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 μm. [2021-0018]
Highlights
G RAYSCALE lithography is an alternative lithography technique enabling the patterning of 3D microstructures in a photoresist material with application ranging from microfluidic [1], optics [2]–[5] and MEMS [6], [7]
This paper proposes a rigorous approach to the modeling of grayscale lithography
The contrast curve is at the center of many grayscale lithography publications for it is used as a transfer function between the resist target and the density on the mask
Summary
G RAYSCALE lithography is an alternative lithography technique enabling the patterning of 3D microstructures in a photoresist material with application ranging from microfluidic [1], optics [2]–[5] and MEMS [6], [7]. Grayscale lithography consists in a combination between a low contrast photoresist and a spatially variable exposure dose that control the resist height after development. A lithographic model compatible with i-line lithography has been developed This model is used to create a new mask data preparation algorithm capable of optimizing both the size and the position of the dots for any resist target. The quality of this approach will be illustrated on experimental profiles of microstructures with vertical and lateral dimensions below 2μm. The final part concludes on the capability of our approach
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