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To mitigate this risk, we propose an automated flow that is capable of producing large-scale realistic design content, and then optimizing the OPC recipe parameters to maximize the process window for this layout. The flow was tested with a triple-patterned 10nm node 1X metal level. First, design-rule clean layouts were produced with a tool called Layout Schema Generator (LSG). Next, the OPC recipe was optimized on these layouts, with a resulting reduction in the number of hotspots. For experimental validation, the layouts were placed on a test mask, and the predicted hotspots were compared with hardware data.
In this paper we will present an efficient way to classify and disposition EUV mask defects through a new algorithm developed to classify defects located on EUV photomasks. By processing scanning electronmicroscopy images (SEM) of small regions of a photomask, we extract highdimensional local features Histograms of Oriented Gradients (HOG). Local features represent image contents compactly for detection or classification, without requiring image segmentation. Using these HOGs, a supervised classification method is applied which allows differentiating between nondefective and defective images. In the new approach we have developed a superior method of detection and classification of defects, using mask and supporting mask printed data from several metallization masks. We will demonstrate that use of the HOG method allows realtime identification of defects on EUV masks regardless of geometry or construct.
The defects identified by this classifier are further divided into subclasses for mask defect disposition: foreign material, foreign material from previous step, and topological defects. The goal of disposition is to categorize on the images into subcategories and provide recommendation of prescriptive actions to avoid impact on the wafer yield.
Repeated measurements of the same structure at separate locations are used to extract SEM contours across several instances. The average measurements from these locations can then be used for OPC model calibration. Using 14nm process data, it is shown that including more contours in hybrid OPC model calibration leads to improved model verification. Within an appropriate range, higher weight on the contour patterns leads to improved model verification on measurement sites unseen by the calibration set. Calibrating a model with fewer contour structures, but at higher weight shows improvement over standard CD only model calibration.
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