Taiwan Semiconductor Manufacturing Comp. Ltd.

Zhiru Yu

Danping Peng

Lin Ping Zhang

Junjiang Lei

Yan Feng

A system and a method of optimizing an optical proximity correction (OPC) model for a mask pattern of a photo mask is disclosed. A machine learning (ML) based model builder includes an OPC model, measurement data and a random term generator. Random terms are generated in a M-dimensional space by the random term generator. The ML based model builder classifies the random terms to clusters by applying a classifying rule. A representative subset of the random terms is determined among the classified clusters, and the representative subset is added to the OPC model.

Machine learning based model builder and its applications for pattern transferring in semiconductor manufacturing

In a method of manufacturing a lithographic mask of an integrated circuit for semiconductor device manufacturing an optical proximity correction (OPC) process to a layout pattern of the integrated circuit is performed to produce a corrected layout pattern. An inverse lithographic technology (ILT) process to the corrected layout pattern is also performed to enhance the corrected layout pattern to produce an OPC-ILT-enhanced layout pattern of the lithographic mask. A first contour image associated with the OPC-ILT-enhanced layout pattern is generated when the OPC-ILT-enhanced layout pattern of the lithographic mask is projected on a wafer. The features of the generated first contour image are extracted. And a second contour image of a developed photo resist pattern on the wafer associated with the OPC-ILT-enhanced layout pattern as an output of a deep neural network is generated.

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Zhiru Yu