Optical metrology of structures formed on semiconductor wafers using machine learning systems
First Claim
1. A method of examining a structure formed on a semiconductor wafer, the method comprising:
- obtaining a first diffraction signal measured using a metrology device;
obtaining a second diffraction signal generated using a machine learning algorithm,wherein the first and second diffraction signal represent light diffracted from the structure formed on the semiconductor wafer, andwherein the machine learning algorithm receives as a direct input one or more parameters that characterize a profile of the structure to generate the second diffraction signal as a direct output of the machine learning algorithm;
comparing the first and second diffraction signals; and
when the first and second diffraction signals match within a matching criterion, determining a feature of the structure based on the one or more parameters of the profile used by the machine learning algorithm to generate the second diffraction signal.
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Abstract
A structure formed on a semiconductor wafer is examined by obtaining a first diffraction signal measured using a metrology device. A second diffraction signal is generated using a machine learning system, where the machine learning system receives as an input one or more parameters that characterize a profile of the structure to generate the second diffraction signal. The first and second diffraction signals are compared. When the first and second diffraction signals match within a matching criterion, a feature of the structure is determined based on the one or more parameters or the profile used by the machine learning system to generate the second diffraction signal.
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Citations
29 Claims
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1. A method of examining a structure formed on a semiconductor wafer, the method comprising:
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obtaining a first diffraction signal measured using a metrology device; obtaining a second diffraction signal generated using a machine learning algorithm, wherein the first and second diffraction signal represent light diffracted from the structure formed on the semiconductor wafer, and wherein the machine learning algorithm receives as a direct input one or more parameters that characterize a profile of the structure to generate the second diffraction signal as a direct output of the machine learning algorithm; comparing the first and second diffraction signals; and when the first and second diffraction signals match within a matching criterion, determining a feature of the structure based on the one or more parameters of the profile used by the machine learning algorithm to generate the second diffraction signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A computer-readable storage medium containing computer executable instructions for causing a computer to examine a structure formed on a semiconductor wafer, comprising instructions for:
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obtaining a first diffraction signal measured using a metrology device; obtaining a second diffraction signal generated using a machine learning algorithm, wherein the first and second diffraction signal represent light diffracted from the structure formed on the semiconductor wafer, and wherein the machine learning algorithm receives as a direct input one or more parameters that characterize a profile of the structure to generate the second diffraction signal as a direct output of the machine learning algorithm; comparing the first and second diffraction signals; and when the first and second diffraction signals match within a matching criterion, a feature of the structure is determined based on the one or more parameters of the profile used by the machine learning algorithm to generate the second diffraction signal. - View Dependent Claims (17, 18, 19, 20, 21)
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22. A system to examine a structure formed on a semiconductor wafer, the system comprising:
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a metrology device configured to measure a first diffraction signal from the structure; a machine learning algorithm configured to generate a second diffraction signal, wherein the first and second diffraction signal represent light diffracted from the structure formed on the semiconductor wafer, and wherein the machine learning algorithm receives as a direct input one or more parameters that characterize a profile of the structure to generate the second diffraction signal as a direct output of the machine learning algorithm; and a processor configured to compare the first and second diffraction signals, wherein when the first and second diffraction signals match within a matching criterion, a feature of the structure is determined based on the one or more parameters or the profile used by the machine learning algorithm to generate the second diffraction signal. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29)
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Specification