The ORIONTM series of test reticles have been used for many years as the photomask industry standard for evaluating contamination inspection algorithms. The deposition of Polystyrene Latex (PSL) spheres on various reticle pattern
designs allow STARlightTM tool owners to measure the relative contamination inspection performance in a consistent and quantifiable manner. However, with recent inspection technology advances such as shorter laser (light source)
wavelengths and smaller inspection pixels, PSL spheres were observed to physically degrade over relatively short time
periods: especially for the smallest sized spheres used to characterize contamination inspection performance at the most
advanced technology nodes.
Investigations into using alternative materials or methods that address the issue of PSL shrinkage have not yet proven
completely successful. Problems such as failure to properly adhere to reticle surfaces or identification of materials that
can produce consistent and predictable sphere sizes for the reliable manufacture of these critical test masks are only some
of the challenges that must be solved. Even if these and other criteria are met, the final substance must appear to
inspection optics as pseudo soft defects which resemble actual contamination that inevitably appears on production
reticle surfaces.
In the interim, programmed pindot defects present in the quartz region of the SPICATM test reticle are being used to characterize contamination performance while a suitable long-term solution to address the issue of shrinking PSL
spheres on ORION masks can be found. This paper examines the results of a programmed pindot test reticle specifically
designed to evaluate contamination algorithms without the deposition of PSL spheres or similar structures. This
alternative programmed pindot test reticle uses various background patterns similar to the ORION, however, it also
includes multiple defects sizes and locations making it more desirable than the limited range of defects found on the
SPICA.
Mask Manufacturing Rules Checking (MRC) has been established as an automated process to detect mask pattern data
that will cause mask inspection problems. This methodology is unique from the Design Rule Checking (DRC) or
Design for Manufacturing (DFM) checks typically performed before sending pattern data to the mask manufacturer in
that it examines the entire mask layout and the spatial relationship between multiple patterns in their final orientation,
scale, and tone. In contrast, DRC and DFM checks are usually performed on individual pattern files. Also, DRC and
DFM checks are not always performed after all pattern transformations are complete, and errors can be introduced that
are not caught until the mask is eventually printed on wafers. Therefore, MRC can often be the only comprehensive
geometric integrity test performed before the mask is manufactured and the last opportunity to catch critical errors that
might have disastrous consequences to yield and consequently to product schedules.
In this paper we review the concepts and implementation of MRC in a merchant mask manufacturing enterprise and
introduce methods to empower DFM decisions by mask customers based on MRC results.
Advanced electronic design automation (EDA) tools, with their simulation, modeling, design rule checking, and optical proximity correction capabilities, have facilitated the improvement of first pass wafer yields. While the data produced by these tools may have been processed for optimal wafer manufacturing, it is possible for the same data to be far from ideal for photomask manufacturing, particularly at lithography and inspection stages, resulting in production delays and increased costs. The same EDA tools used to produce the data can be used to detect potential problems for photomask manufacturing in the data.
In the previous paper, it was shown how photomask MRC is used to uncover data related problems prior to automated defect inspection. It was demonstrated how jobs which are likely to have problems at inspection could be identified and separated from those which are not. The use of photomask MRC in production was shown to reduce time lost to aborted runs and troubleshooting due to data issues.
In this paper, the effectiveness of this photomask MRC program in a high volume photomask factory over the course of a year as applied to more than ten thousand jobs will be shown. Statistics on the results of the MRC runs will be presented along with the associated impact to the automated defect inspection process. Common design problems will be shown as well as their impact to mask manufacturing throughput and productivity. Finally, solutions to the most common and most severe problems will be offered and discussed.
Advanced electronic design automation (EDA) tools, with their simulation, modeling, design rule checking, and optical proximity correction capabilities, have facilitated the improvement of first pass wafer yields. While the data produced by these tools may have been processed for optimal wafer manufacturing, it is possible for the same data to be far from ideal for photomask manufacturing, particularly at lithography and inspection stages, resulting in production delays and increased costs. The same EDA tools used to produce the data can be used to detect potential problems for photomask manufacturing in the data.
A production implementation of automated photomask manufacturing rule checking (MRC) is presented and discussed for various photomask lithography and inspection lines. This paper will focus on identifying data which may cause production delays at the mask inspection stage.
It will be shown how photomask MRC can be used to discover data related problems prior to inspection, separating jobs which are likely to have problems at inspection from those which are not. Photomask MRC can also be used to identify geometries requiring adjustment of inspection parameters for optimal inspection, and to assist with any special handling or change of routing requirements. With this foreknowledge, steps can be taken to avoid production delays that increase manufacturing costs. Finally, the data flow implemented for MRC can be used as a platform for other photomask data preparation tasks.
The inspectability of advanced OPC plates has been verified by successfully completing inspections of photomasks that have OPC throughout the design. The photomasks tested have varying OPC design strategies and degrees of OPC complexity. The defect capture ability has been characterized with classical verification masks like the DuPont Verithoro, and OPC programmed defect test reticle called OPC3, and defect capture occurrences on actual design with advanced OPC features. Printability simulations and test have indicated that mis-sized serifs can be a critical, printable defect class. Inspection results from the 750 nm primary feature size section of the OPC3 test reticle with 0.25 micrometers pixel indicate better than 0.25 micrometers sensitivity to oversized serif defects, better than 0.30 micrometers sensitivity to undersized serifs, and better than 0.21 micrometers sensitivity to misplaced serif line ends. Historically, small defects on OPC structures such as mis-sized serifs could be easily misclassified as a false defect by inspection operators. Defect review software was upgraded to improve the visualization and sizing of defects on OPC structures.
Advanced optical proximity correction (OPC) designs have resulted in many challenges for both the manufacturers of photomasks and automated defect inspection equipment. The successful manufacture of advanced OPC photomasks includes the ability to resolve the OPC features, complete an automated defect inspection that captures all of the defects of concern, and accurately recognize and disposition these defects. New defect types associated with OPC features are important and will print on a wafer or affect critical feature dimensions. Advances in defect detection on designs with OPC required breakthroughs by both the photomask and inspection system manufacturer. Process improvements focused on better resolving OPC features, along with advancements in automated defect inspection systems, have resulted in overall improvements in automated defect infection capability for OPC designs. The ability of OPC inspection algorithms to detect critical defects was confirmed with the DuPont VerithoroTM 890, the OPC3 programed defect test reticle, and defect capture occurrences on actual designs with advanced OPC features. Sensitivity improvements of up to 0.17 micrometer were demonstrated for both OPC and non-OPC type defects.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.