Supreme lithographic performance by simple mask layout based on lithography and layout co-optimization

Tsujita, Koichiro; Arai, Tadashi; Ishii, Hiroyuki; Gyoda, Yuichi; Takahashi, Kazuhiro; Axelrad, V.; Smayling, Michael C.

doi:10.1117/12.878663

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…For the rapid calculation of aerial image intensity, this study adopted the 2D-TCC technique [29], [30], which converts the TCC function in (2) into a W s,t (g u , g v ) function for the approximation of aerial image intensity. Specifically, it fixes the two spatial frequency variables in the TCC function of (2), f u and g v , in (s, t) as (3).…”

Section: Projection Lithograph Modelmentioning

confidence: 99%

Placement of Sub-Resolution Assist Features Based on a Genetic Algorithm

Kan

Huang

et al. 2019

IEEE Access

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Resolution enhancement techniques compatible with an ArF (193 nm) immersion optical lithography system may constitute an effective means of minimizing the size of technology nodes of the dynamic random access memory. This paper investigated one such technique, namely mask optimization (MO), and applied sub-resolution assist features (SRAFs) in the MO to improve the aerial image quality of a target pattern that had undergone optical proximity correction (OPC). This paper first developed an optical model based on the Hopkins model to create an interference map, which was then used to create a cutlevel map. The cut-level map was instrumental in predicting potential SRAF sites and randomly generating SRAFs that would serve as the initial population for a genetic algorithm (GA). Chromosomes were defined as a section map and encoded genes were used to define SRAF and target pattern. Using a GA to identify SRAF geometric measurements and placement was revealed to increase the process window and improve the image performance of the target pattern. This paper used 1D and 2D line/space (L/S) images as the baseline to test the convergence of the proposed method. 2D images were also used to test improvements in aerial image performance. The results indicated that the 1D L/S pattern converged at the 100th iteration. Furthermore, the depths of the focus of the 2D L/S array and 2D contact hole patterns were successfully increased by 113 and 21 nm, respectively. The proposed SRAF method, which integrated the GA and interference map, was able to ensure the diversity of potential SRAF solutions. Moreover, it was able to restrict the SRAF solutions to rectangular structures through the application of mask rules, thereby reducing the cost and improving the feasibility of photomasks. INDEX TERMS Sub-resolution assist feature (SRAF), interference map, genetic algorithm (GA), mask optimization, depth of focus (DOF).

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Section: Projection Lithograph Modelmentioning

confidence: 99%

Placement of Sub-Resolution Assist Features Based on a Genetic Algorithm

Kan

Huang

et al. 2019

IEEE Access

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“…[3,4,5] This is significant since mask data volumes of >500GB per layer are projected for pixelated masks created by complex OPC or inverse lithography; writing times for such masks are nearly prohibitive.…”

mentioning

confidence: 99%

Sub-20nm logic lithography optimization with simple OPC and multiple pitch division

et al. 2012

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The CMOS logic 22nm node is being done with single patterning and a highly regular layout style using Gridded Design Rules (GDR). Smaller nodes will require the same regular layout style but with multiple patterning for critical layers. A line/cut approach is being used to achieve good pattern fidelity and process margin, with extendibility to ~7nm.[1]Design-Source-Mask Optimization (DSMO) has been demonstrated to be effective at the 20nm node.[2] The transition from single-to double-and in some cases triple-patterning was evaluated for different layout styles, with highly regular layouts delaying the need for multiple-patterning compared to complex layouts.To address mask complexity and cost, OPC for the "cut" patterns was studied and relatively simple OPC was found to provide good quality metrics such as MEEF and DOF.[3,4,5] This is significant since mask data volumes of >500GB per layer are projected for pixelated masks created by complex OPC or inverse lithography; writing times for such masks are nearly prohibitive.In this study, we extend the scaling using simplified OPC beyond 20nm in small steps, eventually reaching the 16nm node. The same "cut" pattern is used for each set of simulations, with "x" and "y" locations for the cuts scaled for each step. The test block is a reasonably complex logic function with ~100k gates of combinatorial logic and flip-flops.Experimental demonstration of the cut approach using simplified OPC and conventional illuminators will be presented with comparison to the complex OPC result. MEEF can be measured experimentally. Lines were patterned with 193nm immersion with no complex OPC. The final dimensions were achieved by applying pitch division twice. [6] Using the conditions optimized for the logic block, an SRAM block simulation and experimental results will also be presented.

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A novel OPC method to reduce mask volume with yield-aware dissection

Xie¹,

Wang²,

Zheng³

2013

J. Semicond.

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Growing data volume of masks tremendously increases manufacture cost. The cost increase is partially due to the complicated optical proximity corrections applied on mask design. In this paper, a yield-aware dissection method is presented. Based on the recognition of yield related mask context, the dissection result provides sufficient degrees of freedom to keep fidelity on critical sites while still retaining the frugality of modified designs. Experiments show that the final mask volume using the new method is reduced to about 50% of the conventional method.

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Supreme lithographic performance by simple mask layout based on lithography and layout co-optimization

Cited by 6 publications

References 7 publications

Placement of Sub-Resolution Assist Features Based on a Genetic Algorithm

Placement of Sub-Resolution Assist Features Based on a Genetic Algorithm

Sub-20nm logic lithography optimization with simple OPC and multiple pitch division

A novel OPC method to reduce mask volume with yield-aware dissection

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