Correlation analysis: a fast and reliable method for a better understanding of simulation models in optical lithography

Tollkuhn, Bernd; Heubner, A.; Elian, Klaus; Ruppenstein, B.; Erdmann, Andreas

doi:10.1117/12.599390

Cited by 3 publications

(6 citation statements)

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“…Consideration of different ranges of values can lead to deviations from the presented results. 36 Nevertheless, the observed tendencies especially for the significant impact of the development critical value on LWR are observed for all reasonable choices of parameters ranges.…”

Section: Results Of the Analysismentioning

confidence: 89%

“…To decorrelate the combined impacts of the parameters on the lithography metrics, we compute the semipartial correlation coefficients. 36 To consider the monotonic, but non-linear relation between some of the parameters and the lithography metrics, Spearman's rank correlation coefficient is computed instead of Pearson's linear correlation coefficients. To address both non-linear dependencies and decorrelate the impact of the photoresist parameters, we calculate semipartial rank correlation coefficients (SRCCs).…”

Section: Methodsmentioning

confidence: 99%

“…This section studies the impact of the parameters of the implemented model on important lithography metrics CD, LWR, dose-to-size, and exposure latitude. To perform a qualitative analysis of observed dependencies and to derive general tendencies, we extend previously published work 36 on the application of correlation analysis (CA) for photoresists parameters. The generation of appropriate datasets for CA requires a preprocessing to provide an efficient sampling of the data space and to avoid defects in the simulated photoresist profiles.…”

Section: Relation Between Photoresist Parameters and The Lithography mentioning

confidence: 99%

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Stochastic simulation and calibration of organometallic photoresists for extreme ultraviolet lithography

Belete

Bisschop

Welling

et al. 2021

J. Micro/Nanopattern. Mats. Metro.

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Organometallic photoresists are being pursued as an alternative photoresist material to push the current extreme ultraviolet lithography (EUVL) to the next generation of high-NA EUVL. In order to improve the photoresist performance, an understanding of the photoresist's response to different process conditions is required. In this endeavor, a stochastic development model is implemented, integrated into full photoresist process steps, and applied for photoresist performance investigations. The model is applied to Inpria-YA photoresist, which works mainly by the process of aggregation. Previously published modeling approaches for metal-organic photoresists assume that the development characteristics of these materials depend only on the size of the created oxo-clusters. In contrast to that, we propose a modeling approach that provides a more detailed description of the interaction among the developer, ligands, and oxo-bonds. Further, the calibration procedures conducted to extract the model parameters to match experimental data are discussed. The model approximated the experimental data with CD RMSE and LWR RMSE of 0.60 and 0.40 nm, respectively. We also investigated the impact of photoresist parameters on the process metrics, line width roughness (LWR), critical dimension (CD), doseto-size (DtS), and exposure latitude (EL) with the calibrated model. The investigation shows that details of the interaction of photoresist and developer, especially, the so-called development critical value, have a significant impact on the LWR and DtS. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Results Of the Analysismentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Section: Relation Between Photoresist Parameters and The Lithography mentioning

confidence: 99%

See 1 more Smart Citation

Stochastic simulation and calibration of organometallic photoresists for extreme ultraviolet lithography

Belete

Bisschop

Welling

et al. 2021

J. Micro/Nanopattern. Mats. Metro.

Self Cite

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“…There are dozens of CAR parameters in exposure, PEB, and development process that determine the final CAR profile. The research from Tollkuhn et al 15 . found that all of these parameters had different degrees of influence on the profile.…”

Section: Introductionmentioning

confidence: 99%

“…It is noted that the optimization strategies based on univariate analysis may be vulnerable to the fluctuation of other CAR parameters, resulting in the instability of CAR formulation and the degeneration of the CAR profile 15 . The research from Tollkuhn et al 15 .…”

Section: Introductionmentioning

confidence: 99%

Optimization of chemically amplified resist formulation based on simple random sampling and kernel density estimation

Kong

Dong

et al. 2023

J. Micro/Nanopattern. Mats. Metro.

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Formulation optimization plays an important role in the research and development of chemically amplified resist (CAR). However, the CAR profile after development process is influenced by multiple resist parameters and process conditions, so it is hard to determine the optimal CAR formulation in the multivariate problem. An optimization method for the CAR formulation is developed. The simple random sampling is applied to each CAR parameter's value range independently, and the combinations of these samples from different parameters are used in the simulation of lithography profiles. Kernel density estimation is applied to analyze the simulation results. Then the CAR formulation is optimized based on the probability density distribution from the analysis results. The verification results show that the proposed optimization method can greatly improve the stability of the CAR formulation and thus generating acceptable critical features' sizes of the CAR profile.

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Analysis on the influence of several parameters in physical resist models

Wang

Kong

Dong

et al. 2021

2021 International Workshop on Advanced Patterning Solutions (IWAPS)

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Correlation analysis: a fast and reliable method for a better understanding of simulation models in optical lithography

Cited by 3 publications

References 0 publications

Stochastic simulation and calibration of organometallic photoresists for extreme ultraviolet lithography

Stochastic simulation and calibration of organometallic photoresists for extreme ultraviolet lithography

Optimization of chemically amplified resist formulation based on simple random sampling and kernel density estimation

Analysis on the influence of several parameters in physical resist models

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