Researchers have developed a novel deep learning model to predict the full-chip post-Chemical-Mechanical Polishing (CMP) nanotopography with nanometer-scale accuracy. This model combines data from White Light Interferometry (WLI) and Atomic Force Microscopy (AFM) to overcome the limitations of existing Density Step Height (DSH) modeling, which is often slow and resource-intensive. The proposed Convolutional Neural Network (CNN) approach aims to accelerate the layout manufacturability verification process in the Integrated Circuit (IC) industry. AI
影响 This model could accelerate IC design cycles by improving the accuracy and speed of manufacturability verification.
排序理由 This is a research paper detailing a new deep learning model for a specific engineering problem.
- arXiv
- Atomic Force Microscopy
- Convolutional Neural Network
- Integrated Circuit
- White Light Interferometry
- Chemical-Mechanical Polishing
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