Mitigating the Impact of Mask Absorber Error on Lithographic Performance by Lithography System Holistic Optimization

Sheng, Naiyuan; Li, Enze; Sun, Yiyu; Li, Tie; Li, Yanqiu; Wei, Pengzhi; Liu, Lihui

doi:10.3390/app9071275

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…Therefore, to tackle the focus variation, an analytical defocus expansion function was derived to predict the defocus aerial image in an inverse lithography technology (ILT) framework [10], so that a variational lithography model (VLIM) is derived to take into account exposure dose and focus variations [11]. Meanwhile, we previously proposed the source-mask-numerical aperture (NA) co-optimization (SMNO) method to extend the depth of defocus (DOF) by fine-tuning the NA [12,13], but it inevitably sacrificed resolution due to the reduction of NA. In addition, Peng et al [14] also studied SMO methods to improve the pattern fidelity in the case of an assigned defocus plane which operated at 100 nm defocusing, and our subsequent works have drawn on this approach [15,16], but it is hard to ensure global fidelity in different defocus variations.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Defocus Robust Source and Mask Optimization Using Sensitive Penalty

Wei

et al. 2019

Applied Sciences

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The continuous decrease in the size of lithographic technology nodes has led to the development of source and mask optimization (SMO) and also to the control of defocus becoming stringent in the actual lithography process. Due to multi-factor impact, defocusing is always changeable and uncertain in the real exposure process. But conventional SMO assumes the lithography system is ideal, which only compensates the optical proximity effect (OPE) in the best focus plane. Therefore, to solve the inverse lithography problem with more uniformity of pattern in different defocus variations, we proposed a defocus robust SMO (DRSMO) approach that is driven by a defocus sensitivity penalty function for the first time. This multi-objective optimization samples a wide range of defocus disturbances and it can be proceeded by the mini-batch gradient descent (MBGD) algorithm effectively. The simulation results showed that a more robust defocus source and mask can be designed through DRSMO optimization. The defocus sensitivity factor sβ maximally decreased 63.5% compared to conventional SMO, and due to the low error sensitivity and the depth of defocus (DOF), the process window (PW) was further enlarged effectively. Compared to conventional SMO, the exposure latitude (EL) maximally increased from 4.5% to 10.5% and DOF maximally increased 54.5% (EL = 5%), which proved the validity of the DRSMO method in improving the focusing performance.

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Section: Introductionmentioning

confidence: 99%

Multi-Objective Defocus Robust Source and Mask Optimization Using Sensitive Penalty

Wei

et al. 2019

Applied Sciences

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Effective multi-objective inverse lithography technology at full-field and full-chip levels with a hybrid dynamic priority algorithm

Wei¹,

Li²,

Li³

et al. 2023

Opt. Express

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Inverse lithography technology (ILT), such as source mask optimization (SMO), is used to improve lithography performance. Usually, a single objective cost function is selected in ILT, and an optimal structure for one field point is achieved. The optimal structure is not the case for other images at full field points where the aberrations of the lithography system are different, even in high-quality lithography tools. The optimal structure that must match the high-performance images at the full field is urgently required for extreme ultraviolet lithography (EUVL). In contrast, multi-objective optimization algorithms (MOAs) limit the application of multi-objective ILT. Assigning target priority is incomplete in current MOAs, which results in the over-optimization of some targets and under-optimization of others. In this study, multi-objective ILT and a hybrid dynamic priority (HDP) algorithm were investigated and developed. High-performance images with high fidelity and high uniformity were obtained at multi-field and multi-clip areas across the die. A hybrid criterion was developed for the completion and reasonable prioritization of each target to ensure sufficient improvement. Compared to the current MOAs, the uniformity of images at full-field points was improved by up to 31.1% by the HDP algorithm in the case of multi-field wavefront error-aware SMO. The multi-clip source optimization (SO) problem showed the universality of the HDP algorithm to deal with different ILT problems. It acquired higher imaging uniformity than existing MOAs, which indicated that the HDP is more qualified for multi-objective ILT optimization than existing MOAs.

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Mitigating the Impact of Mask Absorber Error on Lithographic Performance by Lithography System Holistic Optimization

Cited by 2 publications

References 27 publications

Multi-Objective Defocus Robust Source and Mask Optimization Using Sensitive Penalty

Multi-Objective Defocus Robust Source and Mask Optimization Using Sensitive Penalty

Effective multi-objective inverse lithography technology at full-field and full-chip levels with a hybrid dynamic priority algorithm

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