Mr. Andreas Torsy Profile

Andreas Torsy

at Altis Semiconductor

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Publications (4)

Proceedings Article | 2 May 2008 Paper

MEDEA+ project 2T302 MUSCLE: masks through user's supply chain: leadership by excellence

Andreas Torsy

Proceedings Volume 6792, 67920A (2008) https://doi.org/10.1117/12.798584

KEYWORDS: Photomasks, Standards development, Semiconductors, Data modeling, Semiconducting wafers, Lithography, Manufacturing, Reticles, Software development, Microelectronics

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The rapid evolution of our information society depends on the continuous developments and innovations of semiconductor products. The cost per chip functionality keeps reducing by a factor of 2 every 18 month. However, this performance and success of the semiconductor industry critically depends on the quality of the lithographic photomasks. The need for the high quality of photomask drives lithography costs sensitively, which is a key factor in the manufacture of microelectronics devices. Therefore, the aim is to reduce production costs while overcoming challenges in terms of feature sizes, complexity and cycle times. Consequently, lithography processes must provide highest possible quality at reasonable prices. This way, the leadership in the lithographic area can be maintained and European chipmakers can stay competitive with manufacturers in the Far East and the USA. Under the umbrella of MEDEA+, a project called MUSCLE (<< Masks through User's Supply Chain: Leadership by Excellence >>) has been started among leading semiconductor companies in Europe: ALTIS Semiconductor (Project Leader), ALCATEL Vacuum, ATMEL, CEA/LETI, Entegris, NXP Semiconductors, TOPPAN Photomasks, AMTC, Carl ZEISS SMS, DMS, Infineon Technologies, VISTEC Semiconductor, NIKON Precision, SCHOTT Lithotec, ASML, PHOTRONICS, IMEC, DCE, DNP Photomask, STMicroelectronics, XYALIS and iCADA. MUSCLE focuses particularly on mask data flow, photomask carrier, photomask defect characterization and photomask data handling. In this paper, we will discuss potential solutions like standardization and automation of the photomask data flow based on SEMI P10, the performance and the impact of the supply chain parameter within the photomask process, the standardization of photomask defect characterization and a discussion of the impact of new Reticle Enhancement Technologies (RET) such as mask process correction and finally a generic model to describe the photomasks key performance indicators for prototype photomasks.

Proceedings Article | 3 May 2007 Paper

Benchmark and gap analysis of current mask carriers vs future requirements: example of the carrier contamination

H. Fontaine, M. Davenet, D. Cheung, I. Hoellein, P. Richsteiger, P. Dejaune, A. Torsy

Proceedings Volume 6533, 65330W (2007) https://doi.org/10.1117/12.736973

KEYWORDS: Photomasks, Contamination, Particles, Semiconducting wafers, Reticles, Ions, Chemical analysis, Standards development, Crystals, Analytical research

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Proceedings Article | 20 March 2006 Paper

Illumination conditions matching for critical layers manufacturing in a production context

Louis-Pierre Armellin, Andreas Torsy, Ken Hernan, Gurwan Kerrien, Johanna Guidet, Yan Riopel, Vincent Salvetat

Proceedings Volume 6154, 61543V (2006) https://doi.org/10.1117/12.656538

KEYWORDS: Optical proximity correction, Scanners, Fiber optic illuminators, Semiconducting wafers, Lithography, Relays, Scanning electron microscopy, Manufacturing, Critical dimension metrology, Lithographic illumination

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As device geometries shrink, the lithography solutions to satisfy production requirements for a manufacturable process window often includes Optical Proximity Correction (OPC). OPC is sensitive to many process parameters, one of the most important is the illumination condition, this implicitly includes the lens NA and illuminator NA that generate the partial coherence factor σ, of the scanner. In a production context, the same performance is required for the product using several exposure tools but only one OPC scheme; this requires that the illumination conditions between scanners are matched. This verification has to be done not only for tools of the same generation, but the more complex case between tools of different generations. For the gate layer, an important requirement is the Across Chip Linewidth Variation (ACLV) that ensures transistors performance whatever the pitch. This requirement is mainly driven by Nested-Iso Bias. The paper will present the work completed on the gate layer in order to match the illumination conditions between scanners of the same generation and also between two scanners of different generations: one offers 0.68NA and a maximum σ of 0.75, the other has a maximum NA of 0.82 and maximum σ of 0.9. For scanners of the same generation, the matching was done by simply measuring the illumination NA of the tools, and for this a pinhole test was used. The matching was verified after litho by measuring Nested-Iso bias, and then on product using electrical CD measurement. For the "generation matching", two parameters are needed to define the illumination conditions: lens NA and illuminator NA. In this case, Nested-Iso bias is insufficient to identify the matching conditions as several combinations of lens and illuminator NA lead to the same Nested-Iso bias. Instead the OPC was checked on proximity curves generated for line end shortening and SRAM cells. The best matching conditions were then optimised using a simulation tool with the final check completed on product using electrical CD measurement.

Proceedings Article | 28 May 2004 Paper

Detailed process analysis for sub-resolution assist features introduction

Andreas Torsy, Olivier Toublan, Rainer Zimmermann, Harry Smyth, Jens Hassmann

Proceedings Volume 5377, (2004) https://doi.org/10.1117/12.536575

KEYWORDS: SRAF, Optical proximity correction, Printing, Photomasks, Calibration, Model-based design, Data modeling, Visualization, Process modeling, Silicon

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Sub-Resolution Assists Features (SRAF) is a well known and well described method for process window improvement. The introduction of such a technique is not always an easy task for two reasons. On one hand the SRAF placement rules must be defined very well and on the other hand an empirical resist model must be created, which describes the process. Model based Optical and Process effects correction (MB-OPC) is using an empirical model so called black box, which must be able to predict properly the printing feature for any kind of complex design configuration. When SRAF are implemented in the design, the degree of freedom for the MB-OPC can be reduced. Beside that effort to predetermine as required as possible the target layer, SRAF placement rules and SRAF printing restrictions will limit the OPC. MB-OPC has to cover both the parameters space corresponding to areas in which SRAF are placed and the parameter space for which no SRAF has been implemented. Of course, it could also be possible to apply the correction of the proximity effect of a complex design with SRAF by an extensive rule-based OPC. Nevertheless the advantage of MB-OPC exists in the possibility to verify the design after Data Preparation by simulating it with the help of the calibrated model. However one should not trust the simulation alone, always a verification of the design on silicon would be necessary, by comparing simulation to SEM images. Beside the advantages of MB-OPC also weaknesses exist in the meantime, which could require a combination of rule-based and model-based OPC, so called “hybrid OPC”. Empirical models are very often only able to predict the proximity behavior due to a certain range, which is called the optical range of a model. Distances bigger than this range will be covered by extrapolations. This procedure would be correct, if the proximity behavior was as constant as in the area inside the optical range. We generated an empirical model with the Calibre Workbench from Mentor Graphics. For the model calibration we chose structures with SRAF placement rules, which we applied to the design as well as SRAF placement rules which were not applied to the design. Afterwards, we performed simulations of critical lines over pitch including SRAF. Beside the MB-OPC, we will also describe in this paper the process steps how to generate the SRAF placement rules. The restrictions resulting from the SRAF rules are presented. Subsequently, the experimental results will show that both for symmetrical and asymmetrical structures an improvement of the process window has been obtained. Also weaknesses become clear, which place either the model or the SRAF rule-set questionable. Finally two solutions will be compared, a pure MB-OPC including the isolated lines outside of the optical range and a combination of MB-OPC with a rule-based OPC table for the isolated lines.

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