Mr. Bernd Schulz Profile

Bernd Schulz

Senior Member of Technical Staff at GLOBALFOUNDRIES Dresden Module One, GmbH & Co. KG

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Author

Publications (19)

Proceedings Article | 13 March 2018 Presentation + Paper

Matching between simulations and measurements as a key driver for reliable overlay target design

S. Lozenko, T. Shapoval, G. Ben-Dov, Z. Lindenfeld, B. Schulz , L. Fuerst, C. Hartig, R. Haupt, M. Ruhm, R. Wang

Proceedings Volume 10585, 105851E (2018) https://doi.org/10.1117/12.2297011

KEYWORDS: Scatterometry, Overlay metrology, Semiconducting wafers, Diffraction, Diffraction gratings, Computer simulations, Manufacturing, Data modeling, Critical dimension metrology

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Proceedings Article | 28 March 2017 Presentation + Paper

Combined process window monitoring for critical features

Carsten Hartig, Bernd Schulz, Robert Melzer, Matthias Ruhm, Daniel Fischer, Stefan Buhl, Boris Habets, Martin Rößiger, Manuela Gutsch

Proceedings Volume 10145, 101450U (2017) https://doi.org/10.1117/12.2259910

KEYWORDS: Electrical breakdown, Semiconducting wafers, Critical dimension metrology, Overlay metrology, Computer simulations, Lithography, Metals, Optical lithography, Feature extraction, Distance measurement

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Proceedings Article | 19 March 2015 Paper

Influence of the process-induced asymmetry on the accuracy of overlay measurements

Tetyana Shapoval, Bernd Schulz, Tal Itzkovich, Sean Durran, Ronny Haupt, Agostino Cangiano, Barak Bringoltz, Matthias Ruhm, Eric Cotte, Rolf Seltmann, Tino Hertzsch, Eitan Hajaj, Carsten Hartig, Boris Efraty, Daniel Fischer

Proceedings Volume 9424, 94240B (2015) https://doi.org/10.1117/12.2085788

KEYWORDS: Optical filters, Overlay metrology, Semiconducting wafers, Data modeling, Metrology, Optical properties, Optical simulations, Signal processing, Etching, Image segmentation

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Proceedings Article | 17 October 2014 Paper

Overlay leaves litho: impact of non-litho processes on overlay and compensation

Matthias Ruhm, Bernd Schulz, Eric Cotte, Rolf Seltmann, Tino Hertzsch

Proceedings Volume 9231, 92310O (2014) https://doi.org/10.1117/12.2068206

KEYWORDS: Overlay metrology, Etching, Semiconducting wafers, Lithography, Distortion, Metrology, Photomasks, Semiconductor manufacturing, Control systems, Plasma etching

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Proceedings Article | 1 October 2013 Paper

Scanner grid recipe creation improvement for tighter overlay specifications

Eric Cotte, Hariharasudhan Kathiresan, Matthias Ruhm, Bernd Schulz, Uwe Schulze

Proceedings Volume 8886, 888608 (2013) https://doi.org/10.1117/12.2030186

KEYWORDS: Overlay metrology, Scanners, Metrology, Semiconducting wafers, Process control, Time metrology, Lithography, Manufacturing, Pollution control, Photomasks

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Proceedings Article | 10 April 2013 Paper

Material contrast based inline metrology: process verification and control using back scattered electron imaging on CD-SEM

Carsten Hartig, Daniel Fischer, Bernd Schulz, Alok Vaid, Ofer Adan, Shimon Levi, Adam Ge, Jessica Zhou, Maayan Bar-Zvi, Ronny Enge, Uwe Groh

Proceedings Volume 8681, 868108 (2013) https://doi.org/10.1117/12.2012011

KEYWORDS: Metrology, Process control, Scanning electron microscopy, Semiconducting wafers, Etching, Copper, Overlay metrology, Signal detection, Image processing, Metals

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Proceedings Article | 24 March 2009 Paper

Monitoring measurement tools: new methods for driving continuous improvements in fleet measurement uncertainty

Eric Solecky, Chas Archie, Matthew Sendelbach, Ron Fiege, Mary Zaitz, Dmitriy Shneyder, Carlos Strocchia-rivera, Andres Munoz, Srinivasan Rangarajan, William Muth, Andrew Brendler, Bill Banke, Bernd Schulz, Carsten Hartig, Jon-Tobias Hoeft, Alok Vaid, Mark Kelling, Benjamin Bunday, John Allgair

Proceedings Volume 7272, 72721H (2009) https://doi.org/10.1117/12.814089

KEYWORDS: Semiconducting wafers, Metrology, Scatterometry, Process control, Calibration, Manufacturing, Overlay metrology, Time metrology, Atomic force microscopy

