Model-based dummy feature placement for oxide chemical-mechanical polishing manufacturability

Abstract

Chemical-mechanical polishing (CMP) is an enabling technique used in deep-submicron VLSI manufacturing to achieve uniformity in long range oxide planarization [1]. Post-CMP oxide topography is highly related to local spatial pattern density in layout. To change local pattern density, and thus ensure post-CMP planarization, dummy features are placed in layout. Based on models that accurately describe the relation between local pattern density and post-CMP planarization [7; 5; 9], a two-step procedure of global density assignment followed by local insertion is proposed to solve the dummy feature placement problem in the fixeddissection regime with both single-layer and multiple-layer considerations. Two experiments, conducted with real design data, gave excellent results by reducing post-CMP topography variation from 767Å to 152Å in the single-layer formulation and by avoiding cumulative effect in the multiple-layer formulation. The result from single-layer formulation compares very favorably both to the rulebased approach widely used in industry and to the algorithm in [3]. The multiple-layer formulation has no previously published work.

Physical design techniques for optimizing RTA-induced variations

“…Therefore, in a region with very large STI density, dummy polysilicon fills may be inserted to block off some part of the STI region, in order to bring the local STI density within the desired limit. The problem with rule-based dummy filling is that the limit for the allowable density is typically quite large, so that the prescribed fill density must go through trial-and-error for every design; sometimes, no single value works [13]. Compared to the rule-based approach, model-based dummy polysilicon filling is based on the effective STI density, a more complex metric than the local STI density used in the rule-based method.…”

“…Since the problem structure is somewhat similar to that of oxide CMP fill, our method is based on an adaptation of the oxide CMP fill solution in [13]. The approach in [13] has two steps: global dummy fill assignment using LP, followed by local dummy fill insertion where the details of the fills at the local level are determined.…”

“…The approach in [13] has two steps: global dummy fill assignment using LP, followed by local dummy fill insertion where the details of the fills at the local level are determined. In this work, we focus on the first step, since the methods for detailed local dummy fill insertion are very similar to that in CMP dummy fill, and the reader is referred to [13] for details on issues such as the determination of the shapes and locations of dummy fills.…”

“…Compared to the method in [13], additional constraints to control the gradient of the effective STI density are introduced.…”

“…We show that a linear programming (LP) method, similar to that in [13], can be used to solve the dummy polysilicon filling problem. Our experimental results demonstrate that the proposed dummy fill algorithm can reduce the RTA variations to negligible amounts.…”