Dr. Yulu Chen Profile

Dr. Yulu Chen

at Synopsys, Inc.

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Author

Publications (17)

Proceedings Article | 13 June 2022 Presentation

Improved prediction of assist feature printing with physically-based NTD compact models

Folarin Latinwo, Yulu Chen, Cheng-En Wu, Peter Brooker, Hyesook Hong, Delian Yang, Hua Song, Kevin Lucas

Proceedings Volume 12052, 120520P (2022) https://doi.org/10.1117/12.2615990

KEYWORDS: Printing, Data modeling, Data processing, Semiconductors, Semiconducting wafers, Process control, Photoresist materials, Photoresist developing, Optical lithography, Metrology

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Proceedings Article | 22 February 2021 Presentation

Increased OPC modeling accuracy of deformation effects in positive-tone development photoresists

Folarin Latinwo, Yulu Chen, Delian Yang, Rob DeLancey, Owen Huang, Kevin Lucas

Proceedings Volume 11613, 116130F (2021) https://doi.org/10.1117/12.2584781

KEYWORDS: Photoresist materials, Photoresist developing, Optical proximity correction, Optical lithography, Semiconductors, Polymers, Physics, Photoresist processing, Pollution control, Logic

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Proceedings Article | 21 March 2019 Presentation + Paper

Improved validation and optimization of physics-based NTD compact modeling flows

Folarin Latinwo, Delian Yang, Cheng-En (Rich) Wu, Peter Brooker, Yulu Chen, Hua Song, Kevin Lucas

Proceedings Volume 10961, 109610G (2019) https://doi.org/10.1117/12.2516344

KEYWORDS: Data modeling, Calibration, 3D modeling, Photoresist developing, Photoresist materials, Lithography, Optical lithography

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Due to the semiconductor industry’s ever increasing need for finer resolution and improved critical dimension (CD) control, negative tone development (NTD) photoresists (resists) have been adopted for several advanced applications in lithographic patterning. NTD resists enable brightfield imaging by using an organic solvent developer to penetrate and remove the unexposed regions of the resist [1]. For certain critical patterning layers, such as metal trenches and vias, NTD resists are able to provide better resist imaging quality compared to the previous positive tone development (PTD) resist process. However, there are several additional engineering difficulties which must be addressed for an NTD resist process. Specifically, NTD resists have low contrast organic solvent development and in an NTD process the material remaining on the wafer substrate is exposed resist which has been substantially transformed both chemically and mechanically. Therefore, the remaining exposed resist shows significantly more complex physical behavior than the remaining PTD resist and these behaviors require substantial improvement in an OPC (compact) model’s physical modeling accuracy in order to match wafer data and trends [2,3]. Additionally, these more complex resist behaviors place further requirements on the physical validation of OPC modeling inference. In this paper, we present results of our work to understand and improve the optimization and physical validation of physics-based NTD compact modeling flows by utilizing new methods for analysis and automation. We utilize a complete compact model flow containing physics-based resist model forms for chemically amplified resist (CAR) exposure, CAR reaction-diffusion, resist top-loss due to exposure combined with post-exposure bake (PEB), low contrast organic solvent development of resist, and mechanical deformation effects in multiple process steps. We present solid evidence that this physically-based flow has been validated for accuracy and predictability by comparing it to several experimental NTD datasets and to results of rigorous 3D lithography simulation models which were trained to fit other experimental NTD data. We additionally compared key physics-based model forms from the compact model to the more complex full time-based moving surface NTD models of the rigorous 3D simulation. We next analyzed the key physics-based compact model forms for sensitivity to input testpattern type, layout and mask dimension (e.g., linearity and MEEF), traditional dose-focus variations, as well as systematic and random noise in CD metrology. We present the results of this study and make recommendations for minimum testpattern and overall process space data to include in NTD compact model datasets. We also present flow benefits obtained from automating different validation tests including the usefulness of employing rigorous lithography simulation NTD results early in the compact modeling flow to improve overall model quality. [1] S-H. Lee, et all. Understanding dissolution behavior of 193-nm photoresists in organic solvent developers.

Proceedings Article | 20 March 2019 Paper

Investigation of machine learning for dual OPC and assist feature printing optimization

Marco Guajardo, Yulu Chen, Peter Brooker, C.-E. Wu, Kevin Hooker, Folarin Latinwo, Kevin Lucas

Proceedings Volume 10962, 109620E (2019) https://doi.org/10.1117/12.2516134

KEYWORDS: Printing, Optical proximity correction, Photomasks, Calibration, 3D modeling, Semiconducting wafers, Machine learning, Data modeling, Lithography

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Proceedings Article | 19 March 2018 Presentation + Paper

Holistic analysis of aberration induced overlay error in EUV lithography

Yulu Chen, Lars Liebmann, Lei Sun, Allen Gabor, Shuo Zhao, Feixiang Luo, Obert Wood, Xuemei Chen, Daniel Schmidt, Michael Kling, Francis Goodwin

