Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2017 · 14 citations · 12 references
ArchitectureDesignManufacturing EngineeringDesign AutomationDesign OptimizationManufacturing ProcessesDesign For ManufacturingDesign ProcessDesign SynthesisPattern GenerationPhysical DesignAutomated Design Space ExplorationComputer-aided Design AutomationHotspot DetectionLayout GenerationManufacturingProcess Window DevelopmentRecipe FormulationScope
State-of-the-art OPC recipes for production semiconductor manufacturing are fine-tuned, often artfully crafted parameter sets are designed to achieve design fidelity and maximum process window across the enormous variety of patterns in a given design level. In the typical technology lifecycle, the process for creating a recipe is iterative. In the initial stages, very little to no “real” design content is available for testing. Therefore, an engineer may start with the recipe from a previous node; adjust it based on known ground rules and a few test patterns and/or scaled designs, and then refine it based on hardware results. As the technology matures, more design content becomes available to refine the recipe, but it becomes more difficult to make major changes without significantly impacting the overall technology scope and schedule. The dearth of early design information is a major risk factor: unforeseen patterning difficulties (e.g. due to holes in design rules) are costly when caught late. 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.
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Tejas Jhaveri, Vyacheslav Rovner, Lars W. Liebmann et al. · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2010 · 98 citations
Engineering, Computer Engineering, Electrical Engineering +17
A little light magic [optical lithography]
F. M. Schellenberg · IEEE Spectrum · 2003 · 44 citations