Method and system for semiconductor wafer defect review
A semiconductor wafer defect detection system captures test images of a semiconductor wafer. The system analyzes the test images with an analysis model trained with a machine learning process. The analysis model generates simulated integrated circuit layouts based on the test images. The system detects defects in the semiconductor wafer by comparing the simulated integrated circuit layouts to reference integrated circuit layouts.
1. A method, comprising:
capturing a test image of a semiconductor wafer;
generating a simulated integrated circuit layout by analyzing the test image;
generating a reference image of a reference semiconductor wafer;
generating a reference layout based on the reference image;
comparing the simulated integrated circuit layout to the reference layout; and
identifying defects in the semiconductor wafer based on comparing the simulated integrated circuit layout to the reference layout.
2. The method of claim 1 , wherein comparing the simulated integrated circuit layout to the reference integrated circuit layout includes generating a difference layout corresponding to a difference between the reference integrated circuit layout and the simulated integrated circuit layout.
3. The method of claim 2 , wherein identifying defects in the semiconductor wafer includes identifying difference locations in the difference layout.
4. The method of claim 1 , wherein the reference integrated circuit layout is a layout utilized for generating a photolithography mask for semiconductor processing.
5. The method of claim 1 , further comprising generating the simulated integrated circuit layout with an image processing system.
6. The method of claim 5 , further comprising training, with a machine learning process, the image processing system to generate simulated integrated circuit layouts based on test images.
7. The method of claim 6 , wherein the machine learning process includes utilizing a labeled training set including training images and training layouts.
8. The method of claim 7 , wherein the training images are images of one or more reference semiconductor wafers, wherein the training layouts are layouts associated with processing the one or more reference semiconductor wafers.
9. A method, comprising:
training, with a machine learning process, a simulated layout generation system to generate simulated integrated circuit layouts;
providing a test image of a semiconductor wafer to the simulated layout generation system;
generating a simulated integrated circuit layout with the simulated layout generation system;
generating a reference image of a reference semiconductor wafer;
generating a reference layout based on the reference image; and
comparing the simulated integrated circuit layout to a reference integrated circuit layout.
10. The method of claim 9 , further comprising detecting a defect in the semiconductor wafer based on differences between the simulated integrated circuit layout and the reference integrated circuit layout.
11. The method of claim 9 , wherein training the simulated layout generator includes training the simulated layout to generate, for a plurality of training images, simulated integrated circuit layouts that match training integrated circuit layouts.
12. A system, comprising:
a simulated layout generation system configured to:
receive a test image of a semiconductor wafer;
generate a simulated integrated circuit layout based on the test image;
receive a reference image of a reference semiconductor wafer; and
generate a reference layout based on the reference semiconductor wafer; and
a defect detection system configured to compare the simulated integrated circuit layout to a reference integrated circuit layout and to detect a defect in the semiconductor wafer based on a difference between the simulated integrated circuit layout and the reference integrated circuit layout.
13. The system of claim 12 , further comprising an imaging system configured to capture the test image by imaging the semiconductor wafer.
14. The system of claim 13 , wherein the imaging system includes one or more of:
an electron microscope;
a bright field optical imaging system; and
a dark field optical imaging system.
15. The system of claim 12 , wherein the simulated layout generation system includes a deep learning unit configured to learn, via one or more machine learning processes, an algorithm for generating simulated integrated circuit layouts based on test images.
16. The system of claim 15 , further comprising an image processing unit configured to implement the algorithm.
17. The system of claim 16 , wherein the image processing unit is configured to process the test image and generate the simulated integrated circuit layout with the algorithm.
18. The system of claim 17 , wherein the simulated layout generation system includes a training set database including training set data for training the deep learning unit.
19. The system of claim 18 , wherein the training set database includes:
an image database including training images of the training set data; and
a layout database including training layouts of the training set data.
20. The system of claim 19 , wherein the training images are images of one or more reference semiconductor wafers, wherein the training layouts are layouts associated with processing the one or more reference semiconductor wafers.