Fast Lithographic Mask Optimization Considering Process Variation

Su, Yu-Hsuan; Huang, Yu-Chen; Tsai, Liang-Chun; Chang, Yao-Wen; Banerjee, Shayak

doi:10.1109/tcad.2015.2514082

Cited by 40 publications

(15 citation statements)

References 27 publications

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“…Recently, an effective Process Variation Aware OPC algorithm, namely PV-OPC, has been proposed with good results in terms of pattern fidelity under process variations, computational time, and with considering mask notch rule for higher manufacturability through exploiting variational EPE, and adaptive fragmentation [9]. Furthermore, PV-OPC effectively reduces the number of needed simulations.…”

Section: Recent Researchmentioning

confidence: 99%

“…On the other hand, it gets thinner with negative values. Defocus impact causes wafer image to be thinner than its form under nominal focus condition [9]. Thus, for a process window P w , three representative process conditions are defined as follows (illustrated in Figure 4): 3.…”

Section: Representative Lithographic Process Conditionsmentioning

confidence: 99%

“…Resolution enhancement techniques (RETs) aim to improve wafer image quality through manipulating the amplitude and phase of the optical wave to pre-compensate wafer image distortions [8]. Since next-generation lithography (NGL) is still not mature enough, the industry relies heavily on RETs, wherein optical proximity correction (OPC) is dominant, to print sub-16 nm technology nodes in the foreseeable future [9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optical Proximity Correction (OPC) Under Immersion Lithography

Ahmed¹,

Takahashi²,

Kodaman³

2018

Micro/Nanolithography - A Heuristic Aspect on the Enduring Technology

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As advanced technology nodes continue scaling down into sub-16 nm regime, optical microlithography becomes more vulnerable to process variations. As a result, overall lithographic yield continuously degrades. Since next-generation lithography (NGL) is still not mature enough, the industry relies heavily on resolution enhancement techniques (RETs), wherein optical proximity correction (OPC) with 193 nm immersion lithography is dominant in the foreseeable future. However, OPC algorithms are getting more aggressive. Consequently, complex mask solutions are outputted. Furthermore, this results in long computation time along with mask data volume explosion. In this chapter, recent state-of-the-art OPC algorithms are discussed. Thereafter, the performance of a recently published fast OPC methodology-to generate highly manufactured mask solutions with acceptable pattern fidelity under process variations-is verified on the public benchmarks.

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Section: Recent Researchmentioning

confidence: 99%

Section: Representative Lithographic Process Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optical Proximity Correction (OPC) Under Immersion Lithography

Ahmed¹,

Takahashi²,

Kodaman³

2018

Micro/Nanolithography - A Heuristic Aspect on the Enduring Technology

View full text Add to dashboard Cite

show abstract

“…However, the computation time for such an algorithm is expected to dramatically increase for advanced technology nodes, wherein, distortions are widely distributed within the layout region. Under the assumption that intensity follows the normal distribution, Process Variation OPC (PV-OPC) algorithm estimates the intensity within a short computation time [7]. Mask Optimization Solution With Process Window Aware Inverse Correction (MOSAIC) algorithm proposed a relatively fast ILT methodology with some loss of accuracy [22].…”

Section: Previous Workmentioning

confidence: 99%

“…For example, an OPC used in metal layers can run into 3-5 days for realistic industrial cases. Even for simplified unidirectional layers in the poly-silicon, OPC might take 24 hours to find the final mask solution [7]. However, the trade-off between wafer image quality and computation time is often pushed in favor of preserving acceptable image quality with sacrificing the need for shortening the computation time.…”

Section: Introductionmentioning

confidence: 99%

Intensity Difference Map (IDM) Accuracy Analysis for OPC Efficiency Verification and Further Enhancement

Ahmed

Takahashi

Tanaka

et al. 2017

IPSJ Transactions on System LSI Design Methodology

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Optical Proximity Correction (OPC) is still nominated as a main stream in printing Sub-16 nm technology nodes in optical micro-lithography. However, long computation time is required to generate mask solutions with acceptable wafer image quality. Intensity Difference Map (IDM) has been recently proposed as a fast methodology to shorten OPC computation time with preserving acceptable wafer image quality. However, IDM has been evaluated only under a relatively relaxed Edge Placement Error (EPE) constraint of the final mask solution. Such an evaluation does not provide a satisfactory confirmation of the effectiveness of IDM if strict EPE constraints are imposed. In this paper, the accuracy of IDM is deeply analyzed to confirm its validity in terms of wafer image estimation accuracy along with its efficiency in shortening computation time. Thereafter, the stability of IDM accuracy against the increase in pattern area/density is confirmed. Finally, the regions suffering from lack of accuracy are analyzed for further enhancement. Experimental results show that congestion in the mask pattern forms a cardinal source of the lack of accuracy which is compensated through optimized selection of the kernels included in IDM.

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Machine Learning for Mask Synthesis and Verification

Yang

Lin

2022

Machine Learning Applications in Electronic Design Automation

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Fast Lithographic Mask Optimization Considering Process Variation

Cited by 40 publications

References 27 publications

Optical Proximity Correction (OPC) Under Immersion Lithography

Optical Proximity Correction (OPC) Under Immersion Lithography

Intensity Difference Map (IDM) Accuracy Analysis for OPC Efficiency Verification and Further Enhancement

Machine Learning for Mask Synthesis and Verification

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