Method for training machine learning model to determine optical proximity correction for mask
US12399423B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2020 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Mar 9, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG03F1/36
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Training methods and a mask correction method. One of the methods is for training a machine learning model configured to predict a post optical proximity correction (OPC) image for a mask. The method involves obtaining (i) a pre-OPC image associated with a design layout to be printed on a substrate, (ii) an image of one or more assist features for the mask associated with the design layout, and (iii) a reference post-OPC image of the design layout; and training the machine learning model using the pre-OPC image and the image of the one or more assist features as input such that a difference between the reference image and a predicted post-OPC image of the machine learning model is reduced.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.