When something happens to a reticle, the consequences can be dire. Contamination in the wrong place on a reticle can result in a defect in every die of every wafer. Fabs have to keep their reticles clean.
On the other hand, if the reticle is cleaned too many times, the pattern can start to erode. Reticle pattern degradation eventually causes critical dimension uniformity (CDU) changes on the wafer, which can translate into issues of device performance or yield. Plus, while the reticle is going through the cleaning process, it’s not available to do its work in the scanner. Unless reticle cleaning is carefully planned, production of that particular product may screech to a halt. Fabs need to check their reticles for contamination and pattern degradation—at a frequency that balances the cost of taking the reticle offline to inspect it and the cost of the inspection itself against the risk of printing reticle defects or CDU errors on the wafer.
Some fabs have moved their reticle cleaning facilities on site, greatly accelerating the turnaround time to get the reticle cleaned, re-inspected, and back online. New cleaning technologies have also come into favor, including wet processes like UV-ozonated water with hydrogen peroxide, and dry processes including plasma and laser shot cleaning. In general the new processes have resulted in reduced overall defectivity post-clean; however, the problem of pattern erosion remains, and the remaining defects can be more difficult to detect.
Recent studies1 have shown that contamination is more likely to occur at the edges of mask pattern features than in open areas between features. That’s bad news for the wafers, because a variation on the edge of the mask pattern will immediately affect the carefully engineered wavefronts of the light that transfers the mask pattern to the photoresist on the wafer. It’s also bad news for the reticle defect inspectors, because it’s much more difficult to detect a defect in an area of dense pattern than a defect the same size, sitting in the middle of an unused space. Also, the mask error enhancement factor (MEEF) of a defect within dense pattern is higher than that of a defect in open space—which means that the defect within the pattern is more likely to print on the wafer and more likely to affect die yield. It may be difficult to find defects on the edge of pattern, but these defects have the potential to be the most damaging. They must be found.
In the mask shop, reticle inspection is accomplished by comparing the pattern on the mask to the design information—a “die-to-database” inspection. In the IC fab, the mask database is often not available. For that reason, KLA-Tencor invented a database-free method for detecting contamination on a mask, a method called STARlightTM, named for its use of Simultaneous Transmitted And Reflected light. First introduced in 1995, the STARlight methodology2 compares the transmitted-light and reflected-light images of a reticle to determine whether or not a defect is present. Since then, STARlight has undergone many improvements, and today’s fifth-generation STARlight is optimized for detecting defects on edges of pattern features.
1. STARlight operated on the simultaneous transmitted (left) and reflected (middle) image to identify the defect (right).
STARlight addresses the issue of finding localized contaminants, even on pattern edges. It works for single-die, multi-die or shuttle masks (multi-die masks comprised of different die), inspecting any kind of random or repeating pattern—including the scribe line. Once these defects are found, the reticle can be cleaned and re-used. But what happens when the cleaning process is modifying or removing pattern—material that’s supposed to be there—instead of contaminants? Or what if the problem is not localized contamination, but a contaminating film that affects the reticle’s transmissivity? These issues may not create defects on the wafer, but they may affect the wafer’s CDU.
Some inspection systems now offer a mode that maps the reflectivity or transmissivity across the entire reticle. In some cases, these data are collected simultaneously with localized defect data. The reticle maps can then be processed and calibrated against a reference to extract CDU information.
2. Examples of intensity-based CDU maps from the reticle inspection system.
3. Degradation of a sub-resolution assist feature (SRAF), imaged by the reticle inspection system.
With the introduction of new cleaning processes and smaller pattern features, reticle management in the IC fab has extended beyond detection of localized defects to include detection of contaminating films and CDU changes. With thoughtful sampling strategies, regularly inspected reticles can live long, productive lives.
Rebecca Howland, Ph.D., is a senior director in the corporate group and Mark Wylie is a product marketing manager in the Reticle Products Division at KLA-Tencor.
Check out other Process Watch articles: “The Dangerous Disappearing Defect,” “Skewing the Defect Pareto,” “Bigger and Better Wafers,” “Taming the Overlay Beast,” “A Clean, Well-Lighted Reticle,” “Breaking Parametric Correlation,” “Cycle Time’s Paradoxical Relationship to Yield,” and “The Gleam of Well-Polished Sapphire.”
References
1. E. Foca, A. Tchikoulaeva, B. Sass, C. West, P. Nesladek, R. Horn, “New type of haze formation on masks fabricated with Mo-Si blanks,” Photomask Japan 2010.
2. F. Kalk, D. Mentzer, A. Vacca, “Photomask production integration of KLA STARlight 300 system,” Proc. SPIE 2621, 15th Annual BACUS Symposium on Photomask Technology and Management 112 (1995).