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Ever shrinking measurement uncertainty requirements are difficult to achieve for a typical metrology toolset, especially over the entire expected life of the fleet. Many times, acceptable performance can be demonstrated during brief evaluation periods on a tool or two in the fleet. Over time and across the rest of the fleet, the most demanding processes often have measurement uncertainty concerns that prevent optimal process control, thereby limiting premium part yield, especially on the most aggressive technology nodes. Current metrology statistical process control (SPC) monitoring techniques focus on maintaining the performance of the fleet where toolset control chart limits are derived from a stable time period. These tools are prevented from measuring product when a statistical deviation is detected. Lastly, these charts are primarily concerned with daily fluctuations and do not consider the overall measurement uncertainty. It is possible that the control charts implemented for a given toolset suggest a healthy fleet while many of these demanding processes continue to suffer measurement uncertainty issues. This is especially true when extendibility is expected in a given generation of toolset. With this said, there is a need to continually improve the measurement uncertainty of the fleet until it can no longer meet the needed requirements at which point new technology needs to be entertained. This paper explores new methods in analyzing existing SPC monitor data to assess the measurement performance of the fleet and look for opportunities to drive improvements. Long term monitor data from a fleet of overlay and scatterometry tools will be analyzed. The paper also discusses using other methods besides SPC monitors to ensure the fleet stays matched; a set of SPC monitors provides a good baseline of fleet stability but it cannot represent all measurement scenarios happening in product recipes. The analyses presented deal with measurement uncertainty on non-measurement altering metrology toolsets such as scatterometry, overlay, atomic force microscopy (AFM) or thin film tools. The challenges associated with monitoring toolsets that damage the sample such as the CD-SEMs will also be discussed. This paper also explores improving the monitoring strategy through better sampling and monitor selection. The industry also needs to converge regarding the metrics used to describe the matching component of measurement uncertainty so that a unified approach is reached regarding how to best drive the much needed improvements. In conclusion, there will be a discussion on automating these new methods3,4 so they can complement the existing methods to provide a better method and system for controlling and driving matching improvements in the fleet.

Proceedings Article | 24 March 2008 Paper

Automated creation of production metrology recipes based on design information

Jason Cain, Mark Threefoot, Kishan Shah, Bernd Schulz, Stefanie Girol-Gunia, Jon-Tobias Hoeft

Proceedings Volume 6922, 69221J (2008) https://doi.org/10.1117/12.773407

KEYWORDS: Metrology, Overlay metrology, Pattern recognition, Semiconducting wafers, Detection and tracking algorithms, Scatterometry, Time metrology, Target recognition, Databases, Optical alignment

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Proceedings Article | 22 March 2008 Paper

Using in-chip overlay metrology

Stefanie Girol-Gunia, Bernd Schulz, Nigel Smith, Lewis Binns

Proceedings Volume 6922, 69220N (2008) https://doi.org/10.1117/12.774507

KEYWORDS: Overlay metrology, Semiconducting wafers, Calibration, Data modeling, Wafer-level optics, Optical testing, Process control, Photomasks, Etching, Scanners

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Proceedings Article | 3 May 2007 Paper

An empirical approach adressing the transfer of mask placement errors during exposure

B. Alles, B. Simeon, E. Cotte, T. Wandel, B. Schulz, R. Seltmann

Proceedings Volume 6533, 65330U (2007) https://doi.org/10.1117/12.736958

KEYWORDS: Photomasks, Semiconducting wafers, Error analysis, Statistical analysis, Image registration, Overlay metrology, Dysprosium, Data modeling, Statistical modeling, Metals

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Proceedings Article | 4 April 2007 Paper

Meeting overlay requirements for future technology nodes with in-die overlay metrology

Bernd Schulz, Rolf Seltmann, Jens Busch, Fritjof Hempel, Eric Cotte, Benjamin Alles

Proceedings Volume 6518, 65180E (2007) https://doi.org/10.1117/12.708471

KEYWORDS: Overlay metrology, Reticles, Semiconducting wafers, Image registration, Photomasks, Data modeling, Pellicles, Scanners, Error analysis, Metrology

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Proceedings Article | 27 March 2006 Paper

Advanced DFM applications using design-based metrology on CD SEM

G. Lorusso, L. Capodieci, D. Stoler, B. Schulz, S. Roling, J. Schramm, C. Tabery, K. Shah, B. Singh, G. Abbott, A. Roberts, A. Azordegan, L. Heinrichs, Z. Kaliblotzky, E. Castel

Proceedings Volume 6152, 61520B (2006) https://doi.org/10.1117/12.674776

KEYWORDS: Semiconducting wafers, Metrology, Optical proximity correction, Pattern recognition, Design for manufacturing, Scanning electron microscopy, Calibration, Computer aided design, Resolution enhancement technologies, Algorithm development

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Proceedings Article | 24 March 2006 Paper

In-field overlay uncertainty contributors: a back end study

Mike Adel, Aviv Frommer, Elyakim Kassel, Pavel Izikson, Philippe Leray, Bernd Schulz, Rolf Seltmann, Jens Busch

