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Requirements for increasingly integrated metrology solutions continue to drive applications that incorporate process
characterization tools, as well as the ability to improve metrology production capability and cycle time, with a single
application. All of the most critical device layers today, along with even non-critical layers, now require optical
proximity correction (OPC), which must be rigorously modeled and calibrated as part of process development and
extensively verified once new product reticles are released using critical dimension-scanning electron microscopy (CD-SEM)
tools. Automatic setup of complex recipes is one of the major trends in CD-SEM applications, which is adding
much value to CD-SEM metrology. In addition, as integrated circuit dimensions continue to shrink, local line width
variation influences the statistical confidence of a measured CD's representation of the process. A feature, called
"Average CD (ACD)," measures multiple targets within the field of view (FOV). ACD allows not only measurements of
a single data point representing one discrete feature, but also sampling of the mean and variance of the process. These
two applications, automatic recipe creation and ACD, are combined in the second version of the DesignGauge software,
which is available for the latest-generation Hitachi S-9380II CD-SEMs. DesignGauge V2 is not only capable of offline
recipe creation and CD-SEM control, but it also has the ability to directly transfer design-based recipes into standard
CD-SEM recipes. These recipes can be used for OPC model-building and verification as with previous DesignGauge
applications. The software also provides design template-based recipe setup for production layer recipes, which yields
much needed improvement to production tool utilization, as production recipes can thus be written offline for new
products, improving first silicon cycle time, reducing engineering time required to generate recipes, and improving CD-SEM
utilization. Another benefit of the application is an improvement in recipe robustness over conventional direct
image-based pattern recognition. This work will show an extensive evaluation of DesignGauge V2, including rigorous
tests of navigation, pattern recognition success rates, SEM image placement, throughput of recipe creation, and recipe
execution. The impact of ACD will also be evaluated.
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