This paper presents a system for performing mask error correction on both Manhattan and curvilinear shapes. On the Manhattan shapes, the correction may move segments (dissected edges), and on the curvilinear shapes, the correction may move vertices. The segment movement preserves the Manhattan style of the original shapes. Optionally, the vertex movement may be applied on the Manhattan shapes and the corrected results change to be in the curvilinear style. The results of mask error correction on the post-OPC mask of a logic layout will be reported. Dissection and target-point placement work differently between Manhattan and curvilinear shapes. We will analyze the quality and demonstrate optimization of the mask error correction strategies for input mask data consisting of both Manhattan and curvilinear shapes.
The edge-based optical proximity correction (OPC) has been serving the industry for more than 20 years with few changes the mask geometry. In the past 10 years, ILT pioneers created the curvilinear mask using alternate algorithms. The two approaches differ so much that the experiences in conventional OPC do not easily translate to the use of ILT, and vice versa. We report a new approach to curvilinear masks that follows the conventional OPC workflow. It creates and manipulates the curvilinear shapes by generalizing the edge-based OPC to vertices. Conventional OPC techniques, including dissection, classification, target point placement, etc., remain as central roles. Full-chip correction results are included to demonstrate the good performance of the curvilinear mask for both contact and line/space patterns. The analysis of critical patterns shows that the curvilinear OPC lifts the mask rule check restriction to the mask shape that limits Manhattan OPC. The turnaround time of creating the curvilinear mask is around two times than that of the Manhattan mask.
The edge-based OPC has been serving the industry for more than 20 years with few changes in the way to alter the mask. In the past 10 years, ILT pioneers in the creation of the curvilinear mask using alternate algorithms. The two approaches differ so much that the experiences in conventional OPC do not easily translate to the use of ILT and vice versa. In this paper, we report a new system for curvilinear OPC built on top of the conventional OPC workflow without being limited to moving edges. It creates and manipulates the curvilinear shapes by generalizing the edge-based OPC to vertices. Conventional OPC techniques, including dissection, classification, target point placement, etc., keep playing central roles. Full-chip correction results demonstrate the good performance of the curvilinear mask for both contact and line/space patterns. The runtime cost of adoption is reported.
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