Dr. Jiao Liang Profile

Dr. Jiao Liang

Materials Scientist at ASML

SPIE Involvement:

Author

Publications (4)

Proceedings Article | 22 April 2024 Poster + Paper

Advanced pattern selection and coverage check for computational lithography

Keonwoo Bae, Taekyum Kim, Sanghwa Lee, Bongkeun Kim, Seongtae Jeong, Jenny Tang, Qian Zhao, Yiqiong Zhao, Chang-Il Choi, Jiao Liang, Uwe Paul Schroeder, Mark Simmons

Proceedings Volume 12957, 129571M (2024) https://doi.org/10.1117/12.3009845

KEYWORDS: Calibration, Optical proximity correction, Extreme ultraviolet, Data modeling, Education and training, Performance modeling, Advanced patterning, Metrology, Machine learning, Databases

Read Abstract +

Proceedings Article | 28 September 2021 Presentation

Contour-based variability decomposition for stochastic band metrology

Thomas Wallow, Jiyou Fu, Jiao Liang, Jen-Shiang Wang, Jimmy Fan, Maxence Delorme, ChangAn Wang, Fahong Li, Vivek Jain, Rui Yuan

Proceedings Volume 11854, 118540E (2021) https://doi.org/10.1117/12.2601587

KEYWORDS: Metrology, Stochastic processes, Photomasks, Model-based design, Scanning electron microscopy, Line edge roughness, Optical lithography, Semiconducting wafers, Extreme ultraviolet, Wafer-level optics

Read Abstract +

Proceedings Article | 22 March 2018 Paper

Massive metrology using fast e-beam technology improves OPC model accuracy by >2x at faster turnaround time

Qian Zhao, Lei Wang, Jazer Wang, ChangAn Wang, Hong-Fei Shi, James Guerrero, Mu Feng, Qiang Zhang, Jiao Liang, Yunbo Guo, Chen Zhang, Tom Wallow, David Rio, Lester Wang, Alvin Wang, Jen-Shiang Wang, Keith Gronlund, Jun Lang, Kar Kit Koh, Dong Qing Zhang, Hongxin Zhang, Subramanian Krishnamurthy, Ray Fei, Chiawen Lin, Wei Fang, Fei Wang

Proceedings Volume 10585, 105852Q (2018) https://doi.org/10.1117/12.2299971

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

Read Abstract +

Classical SEM metrology, CD-SEM, uses low data rate and extensive frame-averaging technique to achieve high-quality SEM imaging for high-precision metrology. The drawbacks include prolonged data collection time and larger photoresist shrinkage due to excess electron dosage. This paper will introduce a novel e-beam metrology system based on a high data rate, large probe current, and ultra-low noise electron optics design. At the same level of metrology precision, this high speed e-beam metrology system could significantly shorten data collection time and reduce electron dosage. In this work, the data collection speed is higher than 7,000 images per hr. Moreover, a novel large field of view (LFOV) capability at high resolution was enabled by an advanced electron deflection system design. The area coverage by LFOV is >100x larger than classical SEM. Superior metrology precision throughout the whole image has been achieved, and high quality metrology data could be extracted from full field. This new capability on metrology will further improve metrology data collection speed to support the need for large volume of metrology data from OPC model calibration of next generation technology. The shrinking EPE (Edge Placement Error) budget places more stringent requirement on OPC model accuracy, which is increasingly limited by metrology errors. In the current practice of metrology data collection and data processing to model calibration flow, CD-SEM throughput becomes a bottleneck that limits the amount of metrology measurements available for OPC model calibration, impacting pattern coverage and model accuracy especially for 2D pattern prediction. To address the trade-off in metrology sampling and model accuracy constrained by the cycle time requirement, this paper employs the high speed e-beam metrology system and a new computational software solution to take full advantage of the large volume data and significantly reduce both systematic and random metrology errors. The new computational software enables users to generate large quantity of highly accurate EP (Edge Placement) gauges and significantly improve design pattern coverage with up to 5X gain in model prediction accuracy on complex 2D patterns. Overall, this work showed >2x improvement in OPC model accuracy at a faster model turn-around time.

Proceedings Article | 31 March 2014 Paper

Process window enhancement using advanced RET techniques for 20nm contact layer

Yang Ping, Sarah McGowan, Ying Gong, Yee Mei Foong, Jian Liu, Jianhong Qiu, Vincent Shu, Bo Yan, Jun Ye, Pengcheng Li, Hui Zhou, Taksh Pandey, Jiao Liang, Chris Aquino, Stanislas Baron, Sanjay Kapasi

Proceedings Volume 9052, 90521N (2014) https://doi.org/10.1117/12.2048513

KEYWORDS: Optical proximity correction, SRAF, Source mask optimization, Resolution enhancement technologies, Molybdenum, Photomasks, Electroluminescence, Astatine, Printing, Neodymium

Read Abstract +

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years