Proceedings Volume 10583, 105830D (2018) https://doi.org/10.1117/12.2297027

KEYWORDS: Aberration theory, Zernike polynomials, Diffraction, Extreme ultraviolet lithography, Wavefronts, Error analysis, Scanners, Photomasks, Overlay metrology, Lithography

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Proceedings Article | 16 October 2017 Presentation + Paper

Measurement of through-focus EUV pattern shifts using the SHARP actinic microscope

Obert Wood, Yulu Chen, Pawitter Mangat, Kenneth Goldberg, Markus Benk, Bryan Kasprowicz, Henry Kamberian, Jeremy McCord, Thomas Wallow

Proceedings Volume 10450, 1045008 (2017) https://doi.org/10.1117/12.2280371

KEYWORDS: Extreme ultraviolet, Photomasks, Microscopes, Extreme ultraviolet lithography, 3D metrology, Reflectivity, Optical lithography, Image analysis, Image segmentation, Lithography

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Proceedings Article | 16 October 2017 Paper

Rigorous simulation of EUV mask pellicle

Yulu Chen, Xiangyu Zhou, Ulrich Klostermann, Lei Sun, Obert Wood, Mariya Braylovska, Sajan Marokkey, Francis Goodwin

Proceedings Volume 10451, 104510S (2017) https://doi.org/10.1117/12.2280339

KEYWORDS: Pellicles, Photomasks, Extreme ultraviolet, Nanoimprint lithography, Extreme ultraviolet lithography, Transmittance, Temporal coherence, Particles, Nickel, High volume manufacturing

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Proceedings Article | 6 September 2017 Presentation + Paper

Opportunities for sub-wavelength imaging based on motion in structured illumination

Kevin Webb, Yulu Chen, Dergan Lin, Qiaoen Luo, Vivek Raghuram

Proceedings Volume 10410, 104100P (2017) https://doi.org/10.1117/12.2276672

KEYWORDS: Speckle, Motion measurement, Optical imaging, Optical sensing, Microscopy, Biomedical optics, Dielectrics, Coherence imaging, Image resolution, Scattering

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Proceedings Article | 30 March 2017 Presentation + Paper

Design intent optimization at the beyond 7nm node: the intersection of DTCO and EUVL stochastic mitigation techniques

Michael Crouse, Lars Liebmann, Vince Plachecki, Mohamed Salama, Yulu Chen, Nicole Saulnier, Derren Dunn, Itty Matthew, Stephen Hsu, Keith Gronlund, Francis Goodwin

Proceedings Volume 10148, 101480H (2017) https://doi.org/10.1117/12.2260865

KEYWORDS: Extreme ultraviolet, Extreme ultraviolet lithography, Stochastic processes, Optical lithography, Lithography, Tolerancing, Computational lithography, Design for manufacturability, Manufacturing, Back end of line, Source mask optimization, Photomasks, Logic, Optical proximity correction, Nanoimprint lithography

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The initial readiness of EUV patterning was demonstrated in 2016 with IBM Alliance's 7nm device technology. The focus has now shifted to driving the 'effective' k1 factor and enabling the second generation of EUV patterning. Thus, Design Technology Co-optimization (DTCO) has become a critical part of technology enablement as scaling has become more challenging and the industry pushes the limits of EUV lithography. The working partnership between the design teams and the process development teams typically involves an iterative approach to evaluate the manufacturability of proposed designs, subsequent modifications to those designs and finally a design manual for the technology. While this approach has served the industry well for many generations, the challenges at the Beyond 7nm node require a more efficient approach. In this work, we describe the use of “Design Intent” lithographic layout optimization where we remove the iterative component of DTCO and replace it with an optimization that achieves both a “patterning friendly” design and minimizes the well-known EUV stochastic effects. Solved together, this “design intent” approach can more quickly achieve superior lithographic results while still meeting the original device’s functional specifications.

Specifically, in this work we will demonstrate “design intent” optimization for critical BEOL layers using design tolerance bands to guide the source mask co-optimization. The design tolerance bands can be either supplied as part of the original design or derived from some basic rules. Additionally, the EUV stochastic behavior is mitigated by enhancing the image log slope (ILS) for specific key features as part of the overall optimization. We will show the benefit of the “design intent approach” on both bidirectional and unidirectional 28nm min pitch standard logic layouts and compare the more typical iterative SMO approach. Thus demonstrating the benefit of allowing the design to float within the specified range. Lastly, we discuss how the evolution of this approach could lead to layout optimization based entirely on some minimal set of functional requirements and process constraints.

