Dr. Martin Sczyrba Profile

Dr. Martin Sczyrba

at Advanced Mask Technology Center GmbH & Co. KG

SPIE Involvement:

Author

Publications (29)

Proceedings Article | 26 September 2019 Presentation + Paper

Loading effect correction set up by supplementing CD measurement analysis with machine learning

Christian Bürgel, Martin Sczyrba, Clemens Utzny

Proceedings Volume 11148, 111480C (2019) https://doi.org/10.1117/12.2539821

KEYWORDS: Critical dimension metrology, Machine learning, Photomasks, Etching, Scanning electron microscopy, Convolution, Semiconductors, Quality measurement, Environmental sensing, Manufacturing

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With semiconductor technology approaching and exceeding 10 nm design rules the quality requirements for photomasks are continuously tightening. One of the crucial parameters is improved control of the critical dimension (CD) across the photomask. As long as linearity and through pitch effects are not involved, the quality measure is typically defined as CD uniformity. This parameter is normally measured on repeating structures of same size and shape, which are not necessarily placed in identical environments. Density dependent process effects, also called loading effects (LE), pose a challenge for the required CD control. There are several possible contributors to this kind of error within the mask manufacturing flow, such as etch driven loading effects, fogging effects during 50kV exposure and develop driven loading effects. All of these operate at different working ranges, starting at millimeters going down to only a few 100 μm scale. It is comparably easy to derive models for large scale phenomena like etch loading or fogging effects, in contrast to that it is not as straight forward to find suitable models for very short-range effects. A large amount of CD measurements taken by CD SEM is needed to identify such signals of low magnitude and short scales, which make the setup very resource intensive. Furthermore, this methodology requires artificial designs and test structures which aim to sample only the effect of interest. In this paper we present a strategy which combines CD SEM measurements from dedicated test masks with the results from regular product masks. The aim is the derivation and validation of the loading effect correction range and strength. In the first step the data from test masks is analyzed to set up the basic correction parameters. Following this, the approach is supplemented by product data where we combine mask CD and design data. The clear field distribution of the design is convoluted with respect to a hierarchy of length scales. This data is the input for a support vector machine analysis. Thus, we employ a flat machine learning algorithm. However, the input data has been set up to reflect multiple layers of convolution. This particular approach has been chosen, as each convolution length scale is associated with mask process properties, thus alleviating the burden of interpretation which typically mars the interpretation of models obtained by machine learning approaches.

Proceedings Article | 29 August 2019 Paper

Necessity is the mother of invention: support vector machines for CD control

Christian Bürgel, Martin Sczyrba, Clemens Utzny

Proceedings Volume 11177, 1117709 (2019) https://doi.org/10.1117/12.2535745

KEYWORDS: Machine learning, Data modeling, Critical dimension metrology, Performance modeling, Process control, Visualization, Data centers, Solids, Data processing, Optical inspection

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The currently increasing demand for photo-masks in the regime of the 14nm technology drives many initiatives towards capacity and throughput increase of existing production line. Such improvements are facilitated by improved control mechanisms of the tools and processes used within a production line. While process control of long range parameters such as the average CD behavior is demanding yet conceptually well understood, other parameters such as the small scales CD properties are quite often elusive to process control. These properties often require a dedicated test mask to be processed in order to be validated. In this paper we introduce a systematic approach towards a product based monitoring of small scale CD behavior which uses a CD characteristic extracted from the defect inspection process. This characteristic represents the influence of CD relevant processes starting from 200m up to 4000 m. Large variations in the scale and magnitude of the CD characteristic are induced by layout specific design variations. However, the shape of these distinct curves is remarkably similar, which enables their use for monitoring as well as controlling the mask processes on the above stated spatial scales. In this paper it is demonstrated, that a meaningful process evaluation can be performed by using the classification capabilities of the support vector machines. The small scales CD characteristics presented in figure 1 originate from two distinct tools. Matching of the two tools can be assessed by training a support vector machine to classify the small scales CD characteristics according to their origin. The classification performance on the resampled training set as well as on the validation set is a robust measure for tool matching. The results of this approach are depicted in figure 2. The left panel shows the AUC statistics of bootstrapping resamples for tool comparison “A”. In this case no noticeable difference between the two tools is found (an average AUC of 0.55 suggest no learnable difference). This is contrasted by the tool comparison “B”, here the classifier has an average AUC of 0.75, indicating a learnable difference in the tool performances. This result is backed by the process understand of both tool types.

