coating of Organic Solar Cells with Laboratory X-ray Instrumentation

    Published on: March 2, 2021

    6.3K
    Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene
    08:44

    Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

    Published on: August 22, 2017

    7.8K
    Atomically Traceable Nanostructure Fabrication
    12:35

    Atomically Traceable Nanostructure Fabrication

    Published on: July 17, 2015

    8.8K

    Area of Science:

    • Optics and Photonics
    • Computational Lithography
    • Semiconductor Manufacturing

    Background:

    • Accurate modeling of the diffraction near field (DNF) of three-dimensional (3D) masks is critical for extreme ultraviolet (EUV) lithography imaging.
    • Existing models may face computational challenges due to the complexity of 3D mask structures and asymmetric imaging characteristics of EUV systems.

    Purpose of the Study:

    • To develop a computationally efficient and accurate model for simulating the DNF of 3D EUV masks.
    • To address the limitations of current modeling techniques in terms of speed and resource requirements.

    Main Methods:

    • A fast DNF model based on the asymmetric patch data fitting method is proposed.
    • A DNF library is constructed using training mask patches in various orientations and their rigorous DNF results.
    • A convolution-based compact model is developed, with convolution kernels inversely calculated to fit training data.

    Main Results:

    • The proposed model demonstrates a significant reduction in computation time, achieving 60%-70% faster simulation compared to a state-of-the-art machine learning-based EUV mask model.
    • The simulation accuracy of the proposed method is comparable to existing advanced models.
    • The model effectively handles representative local mask features like corners and edges.

    Conclusions:

    • The developed fast DNF model offers a highly efficient solution for EUV mask modeling.
    • This approach provides a valuable tool for advancing EUV lithography imaging modeling with reduced computational cost.
    • The method shows promise for accelerating the design and analysis of EUV masks.