LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Rigorous Model-Based Mask Data Preparation Algorithm Applied to Grayscale Lithography for the Patterning at the Micrometer Scale

Photo by campaign_creators from unsplash

Grayscale mask creation has for the most part been restricted to over-simplified optical and resist models usually based on a contrast curve approach. While this technique has proven to work… Click to show full abstract

Grayscale mask creation has for the most part been restricted to over-simplified optical and resist models usually based on a contrast curve approach. While this technique has proven to work for microstructures of large dimensions (ten to hundreds of micrometers), its capability has not been assessed for microstructures with smaller dimensions. In this paper, a rigorous lithographic model has been developed in Python to simulate the process of imaging, exposure and development of an i-line photoresist. Using this model, a mask data preparation algorithm capable of optimizing simultaneously both the size and position of the dots on a grayscale mask has been implemented. Experimental results after development of the photoresist confirm the capability of our mask data preparation algorithm to achieve microstructures with dimensions ranging between 1 to $3~\mu \text{m}$ . [2021-0018]

Keywords: preparation algorithm; mask data; mask; model; data preparation

Journal Title: Journal of Microelectromechanical Systems
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.