Proceedings Article | 27 June 2019 Paper

Deal gently with the bird you are trying to catch: small scale CD control with machine learning

Christian Bürgel, Martin Sczyrba, Clemens Utzny

Proceedings Volume 11178, 111780L (2019) https://doi.org/10.1117/12.2534978

KEYWORDS: Critical dimension metrology, Machine learning, Data modeling, Process control, Visualization, Data centers, Solids, Detection and tracking algorithms, Data processing, Optical inspection

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Proceedings Article | 20 March 2018 Paper

Hot spot variability and lithography process window investigation by CDU improvement using CDC technique

Thomas Thamm, Bernd Geh, Marija Djordjevic Kaufmann, Rolf Seltmann, Alla Bitensky, Martin Sczyrba, Aravind Narayana Samy

Proceedings Volume 10587, 105870F (2018) https://doi.org/10.1117/12.2297382

KEYWORDS: Photomasks, Scanners, Reticles, Light scattering, Scattering, Logic devices, Source mask optimization, Lithography

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Proceedings Article | 9 November 2015 Paper

Absorber topography dependence of phase edge effects

Aamod Shanker, Martin Sczyrba, Brid Connolly, Laura Waller, Andy Neureuther

Proceedings Volume 9635, 96350G (2015) https://doi.org/10.1117/12.2197861

KEYWORDS: Polarization, Refractive index, Phase measurement, Near field, Absorption, Opacity, Silica, Photomasks, 193nm lithography, Semiconducting wafers, Diffraction, Phase shift keying, Critical dimension metrology, Airborne remote sensing, Finite-difference time-domain method, Panoramic photography, Binary data, Deep ultraviolet

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Proceedings Article | 26 March 2015 Paper

Characterizing the dependence of thick-mask edge effects on illumination angle using AIMS images

Aamod Shanker, Martin Sczyrba, Falk Lange, Brid Connolly, Andrew Neureuther, Laura Waller

Proceedings Volume 9426, 94260O (2015) https://doi.org/10.1117/12.2087615

KEYWORDS: Photomasks, Polarization, Semiconducting wafers, Imaging systems, Printing, Spatial frequencies, Airborne remote sensing, 3D modeling, Phase retrieval, Switches

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Proceedings Article | 31 March 2014 Paper

Critical assessment of the transport of intensity equation as a phase recovery technique in optical lithography

Aamod Shanker, Martin Sczyrba, Brid Connolly, Franklin Kalk, Andy Neureuther, Laura Waller

Proceedings Volume 9052, 90521D (2014) https://doi.org/10.1117/12.2048278

KEYWORDS: Photomasks, Semiconducting wafers, Imaging systems, 3D modeling, Phase imaging, Absorption, Phase shifts, Polarization, Error analysis, Finite-difference time-domain method

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Proceedings Article | 10 September 2013 Paper

Analysis of edge effects in attenuating phase-shift masks using quantitative phase imaging

Aamod Shanker, Martin Sczyrba, Brid Connolly, Andy Neureuther, Laura Waller

Proceedings Volume 8880, 88802A (2013) https://doi.org/10.1117/12.2027825

KEYWORDS: Photomasks, Polarization, Semiconducting wafers, Phase shifts, Phase imaging, Data modeling, Wafer-level optics, Imaging systems, Printing, Phase measurement

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Proceedings Article | 8 November 2012 Paper

The significance of rigorous electromagnetic field simulation on mask development for 20nm optical lithography technology

Fan Jiang, Yunfei Deng, Jongwook Kye, Harry Levinson, Paul Ackmann, Byoung Choi, Frank Schurack, Martin Sczyrba

