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1. (WO2018125220) SYSTEMS, METHODS, AND APPARATUSES FOR IMPLEMENTING OPC MODELING VIA MACHINE LEARNING ON SIMULATED 2D OPTICAL IMAGES FOR SED AND POST SED PROCESSES

Pub. No.:    WO/2018/125220    International Application No.:    PCT/US2016/069523
Publication Date: Fri Jul 06 01:59:59 CEST 2018 International Filing Date: Sat Dec 31 00:59:59 CET 2016
IPC: G03F 1/36
G03F 1/00
G03F 7/20
Applicants: INTEL CORPORATION
Inventors: LAL, Vasudev
WU, Chihhui
TOEPPERWEIN, Gregory
Title: SYSTEMS, METHODS, AND APPARATUSES FOR IMPLEMENTING OPC MODELING VIA MACHINE LEARNING ON SIMULATED 2D OPTICAL IMAGES FOR SED AND POST SED PROCESSES
Abstract:
In accordance with disclosed embodiments, there are provided methods, systems, and apparatuses for implementing Optical Proximity Correction (OPC) modeling via machine learning on simulated 2D optical images for Spin Exposure Develop (SED) and post SED processes. For instance, in accordance with one embodiment, there are means described for creating a mask via a lithography process; fabricating a physical silicon wafer using the mask, the physical silicon wafer having a plurality of features embodied therein as defined by the mask; creating a semi-physical model of the mask using physical parameters of the lithography process used to create the mask, the semi-physical model specifying optical intensity values representing the plurality of features of the mask; capturing Scanning Electron Microscope (SEM) images of the plurality of features embodied within the physical silicon wafer; quantifying differences between (a) the features of the mask as represented by the optical intensity values within the semi-physical model and (b) the plurality of features embodied within the physical silicon wafer as captured by the SEM images; and shifting contours of the plurality of features of the mask as represented by the optical intensity values within the semi-physical model based on the quantified differences. Other related embodiments are disclosed.