Method for improving test pattern coverage range by photoetching model data

Abstract

The invention provides a method for improving a test pattern coverage range by photoetching model data. On the basis of a standard pattern parameter space, the specific structural parameters of a testpattern are added to the standard pattern parameter space; and by performing blank space analysis, the specific test pattern structure missed in the model data is given, thereby realizing a wider coverage range on the test pattern by the photoetching model by means of supplementing the missed model data. By virtue of the new method, it is ensured that the photoetching model has enough coverage range on the test pattern, so that more accurate prediction in an exposure process can be realized. In a photoetching model calibration process, a method for improving the test pattern coverage range bythe photoetching model is proposed, based on the standard image variables and test pattern structural parameters at the same time, thereby improving prediction accuracy on the exposure process and the pattern coverage by the photoetching model.

Description

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AI Technical Summary

Benefits of technology

It describes an improved way to make sure certain parts or features are covered correctly during photolithographic processes used to create semiconductor devices such as integrated circuits (IC). By adding extra dimensions like pixels or lines with known properties to these areas instead of just covering them entirely, we aimed at achieving better quality images from this type of manufacturing.

Problems solved by technology

This patents describes how precise photomasks used during semiconductor device fabrication have been designed with various techniques such as error diffusion algorithms or compensated images obtained through simulation tools like simulated particle hydrodynamics simulations. These errors affect the accuracy of the final printed product due to variations caused by factors like alignment issues when printing different layers onto each other. To correct these distortions, advanced testing methods called Optically Proximance Correctors (OPCs) were introduced into this field.

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