Mr. Peter J. Fiekowsky Profile

Peter J. Fiekowsky

President at AVI-Photomask

SPIE Involvement:

Author

Publications (19)

Proceedings Article | 21 April 2016 Paper

Improving reticle defect disposition via fully automated lithography simulation

Raunak Mann, Eliot Goodman, Keith Lao, Steven Ha, Anthony Vacca, Peter Fiekowsky, Dan Fiekowsky

Proceedings Volume 9778, 97783U (2016) https://doi.org/10.1117/12.2230847

KEYWORDS: Reticles, Semiconducting wafers, Inspection, Photomasks, Scanners, Lithography, Optical proximity correction, Feature extraction, Databases, Critical dimension metrology, Defect inspection

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Most advanced wafer fabs have embraced complex pattern decoration, which creates numerous challenges during in-fab reticle qualification. These optical proximity correction (OPC) techniques create assist features that tend to be very close in size and shape to the main patterns as seen in Figure 1. A small defect on an assist feature will most likely have little or no impact on the fidelity of the wafer image, whereas the same defect on a main feature could significantly decrease device functionality. In order to properly disposition these defects, reticle inspection technicians need an efficient method that automatically separates main from assist features and predicts the resulting defect impact on the wafer image. Analysis System (ADAS) defect simulation system[1]. Up until now, using ADAS simulation was limited to engineers due to the complexity of the settings that need to be manually entered in order to create an accurate result. A single error in entering one of these values can cause erroneous results, therefore full automation is necessary. In this study, we propose a new method where all needed simulation parameters are automatically loaded into ADAS. This is accomplished in two parts. First we have created a scanner parameter database that is automatically identified from mask product and level names. Second, we automatically determine the appropriate simulation printability threshold by using a new reference image (provided by the inspection tool) that contains a known measured value of the reticle critical dimension (CD). This new method automatically loads the correct scanner conditions, sets the appropriate simulation threshold, and automatically measures the percentage of CD change caused by the defect. This streamlines qualification and reduces the number of reticles being put on hold, waiting for engineer review. We also present data showing the consistency and reliability of the new method, along with the impact on the efficiency of in-fab reticle qualification.

Proceedings Article | 23 October 2015 Paper

Automatic classification and defect verification based on inspection technology with lithography simulation

Masaya Kato, Hideki Inuzuka, Takeshi Kosuge, Shingo Yoshikawa, Kayoko Kanno, Hidemichi Imai, Hiroyuki Miyashita, Anthony Vacca, Peter Fiekowsky, Dan Fiekowsky

Proceedings Volume 9635, 96351W (2015) https://doi.org/10.1117/12.2197814

KEYWORDS: Photomasks, Inspection, Critical dimension metrology, Opacity, Lithography, Semiconducting wafers, Source mask optimization, Reticles, Optical proximity correction, Bridges

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Proceedings Article | 20 October 2014 Paper

Increasing reticle inspection efficiency and reducing wafer printchecks at 14nm using automated defect classification and simulation

Shazad Paracha, Eliot Goodman, Benjamin Eynon, Ben Noyes, Steven Ha, Jong-Min Kim, Dong-Seok Lee, Dong-Heok Lee, Sang-Soo Cho, Young Ham, Anthony Vacca, Peter Fiekowsky, Daniel Fiekowsky

Proceedings Volume 9235, 92350Q (2014) https://doi.org/10.1117/12.2070256

KEYWORDS: Inspection, Reticles, Semiconducting wafers, Photomasks, Bridges, Modulation, Lithography, Scanning electron microscopy, Classification systems, Polarization

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Proceedings Article | 2 April 2014 Paper

Improved reticle requalification accuracy and efficiency via simulation-powered automated defect classification

Shazad Paracha, Benjamin Eynon, Ben Noyes, Anthony Nhiev, Anthony Vacca, Peter Fiekowsky, Dan Fiekowsky, Young Mog Ham, Doug Uzzel, Michael Green, Susan MacDonald, John Morgan

Proceedings Volume 9050, 905031 (2014) https://doi.org/10.1117/12.2048622

KEYWORDS: Reticles, Semiconducting wafers, Inspection, Photomasks, Classification systems, Scanning electron microscopy, Critical dimension metrology, Error analysis, Wafer testing, Defect detection

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Proceedings Article | 1 October 2013 Paper

Increasing reticle inspection efficiency and reducing wafer print-checks using automated defect classification and simulation

