Assessing the impact of real world manufacturing lithography variations on post-OPC CD control

Sturtevant, John L.; Word, James; LaCour, Pat; Park, J. W.; Smith, D. A.

doi:10.1117/12.598063

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…There are multiple sources of residual errors in models, and model inaccuracies are only one of several factors which contribute to errors in the final wafer image after mask correction [1]. One significant class of modeling error is related to how the illumination source is represented.…”

Section: Introductionmentioning

confidence: 99%

Study of OPC accuracy by illumination source types

Yang¹,

Park²,

Lee³

et al. 2009

SPIE Proceedings

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The study of OPC (Optical Proximity Correction) model that well predict the wafer result has been researched. As the pattern design shrink down, the need for the CD (Critical Dimension) controllability increased more than before. To achieve these requirements, OPC models must be accurate for full chip process and model inaccuracies are one of several factors which contribute to errors in the final wafer image. For that reason, robust OPC using real lithographic terms was proposed. Real lithographic system is quite different from ideal system that is used for OPC modeling. Until now, this difference was acceptable since pattern size used for OPC model was large, but as device size shrinks, this gap between ideal and real system causes degradation of OPC accuracy. So, various optical parameters such as apodization, laser band width, degree of polarization, illumination are used today in order to compensate for this issue. Especially, major issue in modeling error is related to how the illumination source is used.For this study we assess accuracy of optical model for robust OPC using ideal and actual illumination sources, and test conditions are below. 1) We examined the difference of pupil types to output model respectively.2) A parameterized test pattern layout was used by 1D test pattern types that have various lines and spaces. 3) All models were calculated in automation method so as to exclude the dependency of user skills. 4) OPC accuracies were examined by gate layer patterns on full chip level. The study is performed for 5X~4Xnm nodes lithographic processes. The main focus of the study was on usability of model that is made by measured source data in semiconductor manufacturing. Results clearly showed that the actual source for the optical model has merits and demerits.

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Section: Introductionmentioning

confidence: 99%

Study of OPC accuracy by illumination source types

Yang¹,

Park²,

Lee³

et al. 2009

SPIE Proceedings

View full text Add to dashboard Cite

show abstract

“…Their analysis is based on OPC with the nominal process. It is expected that the difference in consideration of process variations would be even more [24]. Statistical simulation techniques are demonstrated to map the lithography variability to CD or chip timing [25,26].…”

Section: Introductionmentioning

confidence: 99%

True process variation aware optical proximity correction with variational lithography modeling and model calibration

Shi

Pan

2007

J. Micro/Nanolith. MEMS MOEMS

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Optical proximity correction (OPC) is one of the most widely used Resolution Enhancement Techniques (RET) in nanometer designs to improve subwavelength printability. Conventional model-based OPC assumes nominal process conditions without considering process variations because of the lack of variational lithography models. A simple method to improve OPC results under process variations is to sample multiple process conditions across the process window, which requires long runtime. We derive a variational lithography model (VLIM) which can simulate across the process window without much runtime overhead compared to the conventional lithography models. To match the model to experimental data, we demonstrate VLIM calibration method. The calibrated model has accuracy comparable to non-variational models, but it has the advantage of taking process variations into consideration. We introduce the variational edge placement error (V-EPE) metrics based on the model, a natural extension to the edge placement error (EPE) used in conventional OPC algorithms. A true process-variation aware OPC (PV-OPC) framework is proposed using the V-EPE metric. Due to the analytical nature of VLIM, our PV-OPC is only about 2-3× slower than the conventional OPC, but it explicitly considers the two main sources of process variations (exposure dose and focus variations) during OPC. Thus our post PV-OPC results are much more robust than the conventional OPC ones, in terms of both geometric printability and electrical characterization under process variations.

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“…The analysis of [24] is based on OPC with the nominal process. It is expected that the difference with consideration of process variations would be even more [20]. Statistical simulation techniques are demonstrated to map the lithography variability to CD or chip timing [2,17].…”

Section: Introductionmentioning

confidence: 99%

Process variation aware OPC with variational lithography modeling

Yu¹,

Shi²,

Jian³

2006

2006 43rd ACM/IEEE Design Automation Conference

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Optical proximity correction (OPC) is one of the most widely used resolution enhancement techniques (RET) in nanometer designs to improve subwavelength printability. Conventional model-based OPC assumes nominal process parameters without considering process variations, due to prohibitive runtimes of lithography simulations across process windows. This is the first paper to propose a true process-variation aware OPC (PV-OPC) framework. It is enabled by the variational lithography modeling and guided by the variational edge placement error (V-EPE) metrics. Due to the analytical nature of our models, our PV-OPC is only about 2-3× slower than the conventional OPC, but it explicitly considers the two main sources of process variations (dosage and focus) during OPC. Thus our post PV-OPC results are much more robust than the conventional OPC ones, in terms of both geometric printability and electrical characterization under process variations.

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Assessing the impact of real world manufacturing lithography variations on post-OPC CD control

Cited by 5 publications

References 18 publications

Study of OPC accuracy by illumination source types

Study of OPC accuracy by illumination source types

True process variation aware optical proximity correction with variational lithography modeling and model calibration

Process variation aware OPC with variational lithography modeling

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