Automatic assist feature placement optimization based on process-variability reduction

Abstract

To maximize the process window and CD control of main features, sizing and placement rules for sub-resolution assist features (SRAF) need to be optimized, subject to the constraint that the SRAFs not print through the process window. With continuously shrinking target dimensions, generation of traditional rule-based SRAFs is becoming an expensive process in terms of time, cost and complexity. This has created an interest in other rule optimization methodologies, such as image contrast and other edge- and image-based objective functions. In this paper, we propose using an automated model-based flow to obtain the optimal SRAF insertion rules for a design and reduce the time and effort required to define the best rules. In this automated flow, SRAF placement is optimized by iteratively generating the space-width rules and assessing their performance against process variability metrics. Multiple metrics are used in the flow. Process variability (PV) band thickness is a good indicator of the process window enhancement. Depth of focus (DOF), the total range of focus that can be tolerated, is also a highly descriptive metric for the effectiveness of the sizing and placement rules generated. Finally, scatter bar (SB) printing margin calculations assess the allowed exposure range that prevents scatter bars from printing on the wafer.