Mr. Daniel I. Fiekowsky Profile

Daniel I. Fiekowsky

Engineering Manager

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Publications (5)

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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