US 2023/0417682 A1 · METROLOGY SOLUTIONS FOR COMPLEX STRUCTURES OF INTEREST

Abstract

Complex structures, such as gate-all-around (GAA) field effect transistor or high-aspect ratio (HAR) Channel hole etch, etc., in semiconductor devices are measured using a combination of physical modeling and machine learning modeling. Metrology signals collected at different manufacturing process steps, e.g., pre-process step and post-process step of the structure of interest (SOI) may be used. The measurement signals acquired at the pre-process steps are used to determine a first parameter of the SOT, e.g., using physical modeling and machine learning, which may be fed forward and used to generate a physical model of the SOI at the post-process step. A second parameter of the SOI at the post-process step is determined using physical modeling and machine learning and may be fed back and used to generate the physical model of the SOI at the post-process step with post process signals and used to determine other parameters.

Claims24

Dependent claims

A method for measuring at least one parameter of interest from a structure of interest (SOI), comprising:

obtaining post-process step measured signals from a metrology device for a SOI on one or more samples at a post-process step;
extracting post-process measurement results from a post-process physical model for the SOI based on the post-process step measured signals and at least one of a value of a first parameter for the SOI at a pre-process step that is fed forward to the post-process physical model, a value of a second parameter for the SOI at the post-process step that is fed back to the post-process physical model, and a combination thereof;
predicting a final value of the second parameter for the SOI at the post-process step from a trained post-process machine learning model based on the post-process measurement results extracted from the post-process physical model;
and
providing at least the final value of the second parameter for the SOI.

2 more elements

A computer system configured for measuring at least one parameter of interest from a structure of interest (SOI) comprising:

at least one processor, wherein the at least one processor is configured to:
obtain post-process step measured signals from a metrology device for a SOI on one or more samples at a post-process step;
extract post-process measurement results from a post-process physical model for the SOI based on the post-process step measured signals and at least one of a value of a first parameter for the SOI at a pre-process step that is fed forward to the post-process physical model, a value of a second parameter for the SOI at the post-process step that is fed back to the post-process physical model, and a combination thereof;
predict a final value of the second parameter for the SOI at the post-process step from a trained post-process machine learning model based on the post-process measurement results extracted from the post-process physical model;
and
provide at least the final value of the second parameter for the SOI.

3 more elements

Dependencies are inferred from the claim text.

Metrology solutions for complex structures of interest

Life of this patent

Metrology solutions for complex structures of interest

Life of this patent

Abstract

Claims24