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Proceedings of SPIE, the International Society for Optical Engineering | 2009

Aerial image based die-to-model inspections of advanced technology masks

Jun Kim; Wei-Guo Lei; Joan McCall; Suheil Zaatri; Michael Penn; Rajesh Nagpal; Lev Faivishevsky; Michael Ben-Yishai; Udy Danino; Aviram Tam; Oded Dassa; Vivek Balasubramanian; Tejas H. Shah; Mark Wagner; Shmoolik Mangan

Die-to-Model (D2M) inspection is an innovative approach to running inspection based on a mask design layout data. The D2M concept takes inspection from the traditional domain of mask pattern to the preferred domain of the wafer aerial image. To achieve this, D2M transforms the mask layout database into a resist plane aerial image, which in turn is compared to the aerial image of the mask, captured by the inspection optics. D2M detection algorithms work similarly to an Aerial D2D (die-to-die) inspection, but instead of comparing a die to another die it is compared to the aerial image model. D2M is used whenever D2D inspection is not practical (e.g., single die) or when a validation of mask conformity to design is needed, i.e., for printed pattern fidelity. D2M is of particular importance for inspection of logic single die masks, where no simplifying assumption of pattern periodicity may be done. The application can tailor the sensitivity to meet the needs at different locations, such as device area, scribe lines and periphery. In this paper we present first test results of the D2M mask inspection application at a mask shop. We describe the methodology of using D2M, and review the practical aspects of the D2M mask inspection.


Proceedings of SPIE, the International Society for Optical Engineering | 2009

Deployment of OASIS.MASK (P44) as direct input for mask inspection of advanced photomasks

Suheil Zaatri; Yan Liu; Michael Asturias; Joan McCall; Wei-Guo J. Lei; Tsafi Lapidot; Khen Ofek; Aviram Tam; Mark Wagner; Amanda Bowhill; Emile Sahouria; Minyoung Park; Neil DeBella; Pradiptya Ghosh; Steffen Schulze

With each new process technology node, chip designs increase in complexity and size, leading to a steady increase in data volumes. As a result, mask data prep flows require more computing resources to maintain the desired turn-around time (TAT) at a low cost. The effect is aggravated by the fact that a mask house operates a variety of equipment for mask writing, inspection and metrology - all of which, until now, require specific data formatting. An industry initiative sponsored by SEMI® has established new public formats - OASIS® (P39) for general layouts and OASIS.MASK (P44) for mask manufacturing equipment - that allow for the smallest possible representation of data for various applications. This paper will review a mask data preparation process for mask inspection based on the OASIS formats that also reads OASIS.MASK files directly in real time into the inspection tool. An implementation based on standard parallelized computer hardware will be described and characterized as demonstrating throughputs required for the 45nm and 32nm technology nodes. An inspection test case will also be reviewed.


Archive | 2006

System for detection of wafer defects

Dov Furman; Gad Neumann; Mark Wagner; Noam Dotan; Ram Segal; Shai Silberstein


Archive | 1999

Automatic defect classification with invariant core classes

Ariel Ben-Porath; Mark Wagner


Archive | 1996

Reliable defect detection using multiple perspective scanning electron microscope images

Mark Wagner; Noam Dotan


Archive | 2005

Method and apparatus for detecting defects in wafers

Erez Sali; Tomer Yanir; Mark Wagner; Noam Dotan; Yuval Dorfan; Ran Zaslavsky


Archive | 2005

Method and apparatus for detecting defects in wafers including alignment of the wafer images so as to induce the same smear in all images

Yuval Dorphan; Ran Zaslavsky; Mark Wagner; Dov Furman; Shai Silberstein


Archive | 2006

Apparatus for determining optimum position of focus of an imaging system

Dov Furman; Gad Neumann; Mark Wagner; Noam Dotan; Ram Segal; Shai Silberstein


Archive | 2007

Method and system for evaluating a variation in a parameter of a pattern

Michael Ben Yishai; Mark Wagner; Avishai Bartov; Gadi Greenberg; Lior Shoval; Ophir Gvirtzer


Archive | 2003

System for detection of water defects

Dov Furman; Gad Neumann; Mark Wagner; Noam Dotan; Ram Segal; Shai Silberstein

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