Dr. Yiqiong Zhao Profile

Dr. Yiqiong Zhao

Product Marketing Mgr at ASML

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Author

Publications (15)

Proceedings Article | 28 April 2023 Presentation + Paper

A holistic approach to model-based stochastic-aware computational lithography

ChangAn Wang, Yongfa Fan, Mu Feng, Qian Xie, Jazer Wang, Chris Kaplan, Michael Crouse, Xiaoyang Li, Stephen Hsu, Peigen Cao, Yi-Hsing Peng, Stephen Chang, Jun Ye, Youping Zhang, Bin Cheng, Ken Yang, Leiwu Zheng, Jen-Shiang Wang, Austin Peng, Li-Hao Yeh, Cuiping Zhang, Rafael Howell, Alexander Tan, Yiqiong Zhao, Jun Lang, Xiaolong Zhang

Proceedings Volume 12494, 124940B (2023) https://doi.org/10.1117/12.2658508

KEYWORDS: Stochastic processes, Data modeling, Optical proximity correction, Line width roughness, Source mask optimization, Computational lithography, Semiconducting wafers, Modeling, Performance modeling, Photons

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Proceedings Article | 22 February 2021 Presentation + Paper

Stochastic defect criticality prediction enabled by physical stochastic modeling and massive metrology

ChangAn Wang, Peigen Cao, Maxence Delorme, Jen-Yi Wuu, Jiyou Fu, Fuming Wang, Bob Lin, Yiqiong Zhao, Yi-Hsing Peng, Yongfa Fan, Mu Feng, Bin Cheng, Jen-Shiang Wang, Mark Simmoms, Stefan Hunsche, Oliver Patterson, Kuo-Feng Pao, Abdalmohsen Elmalk, Kevin Gao, Ruochong Fei, Xuefeng Zeng, Xiaolong Zhang

Proceedings Volume 11609, 1160916 (2021) https://doi.org/10.1117/12.2584767

KEYWORDS: Stochastic processes, Pattern recognition, Semiconducting wafers, Wafer inspection, Inspection, Defect detection, Metrology, Failure analysis, Data modeling, Calibration

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Proceedings Article | 22 February 2021 Poster + Paper

Enhancing model accuracy and calibration efficiency with image-based pattern selection using machine learning techniques

Ren-Cheng Sun, Dae-Kwon Kang, Chester Jia, Meng Liu, De-Bao Shao, Young-Seok Kim, Jangho Shin, Mark Simmons, Qian Zhao, Mu Feng, Yiqiong Zhao, Shibing Wang, Sungho Kim, Sungwoo Ko, Shinyoung Kim, Jaeseung Choi, Chanha Park

Proceedings Volume 11613, 116130Y (2021) https://doi.org/10.1117/12.2584692

KEYWORDS: Calibration, Machine learning, Signal processing, Physics, Optical proximity correction, Metrology, Lithography, Computational lithography

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Proceedings Article | 23 March 2020 Presentation + Paper

Accurate etch modeling with massive metrology and deep-learning technology

Yifei Lu, Yuhang Zhao, Ming Li, Wei Yuan, Xiang Peng, Hongmei Hu, Shuxin Yao, Zhunhua Liu, Yu Tian, Ying Gao, Bingyang Pan, Weijun Wang, Chunyan Yi, Jinze Wang, Qian Xie, Xichen Sheng, Ying-chen Wu, Guanyong Yan, Yanjun Xiao, Liang Liu, Liang Ji, Qian Zhao, Yongfa Fan, Yiqiong Zhao, Mu Feng, Yueliang Yao, Terrance Yang, Jun Lang

Proceedings Volume 11327, 113270B (2020) https://doi.org/10.1117/12.2552001

KEYWORDS: Etching, Metrology, Calibration, Scanning electron microscopy, Data modeling, Optical proximity correction, Critical dimension metrology, Performance modeling, Image processing, Semiconducting wafers