Sung Jae Ryu, Sung Taek Lim, Anthony Vacca, Peter Fiekowsky, Dan Fiekowsky

Proceedings Volume 8880, 88800D (2013) https://doi.org/10.1117/12.2028275

KEYWORDS: Inspection, Reticles, Semiconducting wafers, Photomasks, Contamination, Lithography, Defect inspection, Inspection equipment, Scanners, Yield improvement

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Proceedings Article | 14 October 2011 Paper

Electron beam EUV patterned mask inspection system

Keizo Yamada, Yasunobu Kitayama, Peter Fiekowsky

Proceedings Volume 8166, 81662W (2011) https://doi.org/10.1117/12.896971

KEYWORDS: Inspection, Photomasks, Extreme ultraviolet, Deep ultraviolet, Electron beams, Sensors, Holons, Defect detection, Extreme ultraviolet lithography, Computer aided design

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Proceedings Article | 17 October 2008 Paper

Auto-classification and simulation of mask defects using SEM and CAD images

Tung-Yaw Kang, Hsin-Chang Lee, H. Zhang, K. Yamada, Y. Kitayama, K. Kobayashi, Peter Fiekowsky

Proceedings Volume 7122, 71221F (2008) https://doi.org/10.1117/12.801411

KEYWORDS: Inspection, Photomasks, Scanning electron microscopy, Computer aided design, Semiconducting wafers, Printing, Defect detection, Defect inspection, Holons, Lithography

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Proceedings Article | 1 November 2007 Paper

Automating defect disposition in fabs and maskshops

Peter Fiekowsky, S. Narukawa, T. Kawashima

Proceedings Volume 6730, 67303R (2007) https://doi.org/10.1117/12.747268

KEYWORDS: Inspection, Photomasks, Statistical analysis, Defect detection, Defect inspection, Critical dimension metrology, Contamination, Crystals, Binary data, Optical inspection

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Proceedings Article | 20 October 2006 Paper

Defining defect specifications to optimize photomask production and requalification

Peter Fiekowsky

Proceedings Volume 6349, 63493R (2006) https://doi.org/10.1117/12.706646

KEYWORDS: Photomasks, Inspection, Semiconducting wafers, Image transmission, Error analysis, Computer simulations, Printing, SRAF, Process control, Critical dimension metrology

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Proceedings Article | 28 June 2005 Paper

An automated mask defect analysis system for increasing mask shop productivity

Peter Fiekowsky, Christopher Lewis, Andy McDonald

Proceedings Volume 5853, (2005) https://doi.org/10.1117/12.617339

KEYWORDS: Inspection, Photomasks, Data processing, Defect detection, Semiconducting wafers, Defect inspection, Process engineering, Yield improvement, Computing systems, Classification systems

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Proceedings Article | 16 August 2002 Paper

Measuring and assessing printability of reticle pinhole defects

Darren Taylor, Anthony Vacca, Larry Zurbrick, William Broadbent, Peter Fiekowsky

Proceedings Volume 4764, (2002) https://doi.org/10.1117/12.479355

KEYWORDS: Reticles, Scanning electron microscopy, Inspection, Semiconducting wafers, Manufacturing, Photomasks, Metrology, Inspection equipment, Calibration, Optics manufacturing

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Proceedings Article | 5 September 2001 Paper

Mask defect disposition: flux-area measurement of edge, contact, and OPC defects correlates to wafer and enables effective decisions

Peter Fiekowsky, Darren Taylor, David Wang, Chien-Chu Yang, Shu-Chun Lin, L. Tu, K. Lin

Proceedings Volume 4409, (2001) https://doi.org/10.1117/12.438329

KEYWORDS: Photomasks, Semiconducting wafers, Optical proximity correction, Metrology, Scanning electron microscopy, Optical testing, Scanners, Lithography, Defect detection, Calibration

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Proceedings Article | 5 September 2001 Paper

New optical metrology for masks: range and accuracy rivals SEM

Rand Cottle, Peter Fiekowsky, C. Hung, Sheng-che Lin

Proceedings Volume 4409, (2001) https://doi.org/10.1117/12.438380

KEYWORDS: Scanning electron microscopy, Photomasks, Metrology, Optical testing, Deep ultraviolet, Semiconducting wafers, Wafer-level optics, Optics manufacturing, Calibration, Optical metrology

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Proceedings Article | 5 September 2001 Paper

Contact holes: optical area measurement predicts printability and is highly repeatable

