TY - JOUR
T1 - Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage
AU - Wang, Jiashuo
AU - Dong, Lisong
AU - Su, Xiaojing
AU - Su, Yajuan
AU - Ma, Xu
AU - Wei, Yayi
N1 - Publisher Copyright:
© 2023 Society of Photo-Optical Instrumentation Engineers (SPIE).
PY - 2023/10/1
Y1 - 2023/10/1
N2 - 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.
AB - 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.
KW - computational lithography
KW - critical patterns selection
KW - resist model calibration
KW - spectrum coverage
UR - http://www.scopus.com/inward/record.url?scp=85181469754&partnerID=8YFLogxK
U2 - 10.1117/1.JMM.22.4.043201
DO - 10.1117/1.JMM.22.4.043201
M3 - Article
AN - SCOPUS:85181469754
SN - 1932-5150
VL - 22
JO - Journal of Micro/ Nanolithography, MEMS, and MOEMS
JF - Journal of Micro/ Nanolithography, MEMS, and MOEMS
IS - 4
M1 - 043201
ER -