OPC in memory-device patterns using boundary layer model for 3-dimensional mask topographic effect

Abstract

Boundary Layer Model (BLM) is applied to OPC for typical memory-device patterning processes for 3D mask topographic effect. It is observed that this BLM successfully accounts for the 3D mask effect as reducing OPC model error down to sub-50 nm node. BLM improves OPC-modeling accuracy depending on specific process conditions such as mask type and pattern geometry. Potential limit of BLM, i.e., how accurately BLM could predict the 3D mask effect is also investigated with respect to CD change: BLM also compared with rigorous simulation for various features and a good match is obtained as small as below 0.5 nm. Some practical issue in OPC modeling such as determination of the phase of boundary layer is addressed, which can be critical for prediction of defocus behavior.

Fast synthesis of topographic mask effects based on rigorous solutions

“…1,2,11 The optimization generally starts with values extracted from rigorous Maxwell solutions of typical layout structures in a small field. 12 It provokes a question: can the prior knowledge of rigorous simulations be exploited in an more efficient and user-friendly way to speed up the topographic mask modeling on full-chip scale?…”

The MEEF NILS divergence for low k1 lithography

“…Several recent publications characterize low k1 patterning of various mask stack and materials [1][2][3][4][5] and in at least some cases 6 simultaneously considered the effect of biasing. Those works generally evaluate contrast, NILS or exposure latitude (all three are proportional to each other) for one-dimensional features as the initial metric for comparison between different mask stacks.…”