Glen Scheid, Darren Taylor, Peter Fiekowsky

Proceedings Volume 4409, (2001) https://doi.org/10.1117/12.438330

KEYWORDS: Photomasks, Semiconducting wafers, Scanning electron microscopy, Optical testing, Wafer-level optics, Metrology, Critical dimension metrology, Reticles, Optical proximity correction, Visible radiation

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Proceedings Article | 22 January 2001 Paper

Soft defect printability: correlation to optical flux-area measurements

Darren Taylor, Peter Fiekowsky

Proceedings Volume 4186, (2001) https://doi.org/10.1117/12.410746

KEYWORDS: Photomasks, Semiconducting wafers, Inspection, Optical spheres, Optical testing, Reticles, 3D image processing, Printing, Wafer-level optics, Contamination

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Proceedings Article | 19 July 2000 Paper

End of thresholds: subwavelength optical linewidth measurement using the flux-area technique

Peter Fiekowsky

Proceedings Volume 4066, (2000) https://doi.org/10.1117/12.392075

KEYWORDS: Photomasks, Scanning electron microscopy, Optical testing, Metrology, Visible radiation, Critical dimension metrology, Image resolution, Wafer-level optics, Opacity, Semiconducting wafers

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Proceedings Article | 30 December 1999 Paper

Defect printability measurement on the KLA-351: correlation to defect sizing using the AVI metrology system

Peter Fiekowsky, Daniel Selassie

Proceedings Volume 3873, (1999) https://doi.org/10.1117/12.373371

KEYWORDS: Scanning electron microscopy, Photomasks, Semiconducting wafers, Metrology, Inspection, Critical dimension metrology, Microscopes, Reticles, Optical testing, Visible radiation

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Proceedings Article | 12 February 1997 Paper

Accurate and repeatable mask defect measurements for quarter-micron technology

Peter Fiekowsky

Proceedings Volume 3236, (1997) https://doi.org/10.1117/12.301208

KEYWORDS: Photomasks, Atomic force microscopy, Microscopes, Scanning electron microscopy, Visible radiation, Opacity, Image transmission, Optical testing, Image resolution, Optical inspection

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A highly repeatable and accurate mask defect measurement has been developed. Defects from 0.1 to 1.5 microns in diameter are measured by computing the total light absorbed or transmitted by a defect. RMS repeatability of better than 9 nanometers on 0.4 micron defects has been achieved. Reliable measurement of defect size is important for developing lithography technologies for smaller geometries, and for commercial mask production. As mask feature sizes have dropped below the wavelength of visible light, getting reliable defect size measurement has become nearly impossible. Even scanning electron microscope (SEM) and atomic force microscope (AFM) measurements have not yet proven reliable even though they provide resolutions down to a few nanometers. This technique of measuring flux absorption or transmission allows reliable measurement of defects that are several times smaller than the wavelength of light used to examine them, with repeatability of 2 - 10 nanometers, depending on the image source. Transmitted light images are acquired from KLA-3xx, Starlight, KLA-219, DRS-1, DRS-2, or other video microscopes. Then the amount of light flux absorbed (by a spot or chrome extension), or transmitted (by a hole or clear intrusion) is measured. That change in flux is converted to an area, which can then be converted to a diameter. This system is currently in use in several large mask shops. It promises to be a powerful QA and analysis tool for developing masks for .25 micron and smaller geometries. Accuracy and repeatability tests have been performed on reference defects on Dupont VeriMasks, and using PSL spheres. Repeatability is limited by vibration of the image and by pixel artifacts in the images from KLA-3xx machines. Accuracy cannot be objectively assessed because there is no 'NIST traceable' reference for defect sizes. However, chrome defect size appears to be linearly correlated to absorbed or transmitted flux, as one would expect from the physics, so defect area accuracy is expected to be similar to the repeatability, around 10 nanometers. This technique does not easily provide separate x- and y- dimensions for non-round defects smaller than the wavelength of light used in the microscope (typically 0.5 micron). Larger defects can be measured in two dimensions using conventional techniques, and Fourier transform techniques can be used to provide useful estimates of x- and y- dimensions of smaller defects.

Proceedings Article | 21 May 1996 Paper

Practical and precise method for mask defect size measurement

Steve George, Peter Fiekowsky

Proceedings Volume 2725, (1996) https://doi.org/10.1117/12.240082

KEYWORDS: Calibration, Inspection, Defect inspection, Video, Photomasks, Image processing, Cameras, Optical filters, Opacity, Imaging systems

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Showing 5 of 19 publications

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