MEEF-based correction to achieve OPC convergence of low-k1 lithography with strong OAI

Choi, Soo-Han; Je, A-Young; Hong, Ji-Suk; Yoo, Moon-Hyun; Kong, Jeong-Taek

doi:10.1117/12.656894

Cited by 9 publications

(5 citation statements)

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“…The MEEF values for different layers are shown in Table XII. These values are larger than previously reported data from the industry [31]- [33]. This is due to the lack of a well-optimized optical correction recipe that should include SRAF insertion and retargeting.…”

Section: Accounting For Nonunity Meefcontrasting

confidence: 51%

Design-Aware Mask Inspection

Kagalwalla

Gupta

Progler

et al. 2012

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Abstract-Mask inspection has become a major bottleneck in the manufacturing flow taking up as much as 40% of the total mask manufacturing time. In this paper, we explore techniques to improve the reticle inspection flow by increasing its design awareness. We develop an algorithm to locate nonfunctional features in a postoptical proximity correction layout without using any design information. Using this, and the timing information of the design (if available), the smallest defect size that could cause the design to fail is assigned to each reticle feature. The criticality of various reticle features is then used to partition the reticle such that each partition is inspected at a different pixel size and sensitivity so that the false and nuisance defect count is reduced without missing any critical defect. We also develop an analytical model to estimate the false and nuisance defect count. Using those models, our simulation results show that this designaware mask inspection can reduce the false and nuisance defect count for a critical polysilicon layer from 80 defects down to 49 defects, leading to substantial reduction in defect review load. We also develop a model to estimate first pass yield (FPY) and show that our method can improve the FPY for a polysilicon layer from 11% to 30%. Apart from the polysilicon layer, the potential benefit of this approach is analyzed for active, contact and all the metal/via layers.Index Terms-Computer-aided design (CAD), design for manufacturability (DFM), mask inspection, mask manufacturing, reticle, semiconductor manufacturing.

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Section: Accounting For Nonunity Meefcontrasting

confidence: 51%

Design-Aware Mask Inspection

Kagalwalla

Gupta

Progler

et al. 2012

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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“…The mask error enhancement factor (MEEF) translates resist bias to amount of bias on the mask (Eq. 8) 8 . However, the MEEF is dependent on proximity effects and feature sizes.…”

Section: Electrically Driven Opc: Algorithmmentioning

confidence: 98%

“…It has been recently demonstrated that the current density across the width of the transistor is not uniform 8 . A variety of edge effects lead to current density at the edges being different from the bulk.…”

Section: Model For Contour-based Current Calculationmentioning

confidence: 99%

Electrically driven optical proximity correction

Banerjee¹,

Elakkumanan²,

Liebmann³

et al. 2008

SPIE Proceedings

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Existing optical proximity correction tools aim at minimizing edge placement errors (EPE) due to the optical and resist process by moving mask edges. However, in low-k1 lithography, especially at 45nm and beyond, printing perfect polygons is practically impossible to achieve in addition to incurring prohibitively high mask complexity and cost. Given the impossibility of perfect printing, we argue that aiming to reduce the error of electrical discrepancy between the ideal and the printed contours is a more reasonable strategy. In fact, we show that contours with non-minimal EPE may result in closer match to the desired electrical performance.Towards achieving this objective, we developed a new electrically driven OPC (ED-OPC) algorithm. The tool combines lithography simulation with an accurate contour-based model of shape electrical behavior to predict the on/off current through a transistor gate. The algorithm then guides edge movements to minimize the error in current, rather than in edge placement, between current values for printed and target shapes. The results on industrial 45nm SOI layouts using high-NA immersion lithography models show up to a 5% improvement in accuracy of timing over conventional OPC, while at the same time showing up to 50% reduction in mask complexity for gate regions. The results confirm that better timing accuracy can be achieved despite larger edge placement error.

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“…Notable variations of this simple schema, which address feedback non-localities, have recently been introduced in [2][3][4], including Matrix OPC, to improve convergence or deal with double exposure processes.…”

Section: L)mentioning

confidence: 99%

Extreme mask corrections: technology and benefits

Granik

Cobb

Медведев

2008

Optical Microlithography XXI

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We establish criteria to recognize extreme OPC corrections and discuss their difference from the traditional corrections. Then we present new proximity correction methods for rigorous bi-and tri-tone mask optimization that cast problem as a constraint minimization over the space of piecewise constant or continuous functions. The primary optimization objective is stated as a contour integral over the target. The constraints on image amplitude form convex functionals for dark areas and non-convex functionals for bright areas. A Lagrangian of this constrained problem is minimized. This delivers extreme, aggressive mask corrections, which are not confined by the fragmentation schema or the orientation of its sites. We analyze performance of these corrections under challenging process conditions and evaluate fidelity benefits.

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MEEF-based correction to achieve OPC convergence of low-k1 lithography with strong OAI

Cited by 9 publications

References 0 publications

Design-Aware Mask Inspection

Design-Aware Mask Inspection

Electrically driven optical proximity correction

Extreme mask corrections: technology and benefits

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