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The semiconductor design node shrinking requires tighter edge placement errors (EPE) budget. OPC error, as one major contributor of EPE budget, need to be reduced with better OPC model accuracy. In addition, the CD (Critical Dimension) shrinkage in advanced node heavily relies on the etch process. Therefore AEI (After Etch Inspection) metrology and modeling are important to provide accurate pattern correction and optimization. For nodes under 14nm, the etch bias (i.e. the bias between ADI (After Development Inspection) CD and AEI CD) could be -10 nm ~ -50 nm, with a strong loading and aspect-ratio dependency. Etch behavior in advanced node is very complicated and brings challenges to conventional rule based OPC correction. Therefore, accurate etch modeling becomes more and more important to make precise prediction of final complex shapes on wafer for OPC correction. In order to ensure the accuracy of etch modeling, high quality metrology is necessary to reduce random error and systematic measurement error. Moreover, CD gauges alone are not sufficient to capture all the effects of the etch process on different patterns. Edge placement (EP) gauges that accurately describe the contour shapes at various key positions are needed. In this work we used the AEI SEM images obtained from traditional CD-SEM flow, processed with ASML’s MXP (Metrology for eXtreme Performance) tool, and used the extracted CD gauges and massive EP gauges to train a deeplearning Newron Etch model. In the approach, MXP reduced the AEI metrology random errors and shape fitting measurement error and provides better pattern coverage with massive reliable CD and EP gauges, Newron Etch captures complex and unknown physical and chemical effects learned from wafer data. Results shows that MXP successfully extracted stable contour from AEI SEM for various pattern types. Three etch models are calibrated and compared: CD based EEB model (Effective Etch Bias), CD+EP based EEB model, and CD+EP based Newron etch model. CD based EEB model captures the major trend of the etch process. Including EP gauges helps EEB model with about 10% RMS reduction on prediction. Integration of MXP (CD+EP) and Newron Etch model gains about 45% prediction RMS reduction compared to baseline model. The good prediction of Newron Etch is also verified from wafer SEM overlay on complex-shape patterns. This result validates the effectiveness of ASML’s solution of deep learning etch model integration with MXP AEI’s massive wafer data extraction from etch process, and will help to provide accurate and reliable etch modeling for advanced node etch OPC correction in semiconductor manufacturing.

Proceedings Article | 26 March 2019 Presentation + Paper

OPC model accuracy study using high volume contour based gauges and deep learning on memory device

Young-Seok Kim, SeIl Lee, Zhenyu Hou, Yiqiong Zhao, Meng Liu, Yunan Zheng, Qian Zhao, Daekwon Kang, Lei Wang, Mark Simmons, Mu Feng, Jun Lang, Byoung-Il Choi, Gilbert Kim, Hakyong Sim, Jongcheon Park, Gyun Yoo, JeonKyu Lee, Sung-woo Ko, Jaeseung Choi, Cheolkyun Kim, Chanha Park

Proceedings Volume 10959, 1095913 (2019) https://doi.org/10.1117/12.2515274

KEYWORDS: Calibration, Metrology, Optical proximity correction, Data modeling, Instrument modeling, Scanning electron microscopy, Time metrology, Neural networks, Semiconducting wafers

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Proceedings Article | 20 March 2019 Presentation + Paper

Compact modeling of negative tone development resist with photo decomposable quencher

Ao Chen, Kar Kit Koh, Yee Mei Foong, Bradley Morgenfeld, Jun Chen, Sandra Lee, Xi Chen, Hesham Omar, Mu Feng, ChangAn Wang, Keith Gronlund, Jun Lang, James Guerrero, Yiqiong Zhao

Proceedings Volume 10961, 109610F (2019) https://doi.org/10.1117/12.2514784

KEYWORDS: Diffusion, SRAF, Photoresist processing, Calibration, Photo decomposable quencher, Semiconducting wafers, Process modeling, Performance modeling, 3D modeling, Error analysis

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Proceedings Article | 7 February 2005 Paper

Design of DOE for beam shaping with highly NA focused cylindrical vector beam

Yiqiong Zhao, Qiwen Zhan, Yong-Ping Li

Proceedings Volume 5636, (2005) https://doi.org/10.1117/12.574724

KEYWORDS: Diffractive optical elements, Beam shaping, Particles, Polarization, Optical design, Optical tweezers, Optimization (mathematics), Algorithms, Lithium, Printing

