Dose-modulation-induced mask CD error on simultaneous correction of fogging and loading effect

Lee, Ho‐June; Yang, Seung-Hune; Park, Jin‐Hong; Moon, Seong-Yong; Choi, Seong-Woon; Sohn, Jung Min

doi:10.1117/12.518283

Cited by 2 publications

(5 citation statements)

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“…The long-range mask CD uniformity errors include the residual fogging effect in electron beam lithography, resist develop and pattern etch loading [6,11,12]. These errors are usually described using a density loading model that involves a convolution of the pattern density with a Gaussian point spread function.…”

Section: Long-range Calibrationmentioning

confidence: 99%

“…The most significant contribution to long-range mask CD errors can be expressed as process non-uniformity and pattern density loading effects [6,7].…”

Section: Modeling Approachmentioning

confidence: 99%

“…Proximity effects having a range of influence from zero to few micrometers and long-range effects having a range of influence from tens of micrometers to tens of millimeters are discussed here. The intermediate mid-range effects are assumed to be corrected via compensation of the electron beam lithography tools [6,7,11] and are not considered here. Furthermore, interdependencies between the proximity, mid-range, and long-range errors are assumed to be negligible as discussed in the introduction.…”

Section: Modeling Approachmentioning

confidence: 99%

“…Past efforts included pattern data and dosebased correction techniques for the etch effects. It was demonstrated that etch loading effects can be included in the electron beam proximity effect correction through tuning of the exposure ratio of forward and back scattered electrons in the correction function [6]. The correction of etch loading through a dose adjustment was also demonstrated [7].…”

Section: Introductionmentioning

confidence: 97%

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Advanced mask process modeling for 45-nm and 32-nm nodes

Tejnil

Sahouria

et al. 2008

Optical Microlithography XXI

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As tolerance requirements for the lithography process continue to shrink with each new technology node, the contributions of all process sequence steps to the critical dimension error budgets are being closely examined, including wafer exposure, resist processing, pattern etch, as well as the photomask process employed during the wafer exposure. Along with efforts to improve the mask manufacturing processes, the elimination of residual mask errors via pattern correction has gained renewed attention. The portfolio of correction tools for mask process effects is derived from well established techniques commonly used in optical proximity correction and in electron beam proximity effect compensation. The process component that is not well captured in the correction methods deployed in mask manufacturing today is etch. A mask process model to describe the process behavior and to capture the physical effects leading to deviation of the critical dimension from the target value represents the key component of model-based correction and verification. This paper presents the flow for generating mask process models that describe both shortrange and long-range mask process effects, including proximity loading effects from etching, pattern density loading effects, and across-mask process non-uniformity. The flow is illustrated with measurement data from real test masks. Application of models for both mask process correction and verification is discussed.

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Section: Long-range Calibrationmentioning

confidence: 99%

“…The most significant contribution to long-range mask CD errors can be expressed as process non-uniformity and pattern density loading effects [6,7].…”

Section: Modeling Approachmentioning

confidence: 99%

Section: Modeling Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

See 2 more Smart Citations

Advanced mask process modeling for 45-nm and 32-nm nodes

Tejnil

Sahouria

et al. 2008

Optical Microlithography XXI

View full text Add to dashboard Cite

show abstract

“…Past efforts included pattern data and dose-based correction techniques for the etch effects. It was demonstrated that etch loading effects can be included in the electron beam proximity effect correction through tuning of the exposure ratio of forward and back scattered electrons in the correction function [11]. The correction of etch loading through a dose adjustment was also demonstrated [12].…”

Section: Introductionmentioning

confidence: 97%

Model based mask process correction and verification for advanced process nodes

2009

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The extension of optical lithography at 193nm wavelength to the 32nm node and beyond drives advanced resolution enhancement techniques that impose even tighter tolerance requirements on wafer lithography and etch as well as on mask manufacturing. The presence of residual errors in photomasks and the limitations of capturing those in process models for the wafer lithography have triggered development work for separately describing and correcting mask manufacturing effects. Long range effects -uniformity and pattern loading driven -and short range effects -proximity and linearity -contribute to the observed signatures. The dominating source of the short range errors is the etch process and hence it was captured with a variable etch bias model in the past [1]. The paper will discuss limitations and possible extensions to the approach for improved accuracy. The insertion of mask process correction into a post tapeout flow imposes strict requirements for runtime and data integrity. The paper describes a comprehensive approach for mask process correction including calibration and model building, model verification, mask data correction and mask data verification. Experimental data on runtime performance is presented. Flow scenarios as well as other applications of mask process correction for gaining operational efficiency in both tapeout and mask manufacturing are discussed.

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Dose-modulation-induced mask CD error on simultaneous correction of fogging and loading effect

Cited by 2 publications

References 0 publications

Advanced mask process modeling for 45-nm and 32-nm nodes

Advanced mask process modeling for 45-nm and 32-nm nodes

Model based mask process correction and verification for advanced process nodes

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