Mask manufacturing rules are usually determined from assumed or experimentally acquired mask-manufacturing limits. These rules are then applied during resolution enhancement data treatment to guide and/or limit pattern correction strategies. This technique can be highly reactive and may not allow a careful tradeoff between the mask making capability and the end user needs. We have explored techniques to develop mask manufacturability rules in the context of wafer lithography and device needs.
In this paper, we consider methods to improve the capture and usage of mask making information for resolution enhancement by applying a novel test mask and design, which is tied to a process modeling software. Mask manufacturing models are established from the test maks design and these models are applied to generate geometrical rules and continuous models linking the mask making capability to the lithography requirements. The analysis of mask manufacturing constraints is extended into the device domain through yield prediction tools that capture the impact of lithography variability on device performance.
We find techniques allowing a more dynamic generation of relevant mask making constraints that can optimize both yield and cycle time in the resolution ehancement process flow. Toward this, usage cases are highlighted to illustrate the interaction of specific design layouts and our mask manufacturability.