Computational lithography modeling method and device

Abstract

The application relates to the technical field of integrated circuit manufacturing and discloses a computational lithography modeling method and device. The method comprises the steps of determining an optical module group by acquiring the type of a graphic unit included in a test pattern, and then acquiring the parameters of a physical optical model according to the optical module group; calculating the ideal light intensity distribution of the optical module group on the photoresist, and acquiring the parameters of a photochemical model according to the ideal light intensity distribution and a photochemical reaction excited by the optical module group on the photoresist; then simulating a boundary position formed by the test pattern on the photoresist, acquiring the key dimension simulation data of the test pattern, and establishing a computational lithography model if a fitting error between the key dimension measurement data and the key dimension simulation data is not greater than a preset allowable tolerance. The computational lithography modeling method disclosed in the application improves the precision of a lithography model by establishing different optical modules to simulate different graphic units.

Description

technical field [0001] The present application relates to the technical field of integrated circuit manufacturing, and in particular to a computational lithography modeling method and device. Background technique [0002] With the development of photolithography technology, the size of devices in the integrated circuit manufacturing process has developed from submicron to ultra-deep submicron, that is, the key line width of devices has been continuously reduced. As the key line width of the device shrinks, the optical proximity effect (Optical Proximity Effect, OPE) in the lithography process becomes more and more prominent. After the graphics on the reticle are transferred to the wafer surface, various distortions occur in the acquired graphics, such as narrowing of the line width. In order to solve this problem, the model-based Optical Proximity Correction (OPC) technology is usually used to correct the mask pattern before lithography, so that the lithography results can ...

AI Technical Summary

Problems solved by technology

In a set of computational lithography model parameters, the physical optics model parameters corresponding to an optical module, when simulating and fitting a test pattern, the fitting results obtained for different pattern units are different, which leads to When using the fitting results to optimize the model parameters, the accuracy of the optimization results cannot be guaranteed

Therefore, with the increasing complexity of the test pattern, the accuracy of the computational lithography model will not be able to meet the requirements of the lithography process

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