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Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...

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Updated: Jun 8, 2026

Patterning via Optical Saturable Transitions - Fabrication and Characterization
08:19

Patterning via Optical Saturable Transitions - Fabrication and Characterization

Published on: December 11, 2014

Physical optics modeling in soft-x-ray projection lithography.

W C Sweatt, G N Lawrence

    Applied Optics
    |September 22, 2010
    PubMed
    Summary
    This summary is machine-generated.

    We created a new diffraction tool to predict image quality in projection lithography. This method accounts for partial coherence, source changes, and optical defects for accurate predictions.

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    Area of Science:

    • Optics and Photonics
    • Semiconductor Manufacturing

    Background:

    • Projection lithography is crucial for microchip fabrication.
    • Accurate prediction of image quality is essential for process control and yield optimization.

    Purpose of the Study:

    • To develop a novel diffraction-based computational tool for predicting image quality in projection lithography systems.
    • To incorporate the effects of partial coherence, source variations, and optical aberrations into the image quality prediction.

    Main Methods:

    • A diffraction-based model was developed to simulate image formation.
    • The model accounts for partially coherent illumination conditions.
    • It also incorporates aberrations in both condenser and camera optics.

    Main Results:

    • The tool successfully predicts image quality degradation due to partial coherence.
    • Source variations and imaging defects in optical systems are quantifiable.
    • The model provides a comprehensive assessment of factors influencing lithographic image fidelity.

    Conclusions:

    • The developed diffraction-based tool offers a robust method for evaluating image quality in projection lithography.
    • It enables better understanding and mitigation of factors affecting lithographic performance.
    • This tool can aid in the design and optimization of lithography systems.