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Proceedings Article | 18 October 2004 Paper

Design of DOE for the control of optical “bubble” generated by highly focused radially polarized beam

Yiqiong Zhao, Qiwen Zhan, Yong-Ping Li

Proceedings Volume 5514, (2004) https://doi.org/10.1117/12.559317

KEYWORDS: Diffractive optical elements, Optical tweezers, Particles, Polarization, Optimization (mathematics), Wavefronts, Physics, Chemical species, Algorithms, Optical design

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Proceedings Article | 29 September 2004 Paper

Beam shaping with high-NA cylindrical vector beam illumination in SIL systems

Yiqiong Zhao, Qiwen Zhan, Yong-Ping Li

Proceedings Volume 5525, (2004) https://doi.org/10.1117/12.559301

KEYWORDS: Wave propagation, Diffractive optical elements, Solids, Dielectric polarization, Beam propagation method, Interfaces, Optical storage, 3D optical data storage, Data storage, Near field optics

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Proceedings Article | 29 September 2004 Paper

A new simulated annealing algorithm applied to the design of diffractive optical elements used in uniform illumination

Hongliang Liu, Yiqiong Zhao, Yong-Ping Li

Proceedings Volume 5525, (2004) https://doi.org/10.1117/12.559028

KEYWORDS: Diffractive optical elements, Optical design, Algorithms, Optimization (mathematics), Computer simulations, Beam shaping, Monte Carlo methods, Optical simulations, Annealing, Personal protective equipment

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Proceedings Article | 3 November 2003 Paper

Improving PMA and IO algorithms for annular Gaussian beam uniform illumination

Yong-Ping Li, Qiu-Gui Zhou, Yiqiong Zhao

Proceedings Volume 5175, (2003) https://doi.org/10.1117/12.504690

KEYWORDS: Information operations, Detection and tracking algorithms, Diffractive optical elements, Gaussian beams, Fourier transforms, Algorithms, Beam shaping, Inverse problems, Optical design, Computer simulations

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Proceedings Article | 3 November 2003 Paper

Self-iterative algorithms for beam shaping in the vector domain

Yiqiong Zhao, Yong-Ping Li, Qiu-Gui Zhou

Proceedings Volume 5175, (2003) https://doi.org/10.1117/12.504441

KEYWORDS: Beam shaping, Polarization, Personal protective equipment, Diffraction, Diffractive optical elements, Near field, Far-field diffraction, Information operations, Wave propagation, Optical design

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SPIE Journal Paper | 1 November 2003

Vector iterative algorithms for beam shaping

Yiqiong Zhao, Yong-Ping Li

OE, Vol. 42, Issue 11, (November 2003) https://doi.org/10.1117/12.10.1117/1.1619411

KEYWORDS: Polarization, Beam shaping, Diffraction, Far-field diffraction, Diffractive optical elements, Information operations, Optical design, Fourier transforms, Lithium, Error analysis

Proceedings Article | 5 September 2002 Paper

Precise design of the pure phase element for quasi-annular beam shaping

Yuan Wu, Junzhong Xu, Yiqiong Zhao, Shaojun Fu, Yongping Li

Proceedings Volume 4914, (2002) https://doi.org/10.1117/12.481754

KEYWORDS: Personal protective equipment, Beam shaping, Algorithm development, Optimization (mathematics), Fusion energy, Staring arrays, High power lasers, Fourier transforms, Digital filtering, Diffraction

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Proceedings Article | 5 September 2002 Paper

Integrated DOE for beam combination and shaping

Yiqiong Zhao, De-wei Chen, Yongping Li

Proceedings Volume 4914, (2002) https://doi.org/10.1117/12.481782

KEYWORDS: Diffractive optical elements, Diffraction gratings, Personal protective equipment, Etching, Diffraction, Ion beams, Chemical elements, Beam shaping, High power lasers, Modulation

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Showing 5 of 15 publications

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