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.
In order to resolve the causality dilemma of which comes first, accurate design rules or real designs, this paper presents a flow for exploration of the layout design space to early identify problematic patterns that will negatively affect the yield.
A new random layout generating method called Layout Schema Generator (LSG) is reported in this paper, this method generates realistic design-like layouts without any design rule violation. Lithography simulation is then used on the generated layout to discover the potentially problematic patterns (hotspots). These hotspot patterns are further explored by randomly inducing feature and context variations to these identified hotspots through a flow called Hotspot variation Flow (HSV). Simulation is then performed on these expanded set of layout clips to further identify more problematic patterns.
These patterns are then classified into design forbidden patterns that should be included in the design rule checker and legal patterns that need better handling in the RET recipes and processes.