SEM FOV fingerprint in stochastic EPE and placement measurements in large FOV SEM devices
A method of reducing variability of an error associated with a structure on a substrate in a lithography process is disclosed. The method includes determining, based on one or more images obtained based on a scan of the substrate by a scanning electron microscope (SEM), a first error due to a SEM distortion in the image. The method also includes determining, based on the image, a second error associated with a real error of the structure, where the error associated with the structure includes the first error and the second error. A command is generated by a data processor that enables a modification of the lithography process and an associated reduction of the variability of the error based on reducing any of the first error or the second error.
1. A method comprising:
determining, based on an image obtained based on a measurement of a substrate by a scanning electron microscope (SEM), a first error due to a SEM distortion in the image;
determining, based on the image, a second error associated with a real error of a structure on the substrate, where the error associated with the structure in a lithography process comprises the first error and the second error; and
generating, by a data processor, a command that enables a modification of the lithography process and an associated reduction of a variability of the error associated with the structure based on reducing any of the first error or the second error, wherein the error is determined in part by averaging a plurality of local errors corresponding to a plurality of neighboring features in a field of view of the SEM.
2. The method of claim 1 , wherein the determining, based on the image, the first error includes determining, based on a plurality of images obtained based on the measurement of the substrate by the SEM, the first error, and/or
wherein the determining, based on the image, the second error includes determining, based on the plurality of images, the second error.
3. The method of claim 1 , wherein the real error is a difference between a feature on the structure and a corresponding feature in a target pattern.
4. The method of claim 3 , wherein the feature is any selected from: an edge placement gauge, a contact hole center, or a critical dimension.
5. The method of claim 1 , wherein the SEM distortion is due to any selected from: an artifact in electron imaging, vibration in the SEM system, or an artifact in electron detection.
6. The method of claim 1 , further comprising decomposing the first error into a time-constant error or a time-dependent error.
7. The method of claim 6 , further comprising removing any of the time-constant error or time-dependent error from the first error to reduce the error.
8. The method of claim 1 , wherein the first error or the second error is mean square error and wherein the variability of the error is a standard deviation of the error or a variance of the error.
9. The method of claim 1 , further comprising:
generating, with an edge detection algorithm, a contour on a portion of the structure; and
determining the error based on a difference between the contour and a corresponding feature in a target pattern.
10. The method of claim 9 , wherein the local errors are weighted according to a weighted average of the plurality of local errors and centered at a center of the plurality of neighboring features, or the local errors are weighted according to a Gaussian distribution centered at a center of the plurality of neighboring features.
11. The method of claim 1 , further comprising:
generating a real residual displacement by at least removing the first error associated with the SEM distortion; and
flagging a feature of the structure when a portion of the real residual displacement associated with the feature exceeds a threshold.
12. The method of claim 1 , further comprising:
monitoring a plurality of images acquired by the SEM;
determining whether the error exceeds a threshold; and
generating, when the threshold is exceeded, any one or more selected from: an alert to a user to recalibrate the SEM, a command causing the SEM to automatically recalibrate, or an instruction that modifies the operation of the SEM to reduce the error.
13. The method of claim 1 , wherein the modification of the lithography process comprising any selected from: changing a focus of radiation used to manufacture the substrate, modifying a parameter used in a source-mask optimization, modifying a number of radiation sources used in the lithography process, or modifying a configuration of a mirror on a digital mirror device.
14. A computer program product comprising a non-transitory computer readable medium having instructions therein, the instructions, upon execution by a computer system, configured to cause the computer system to at least:
determine, based on an image obtained based on a measurement of a substrate by a scanning electron microscope (SEM), a first error due to a SEM distortion in the image;
determine, based on the image, a second error associated with a real error of a structure on the substrate, where the error associated with the structure in a lithography process comprises the first error and the second error; and
generate a command that enables a modification of the lithography process and an associated reduction of a variability of the error associated with the structure based on reducing any of the first error or the second error, wherein the error is determined in part by averaging a plurality of local errors corresponding to a plurality of neighboring features in a field of view of the SEM.
15. The computer program product of claim 14 , wherein the real error is a difference between a feature on the structure and a corresponding feature in a target pattern and wherein the feature is any selected from: an edge placement gauge, a contact hole center, or a critical dimension.
16. The computer program product of claim 14 , wherein the SEM distortion is due to any selected from: an artifact in electron imaging, vibration in the SEM system, or an artifact in electron detection.
17. A system comprising:
a scanning electron microscope (SEM) configured to scan a substrate with an electron beam and generate an image of the substrate, the image indicating an error associated with a structure on the substrate; and
the computer program product of claim 14 .
18. A computer program product comprising a non-transitory computer readable medium having instructions therein, the instructions, upon execution by a computer system, configured to cause the computer system to at least:
determine, based on an image obtained based on a measurement by a scanning electron microscope (SEM), a first error due to a SEM distortion in the image, wherein the image indicates an error associated with a structure on the substrate; and
generate a command that enables a modification of a lithography process and an associated reduction of a variability of the error associated with the structure on the substrate based on reducing the first error.
19. The computer program product of claim 18 , wherein the instructions are further configured to cause the computer system to:
determine, based on the image, a second error associated with a real error of the structure, where the error associated with the structure comprises the first error and the second error,
wherein the command enables the modification of the lithography process and the associated reduction of the variability of the error based on reducing the first error or the second error, and
wherein the error is determined in part by averaging a plurality of local errors corresponding to a plurality of neighboring features in a field of view of the SEM.
20. A system comprising:
a scanning electron microscope (SEM) configured to scan a substrate with an electron beam and generate an image of the substrate, the image indicating an error associated with a structure on the substrate; and
the computer program product of claim 18 .