Measurement Sampling Frequency Impact on Determining Magnitude of Pattern Placement Errors on Photomasks J. Whitteya, F. Laskea, K.-D. Roetha, J. McCormacka, D. Adama, J. Bendera C. N. Berglundb, M. Takacb, Seurien Chouc a KLA Tencor MIE GmbH, Kubacher Weg 4, 35781 Weilburg, Germany b Northwest Technology Group Consulting, Inc., 16505 A SE 1st Street, Vancouver, WA 98684, USA c Synopsis, Inc., 700E Middlefield Road, Mountain View, CA 94043, USA ABSTRACT Current methodologies for determining pattern placement errors on production masks are based primarily on limited sample sizes and Gaussian statistics. These methodologies and accepted practices may not be indicative of the true nature of pattern placement errors actually occurring on the photomasks. Pattern placement errors can originate from a variety of sources on e-beam generated photomasks. Random shot placement errors, localized charging and heating, proximity effects, global charging, and writing strategies may all have an impact on overall pattern placement errors. It is suspected therefore that pattern placement errors on photomasks are not all well approximated as Gaussian, but include a number of significant errors with unique spatial signatures that need to be addressed differently. This paper investigates different measurement sampling strategies on a single leading edge poly layer to determine what level or amount of measurements might be necessary to more accurately determine the probabilities of the true placement errors on the photomask, and what spatially dependent components may or may not be accurately represented in the measurements. Keywords: Mask metrology, registration, sampling, overlay, yield
Introduction In collaboration with a leading edge captive mask manufacturer pattern placement performance of a poly layer reticle was measured using different sampling strategies to ascertain whether current methodologies for measuring pattern placement errors are truly indicative of the real placement errors that can occur on a mask. An adaptive metrology technique was employed based on arrays with different pitches that captures successively small and smaller areas depending on the errors detected in larger area sampling plans. Measurements were performed using KLA-Tencor’s LMS IPRO4 on actual in-die features at thousands of locations across the reticle. Typically photomasks today are dispositioned using a 3 sigma value for X and Y placement errors based on an approximate range of thirty to three hundred measurement points. Often times these measurement points are registration targets located in the scribe of the exposure field on the reticle. Depending on writing strategies, local charging, pattern densities, stripe field boundaries, plate flatness, noise, chucking and other effects, the measured features in the scribe are often times not indicative of the errors within the exposure field itself 1 . The simplified error budget model shown in figure 1 illustrates some of the issues involved, where we have divided the error sources into three categories – random errors, spatially systematic errors that are slowly varying across the reticle (low spatial), and spatially systematic errors that are short range in nature (high spatial). Starting at the 32nm node more detailed registration evaluations should be performed to ensure minimum impact from the reticle to wafer overlay yield. This discrepancy in reported errors or the probability of additional errors may lead to yield loss in manufacturing depending on the particular layer combinations6. Detected errors on the photomask measured for this paper were a combination of random and systematic errors. Given the magnitude of the systematic errors the question arises as to whether today’s sampling strategies and the employment of Gaussian statistics are the correct way to disposition product reticles. The goal of pattern placement metrology is to accurately estimate the probability of the true nature and Photomask Technology 2009, edited by Larry S. Zurbrick, M. Warren Montgomery, Proc. of SPIE Vol. 7488, 74881I · © 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.833495
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