Semiconductor device and method of aligning semiconductor wafers for bonding
US-9852972-B2 · Dec 26, 2017 · US
US11829077B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11829077-B2 |
| Application number | US-202117161369-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 28, 2021 |
| Priority date | Dec 11, 2020 |
| Publication date | Nov 28, 2023 |
| Grant date | Nov 28, 2023 |
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A wafer shape metrology system includes a wafer shape metrology sub-system configured to perform one or more stress-free shape measurements on a first wafer, a second wafer, and a post-bonding pair of the first and second wafers. The wafer shape metrology system includes a controller communicatively coupled to the wafer shape metrology sub-system. The controller is configured to receive stress-free shape measurements from the wafer shape sub-system; predict overlay between one or more features on the first wafer and the second wafer based on the stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer; and provide a feedback adjustment to one or more process tools based on the predicted overlay. Additionally, feedforward and feedback adjustments may be provided to one or more process tools.
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What is claimed: 1. A wafer shape metrology system comprising: a wafer shape metrology sub-system configured to perform one or more stress-free shape measurements on a first wafer, a second wafer, and a post-bonding pair of the first wafer and the second wafer; and a controller communicatively coupled to the wafer shape metrology sub-system, the controller including one or more processors configured to execute a set of program instructions stored in a memory, the set of program instructions configured to cause the one or more processors to: receive the one or more stress-free shape measurements from the wafer shape sub-system; predict overlay between one or more features on the first wafer and one or more features on the second wafer based on the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer; and provide a feedback adjustment to one or more process tools based on the predicted overlay. 2. The wafer shape metrology system of claim 1 , wherein the predicting the overlay between the one or more features on the first wafer and the one or more features on the second wafer based on the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer comprises: extracting one or more wafer shape parameters from the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer. 3. The wafer shape metrology system of claim 2 , wherein the extracted one or more wafer shape parameters comprises at least one of local shape curvature (LSC) or in-plane distortion (IPD). 4. The wafer shape metrology system of claim 2 , further comprising: inputting the extracted one or more wafer shape parameters into a machine learning algorithm to predict the overlay between the one or more features on the first wafer and the one or more features on the second wafer. 5. The wafer shape metrology system of claim 4 , furthering comprising: training the machine learning algorithm. 6. The wafer shape metrology system of claim 5 , wherein the training the machine learning algorithm comprises: training the machine learning algorithm with infrared overlay data. 7. The wafer shape metrology system of claim 2 , further comprising: inputting the extracted one or more wafer shape parameters into a mechanical model to predict the overlay between the one or more features on the first wafer and the one or more features on the second wafer. 8. The wafer shape metrology system of claim 1 , wherein the providing the one or more feedback control signals to the one or more process tools based on the predicted overlay comprises: providing the one or more feedback control signals to a bonder based on the predicted overlay to adjust one or more process controls of the bonder. 9. The wafer shape metrology system of claim 1 , wherein the wafer shape metrology sub-system comprises a first interferometer sub-system and a second interferometer sub-system. 10. A system comprising: a controller configured to receive shape measurements from a wafer shape metrology sub-system, the controller including one or more processors configured to execute a set of program instructions stored in a memory, the set of program instructions configured to cause the one or more processors to: receive one or more stress-free shape measurements from a wafer shape sub-system; predict overlay between one or more features on a first wafer and one or more features on a second wafer based on the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer; and provide a feedback adjustment to one or more process tools based on the predicted overlay. 11. The system of claim 10 , wherein the predicting overlay between the one or more features on the first wafer and the one or more features on the second wafer based on the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer comprises: extracting one or more wafer shape parameters from the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer. 12. The system of claim 11 , wherein the extracted one or more wafer shape parameters comprises at least one of local shape curvature (LSC) or in-plane distortion (IPD). 13. The system of claim 11 , further comprising: inputting the extracted one or more wafer shape parameters into a machine learning algorithm to predict overlay between the one or more features on the first wafer and the one or more features on the second wafer. 14. The system of claim 13 , furthering comprising: training the machine learning algorithm. 15. The system of claim 14 , wherein the training the machine learning algorithm comprises: training the machine learning algorithm with infrared overlay data. 16. The system of claim 10 , further comprising: inputting the extracted one or more wafer shape parameters into a mechanical model to predict overlay between one or more features on the first wafer and one or more features on the second wafer. 17. The system of claim 10 , wherein the providing one or more feedback control signals to the one or more process tools based on the predicted overlay comprises: providing the one or more feedback control signals to a bonder based on the predicted overlay to adjust one or more process controls of the bonder. 18. The system of claim 10 , wherein the wafer shape metrology sub-system comprises a first interferometer sub-system and a second interferometer sub-system. 19. A method comprising: acquiring one or more stress-free shape measurements for a first wafer, a second wafer, and a post-bonding pair of the first wafer and the second wafer; predicting overlay between one or more features on the first wafer and one or more features on the second wafer based on the one or more stress-free shape measurements of the first wafer, the second wafer, and the post-bonding pair of the first wafer and the second wafer; and providing a feedback adjustment to one or more process tools based on the predicted overlay.
Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects · CPC title
characterised by multiple measurements, corrections, marking or sorting processes · CPC title
Monitoring of warpages, curvatures, damages, defects or the like · CPC title
Subject matter not provided for in other groups of this subclass · CPC title
Overlay, i.e. relative alignment between patterns printed by separate exposures in different layers, or in the same layer in multiple exposures or stitching · CPC title
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