This article presents results from an algorithm that can automatically quantify critical dimensions in images
from Mask inspection tools with a very high level of accuracy. Using such an algorithm the inspection
systems can be run with much tighter settings, resulting in more false defect detections that can then be
filtered using the algorithm described here. Such a technique could potentially make the inspection system
suitable for inspecting photo-masks beyond its practical limitation.
The Critical Dimension Uniformity (CDU) specification on photomasks continues to decrease with each successive node.
The ITRS roadmap for optical masks indicates that the CDU (3 sigma) for dense lines on binary or attenuated phase shift
mask is 3.4nm for the 45nm half-pitch (45HP) node and will decrease to 2.4nm for the 32HP node. The current
capability of leading-edge mask shop patterning processes results in CDU variation across the photomask of a similar
magnitude.
Hence, we are entering a phase where the mask CDU specification is approaching the limit of the capability of the
current Process of Record (POR). Mask shops have started exploring more active mechanisms to improve the CDU
capability of the mask process. A typical application is feeding back the CDU data to adjust the mask writer dose to
compensate for non-uniformity in the CDs, resulting in improved quality of subsequent masks. Mask makers are
currently using the CD-SEM tool for this application. While the resolution of SEM data ensures its position as the
industry standard and continued requirement to establish the photomask CD Mean to Target value, a dense measurement
of CDs across the reticle with minimal cycle time impact would have value.
In this paper, we describe the basic theory and application of a new, reticle inspection intensity-based CDU approach
that has the advantage of dense sampling over larger areas on the mask. The TeraScanHR high NA reticle inspection
system is used in this study; it can scan the entire reticle at relatively high throughput, and is ideally suited for collecting
dense CDU data. We describe results obtained on advanced memory masks and discuss applications of CDU maps for
optimizing the mask manufacturing process. A reticle inspection map of CDU is complementary to CD-SEM data. The
dense data set has value for various applications, including feedback to mask writer and engineering analysis within the
mask shop.
Conventional photomask inspection techniques utilize global sensitivity for all inspected area in the die; SRAF and OPC
features become the sensitivity-limiters for advanced photomasks which can result in reduced sensitivity to defects of
interest (DOI). We describe the implementation of Sensitivity Control Layer (SCL), a novel database inspection
methodology for the KLA-Tencor TerascanHR platform to improve sensitivity and reduce nuisance detections. This
methodology enables inspection at maximum sensitivity in critical die-areas via "layer definition" and reducing
sensitivity to sub-resolution features during inspection which can dramatically improve false-rate. DRAM and FLASH
inspection performance was improved through the use of up to 6-control layers to increase sensitivity in the active area
while reducing false detections by as much as 100X. Post-inspection defect analysis, and improved disposition accuracy
of the SCL-enabled inspections will also benefit cycle time and higher throughput. In all test cases, sensitivity
parameters were increased in the regions of interest over baseline inspections run with typical, production-type
inspection methodologies. SCL inspection-sensitivity management, and layer partitioning of OPC structures, SRAF's,
and other sub-resolution features is discussed in detail.
Conventional photomask inspection techniques utilize global sensitivity for all inspected area in the die; SRAF and OPC
features become the sensitivity-limiters, which can result in reduced visibility to defects of interest (DOI). We describe
the implementation of Sensitivity Control Layer (SCL), a novel database inspection methodology for the KLA-Tencor
TerascanHR platform. This methodology enables inspection at maximum sensitivity in critical die-areas via "layer
definition" during job set-up and sensitivity management of the layers during inspection. Memory device inspection
performance was improved through the use of up to six control layers to increase sensitivity in the active area while
reducing nuisance detections by as much as 100X. The corresponding inspection time was reduced by 30%, illustrating
the potential for substantial throughput advantage using SCL. Post-inspection analysis and improved disposition
accuracy of the SCL-enabled inspections will also benefit cycle time and higher throughput. In all test cases, sensitivity
parameters were increased in the regions of interest over baseline inspections run with typical production-use
methodologies. SCL inspection management and application on OPC structures, SRAFs, and MRC violations (slivers)
are discussed in detail.
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