Proceedings Volume 8522, 852219 (2012) https://doi.org/10.1117/12.964292

KEYWORDS: Photomasks, Photovoltaics, Optical proximity correction, Lithography, Electromagnetism, SRAF, Optical lithography, Nanoimprint lithography, Diffraction, Printing

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Proceedings Article | 8 November 2012 Paper

Backside defect printability for contact layer with different reticle blank material

Guoxiang Ning, Christian Holfeld, Daniel Fischer, Paul Ackmann, Andre Holfeld, Karin Kurth, Martin Sczyrba, Tino Hertzsch, Rolf Seltmann, Angeline Ho, Fang GN

Proceedings Volume 8522, 85221X (2012) https://doi.org/10.1117/12.958607

KEYWORDS: Critical dimension metrology, Semiconducting wafers, Reticles, Photomasks, Phase shifts, Binary data, Printing, Design for manufacturability, Manufacturing, Defect detection

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Proceedings Article | 30 June 2012 Paper

Tales of scales: how to enable backup process tool qualification for high-end photomasks

G. Cantrell, Christian Bürgel, Martin Sczyrba, Jan Heumann, Stefan Meusemann, Clemens Utzny

Proceedings Volume 8441, 844103 (2012) https://doi.org/10.1117/12.964671

KEYWORDS: Critical dimension metrology, Reticles, Photoresist processing, Photomasks, Principal component analysis, Inspection, Scanning electron microscopy, Spatial resolution, Lithography, Manufacturing

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Proceedings Article | 14 October 2011 Paper

Printability and detection of backside defects on photomasks

Guoxiang Ning, Christian Holfeld, Anna Tchikoulaeva, Martin Sczyrba, Angeline Ho, Karsten Bubke, Soon Yoeng Tan, Andre Holfeld, Byoung Il Choi

Proceedings Volume 8166, 81664D (2011) https://doi.org/10.1117/12.899127

KEYWORDS: Semiconducting wafers, Critical dimension metrology, Reticles, Particles, Photomasks, Inspection, Glasses, Defect detection, Manufacturing, Metals

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Reticles are contaminated during its lifetime and can catch particles as large as several tens of microns. Such defects on the backside of photomasks are usually considered as uncritical and thus do not receive much attention. Backside defects are out of focus by the mask thickness during wafer exposure and cannot be directly imaged on wafer. However, the shadow of the defects changes the local illumination of the mask patterns and may result in spatial variation of critical dimension (CD) on wafer depending on numerical aperture (NA) and pupil shape. There have been only a few investigations on printability of backside defects in the past, and no data are available for the most advanced technology nodes. Reticles are regularly inspected for particles on the glass side in the wafer fab but limits for acceptable defect size are based on estimations. Detection of non-acceptable particles causes exposed wafers being either delayed or reworked with impact on throughput and cost performance. It is therefore important to gain better understanding of critical sizes of backside defects and of appropriate detection capabilities. We have designed and manufactured a test mask with repeating patterns of 20nm, 28nm and 40nm technology node ranging from contact and line/space critical layers to non-critical implant layers. Programmed chrome defects of varying size are placed on the backside of the mask opposite to the repeating front side patterns in order to measure the spatial variation of transmission and wafer CD caused by the backside defects. The test mask was printed on a bare Silicon wafer and the size of printed features was measured by spatial sampling. Wafer CD variation for different backside defect sizes are demonstrated and compared for 28nm node first metal layer. Although the opaque chrome defects on the backside do not behave like real particles they aim on deriving a print threshold for backside particles based on actual wafer data. After such critical size of backside defects is obtained the reticle was also utilized to investigate the detection ability of backside defects by defect inspection of the reticle.

Proceedings Article | 19 May 2011 Paper

193-nm radiation durability study of MoSi binary mask and resulting lithographic performance

Isabelle Servin, Jérôme Belledent, Laurent Pain, Brid Connolly, Martin Sczyrba, Matt Lamantia

Proceedings Volume 8081, 80810X (2011) https://doi.org/10.1117/12.899173

KEYWORDS: Photomasks, Semiconducting wafers, Critical dimension metrology, Scanners, SRAF, Binary data, Lithography, Cadmium, Metrology, Scattering

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