Proceedings Volume 6152, 615213 (2006) https://doi.org/10.1117/12.656467

KEYWORDS: Reticles, Overlay metrology, Scanners, Data modeling, Semiconducting wafers, Metrology, Chemical mechanical planarization, Manufacturing, Polishing, Optical alignment

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Proceedings Article | 10 May 2005 Paper

In field overlay uncertainty contributors

Aviv Frommer, Elyakim Kassel, Pavel Izikson, Mike Adel, Philippe Leray, Bernd Schulz

Proceedings Volume 5752, (2005) https://doi.org/10.1117/12.599397

KEYWORDS: Reticles, Overlay metrology, Semiconducting wafers, Scanners, Dysprosium, Metrology, Data modeling, Personal protective equipment, Lithography, Manufacturing

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Proceedings Article | 24 May 2004 Paper

Time-based PEB adjustment for optimizing CD distributions

Paul Friedberg, Cherry Tang, Bhanwar Singh, Thomas Brueckner, Wolfram Gruendke, Bernd Schulz, Costas Spanos

Proceedings Volume 5375, (2004) https://doi.org/10.1117/12.535871

KEYWORDS: Critical dimension metrology, Semiconducting wafers, Temperature metrology, 193nm lithography, Photoresist materials, Scatterometry, Data modeling, Lithography, Sensors, Thermal effects

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Proceedings Article | 2 June 2003 Paper

Lithography and metrology overlay troubleshooting by advanced query and multivariate analysis

Bernd Schulz, Jens Krause, John Robinson, Craig MacNaughton

Proceedings Volume 5038, (2003) https://doi.org/10.1117/12.483470

KEYWORDS: Overlay metrology, Semiconducting wafers, Data modeling, Databases, Lithography, Metrology, Statistical analysis, Data analysis, Metals, Back end of line

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Proceedings Article | 16 July 2002 Paper

Overlay accuracy in 0.18-micron copper dual-damascene process

Bernd Schulz, Harry Levinson, Rolf Seltmann, Joel Seligson, Pavel Izikson, Anat Ronen

Proceedings Volume 4689, (2002) https://doi.org/10.1117/12.473477

KEYWORDS: Overlay metrology, Semiconducting wafers, Calibration, Wafer-level optics, Etching, Optical testing, Metrology, Reticles, Scanners, Manufacturing

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Proceedings Article | 5 July 2000 Paper

Overlay budget considerations for an all-scanner fab

Rolf Seltmann, Wolfgang Demmerle, Marc Staples, Anna Maria Minvielle, Bernd Schulz, Sven Muehle

Proceedings Volume 4000, (2000) https://doi.org/10.1117/12.388935

KEYWORDS: Optical alignment, Overlay metrology, Semiconducting wafers, Chemical mechanical planarization, Aluminum, Reticles, Copper, Metals, Distortion, Data transmission

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Proceedings Article | 2 June 2000 Paper

Automated process control monitor for 0.18-um technology and beyond

Bryan Choo, Trina Riley, Bernd Schulz, Bhanwar Singh

Proceedings Volume 3998, (2000) https://doi.org/10.1117/12.386474

KEYWORDS: Line scan image sensors, Critical dimension metrology, Semiconducting wafers, Process control, Lithography, Image processing, Pattern recognition, Etching, Lithium, Optical lithography

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Currently, most production fabs use critical dimension (CD) measurements as their primary means for process control in printing lines, spaces and contacts. Historically, this has been adequate to control the lithography and etch processes and produce reasonable yields. However, as the industry moves from 0.25 micrometer manufacturing to 0.18 micrometer and beyond, it is becoming increasingly obvious that CD measurements alone do not provide enough information about the printed structures. As the geometry shrinks, slight changes in the shape and profile can significantly affect the electrical characteristics of the circuit while maintaining the same CD value. In this paper, we will describe a method which, in conjunction with the CD measurements, better characterizes the circuit structures and therefore provides valuable feedback about the process. This method compares stored image and linescan information of a 'golden' (correctly processed) structure to that of the structure being measured. Based on the collected data, it is possible to distinguish between different profiles and determine if a process shift has occurred, even when the measured CD remains within specification. The correlation score therefore provides an additional constraint that better defines the true process window and provides an additional flag for process problems. Without this information, the process used may not be truly optimized, or a shift may occur that is not detected in a timely manner, resulting in the loss of yield and revenue. This data collection has been implemented in production on a local interconnect lithography process. Before the correlation information was available, it was very difficult to detect the scumming within the LI trench, in which it was a time consuming and labor intensive procedure to identify problem lots. The correlation scores, collected automatically and concurrently with the CD measurement, allowed tracking through the SPC chart and the automatic flagging of problems while the lot was still in the photolithography module. The result has been faster feedback control and thus less scrap material.

Showing 5 of 19 publications

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