Characterization of photoresist and simulation of a developed resist profile for the fabrication of gray-scale diffractive optic elements

Park, Jong Rak; Sierchio, Justin M.; Zaverton, Melissa; Kim, Young‐Sik; Milster, Tomas D.

doi:10.1117/1.oe.51.2.023401

Cited by 1 publication

(2 citation statements)

References 22 publications

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“…Twenty-five parameters are used to describe the exposure, post-exposure bake, and development processes. They are used in the calibration of rigorous resist models 40 – 42 The parameters utilized for calibrating the resist model in this paper are listed in Table 6.…”

Section: Results and Analysis Of Resist Model Verificationmentioning

confidence: 99%

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Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage

Wang,

Dong,

et al. 2023

J. Micro/Nanopattern. Mats. Metro.

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Background: The resist model is a significant element of computational lithography. Accurate calibration of the resist model is essential to obtain predictive results that closely match the exposure results on wafers. The trade-off between model accuracy and runtime is a challenging task. The selection of critical patterns used in model calibration affects these two metrics directly.Aim: Having a dependable method for choosing critical patterns during resist model calibration is essential for lithography engineers with diverse professional backgrounds. Equally important is the ability to decrease runtime while maintaining the precision of calibrated resist models. To address these concerns, we present an approach for selecting critical patterns utilized in resist model calibration.Approach: Since the spectrum carries pattern information, critical patterns are selected based on the coverage of the spectrum in the frequency domain. The spectrum coverage (SCO) of each pattern in the entire test pattern set is calculated according to the frequency and amplitude of all the spectra. Combinations of critical patterns are selected based on their SCO values. The optimal combinations include the most types of spectra and aim to adapt the calibrated model for broad applicability, encompassing both universal and unique patterns. Results:The model verification results are compared with the experience-based methods, which select critical patterns based on the pitch-to-CD ratio. The accuracy and effectiveness of the proposed methodology have been demonstrated through experimental results. Compared with experience-based methods that only have dense and isolated critical patterns, our proposed method has a 9.8% increase in accuracy and a 35% decrease in runtime. Even compared with experience-based methods that include forbidden pitches, our method still achieves a 6.4% increase in accuracy without increasing runtime.Conclusions: In summary, the suggested approach for selecting critical patterns based on SCO surpasses the experience-based methods in terms of both accuracy and efficiency. It can significantly shorten the modeling cycle of resists.

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Section: Results and Analysis Of Resist Model Verificationmentioning

confidence: 99%

“…They are used in the calibration of rigorous resist models. [40][41][42] The parameters utilized for calibrating the resist model in this paper are listed in Table 6.…”

Section: Calibration Parameters Of Resist Modelmentioning

confidence: 99%

Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage

Wang,

Dong,

et al. 2023

J. Micro/Nanopattern. Mats. Metro.

View full text Add to dashboard Cite

show abstract

Characterization of photoresist and simulation of a developed resist profile for the fabrication of gray-scale diffractive optic elements

Cited by 1 publication

References 22 publications

Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage

Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage

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