Proceedings Article | 27 March 2017 Paper

Monte Carlo sensitivity analysis of EUV mask reflectivity and its impact on OPC accuracy

Yulu Chen, Obert Wood, Jed Rankin, Eric Gullikson, Julia Meyer-Ilse, Lei Sun, Zhengqing John Qi, Francis Goodwin, Jongwook Kye

Proceedings Volume 10143, 101431S (2017) https://doi.org/10.1117/12.2258121

KEYWORDS: Data modeling, Photomasks, Reflectivity, Extreme ultraviolet, Optical proximity correction, Monte Carlo methods, Extreme ultraviolet lithography, Reflectors, Statistical analysis, Electromagnetic theory, Surface roughness, Silicon, Molybdenum, Scanning tunneling microscopy

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Proceedings Article | 27 March 2017 Presentation + Paper

Separating the optical contributions to line-edge roughness in EUV lithography using stochastic simulations

Anindarupa Chunder, Azat Latypov, Yulu Chen, John Biafore, Harry Levinson, Todd Bailey

Proceedings Volume 10146, 101460B (2017) https://doi.org/10.1117/12.2258693

KEYWORDS: Monte Carlo methods, Stochastic processes, Line edge roughness, Extreme ultraviolet lithography, Extreme ultraviolet, Photoresist materials, EUV optics, Lithography, Chemically amplified resists, Calibration, Edge roughness, Photoresist processing

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Proceedings Article | 24 March 2017 Presentation + Paper

Printability and actinic AIMS review of programmed mask blank defects

Erik Verduijn, Pawitter Mangat, Obert Wood, Jed Rankin, Yulu Chen, Francis Goodwin, Renzo Capelli, Sascha Perlitz, Dirk Hellweg, Ravi Bonam, Shravan Matham, Nelson Felix, Daniel Corliss

Proceedings Volume 10143, 101430K (2017) https://doi.org/10.1117/12.2260053

KEYWORDS: Photomasks, Semiconducting wafers, Scanning electron microscopy, Extreme ultraviolet, Printing, Bridges, Extreme ultraviolet lithography, Inspection, Chromium, Atomic force microscopy

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Proceedings Article | 10 May 2016 Paper

Thin absorber EUV photomask based on mixed Ni and TaN material

Derrick Hay, Patrick Bagge, Ian Khaw, Lei Sun, Obert Wood, Yulu Chen, Ryoung-han Kim, Zhengqing John Qi, Zhimin Shi

Proceedings Volume 9984, 99840G (2016) https://doi.org/10.1117/12.2240093

KEYWORDS: Extreme ultraviolet, Photomasks, Nickel, Nanoparticles, Reflectivity, Absorption, Nanocomposites, Extreme ultraviolet lithography, Lithography, Etching

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Proceedings Article | 18 March 2016 Paper

Application of EUV resolution enhancement techniques (RET) to optimize and extend single exposure bi-directional patterning for 7nm and beyond logic designs

Ryoung-Han Kim, Obert Wood, Michael Crouse, Yulu Chen, Vince Plachecki, Stephen Hsu, Keith Gronlund

Proceedings Volume 9776, 97761R (2016) https://doi.org/10.1117/12.2219177

KEYWORDS: SRAF, Resolution enhancement technologies, Logic, Extreme ultraviolet lithography, Source mask optimization, Optical proximity correction, Line edge roughness, Nanoimprint lithography, Stochastic processes, Semiconducting wafers

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Proceedings Article | 18 March 2016 Paper

Comparison of left and right side line edge roughness in lithography

Lei Sun, Nicole Saulnier, Genevieve Beique, Erik Verduijn, Wenhui Wang, Yongan Xu, Hao Tang, Yulu Chen, Ryoung-han Kim, John Arnold, Nelson Felix, Matthew Colburn

Proceedings Volume 9778, 977822 (2016) https://doi.org/10.1117/12.2219665

KEYWORDS: Line edge roughness, Metrology, Lithography, Etching, Semiconductors, Scattering, Inspection, Critical dimension metrology, Photomasks, Roads, Extreme ultraviolet lithography

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Proceedings Article | 16 March 2016 Paper

Directed self-assembly aware restricted design rule and its impact on design ability

Yulu Chen, Ryoung-han Kim

Proceedings Volume 9781, 978104 (2016) https://doi.org/10.1117/12.2219216

KEYWORDS: Design for manufacturability, Manufacturing, Design for manufacturing, Directed self assembly, Information operations, Analog electronics, Annealing, Etching, Evolutionary algorithms, Optical lithography

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Proceedings Article | 15 March 2016 Paper

Line edge roughness frequency analysis for SAQP process

Lei Sun, Xiaoxiao Zhang, Shimon Levi, Adam Ge, Hua Zhou, Wenhui Wang, Navaneetha Krishnan, Yulu Chen, Erik Verduijn, Ryoung-han Kim

Proceedings Volume 9780, 97801S (2016) https://doi.org/10.1117/12.2229176

KEYWORDS: Line edge roughness, Line width roughness, Lithography, Optical lithography, Semiconductor manufacturing, Chemical mechanical planarization, Dielectrophoresis

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Showing 5 of 17 publications

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