1. Computational rule-based approach for corner correction of non-Manhattan geometries in mask aligner photolithography
- Author
-
Toralf Scharf, Chen Yan, Raoul Kirner, Wilfried Noell, Reinhard Voelkel, Carsten Rockstuhl, and Andreas Vetter
- Subjects
Diffraction ,Computer science ,optical proximity correction ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,01 natural sciences ,law.invention ,010309 optics ,Optics ,Optical proximity correction ,law ,0103 physical sciences ,Hardware_INTEGRATEDCIRCUITS ,Lithography ,Orientation (computer vision) ,business.industry ,resolution enhancement ,simulation ,021001 nanoscience & nanotechnology ,Atomic and Molecular Physics, and Optics ,Feature (computer vision) ,Line (geometry) ,lithography ,Photomask ,Photolithography ,0210 nano-technology ,business - Abstract
In proximity mask aligner photolithography, diffraction of light at the mask pattern is the predominant source for image shape distortions such as line end shortening and corner rounding. One established method to mitigate the impact of diffraction is optical proximity correction. This method relies on a deliberate sub-resolution modification of photomask features to counteract such shape distortions, with the goal to improve pattern fidelity and uniformity of printed features. While previously considered for masks featuring only rectangular shapes in horizontal or vertical orientation, called Manhattan geometries, we demonstrate here the capabilities of computational mask aligner lithography by extending optical proximity correction to non-Manhattan geometries. We combine a rigorous simulation method for light propagation with a particle-swarm optimization to identify suitable mask patterns adapt to each occurring feature in the mask. The improvement in pattern quality is demonstrated in experimental prints. Our method extends the use of proximity lithography in optical manufacturing, as required in a multitude of micro-optical devices. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
- Published
- 2019