Computational lithography is a set of mathematical and algorithmic approaches used to improve the resolution and manufacturability of integrated circuits during the photolithography process. As semiconductor features shrink below the wavelength of light used in patterning, traditional optical methods become insufficient—computational techniques bridge this gap.
Key Techniques
- Optical Proximity Correction (OPC): Modifies mask patterns to compensate for optical distortions.
- Inverse Lithography Technology (ILT): Treats mask synthesis as an inverse problem to produce optimal mask shapes.
- Source-Mask Optimization (SMO): Co-optimizes the illumination source and mask design for better patterning fidelity.
Why It Matters
As Moore’s Law pushes toward ever-smaller transistors, computational lithography enables continued scaling without requiring entirely new light sources or equipment. It plays a critical role in advanced nodes such as 7nm, 5nm, and beyond.
Further Reading
For more information, refer to academic journals like Journal of Micro/Nanolithography or industry resources from companies like ASML, Synopsys, and Cadence.