Results from the KLA-Tencor TeraScanXR reticle inspection tool

Dayal, Aditya; Mu, Bo; Iyer, Venkat; Lim, Phillip; Goonesekera, Arosha; Broadbent, Bill

doi:10.1117/12.801831

Cited by 3 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, for an inspection with pixel size, p and sensitivity S, we shall model resolution as shown in (15) for both CD and contamination defects. Current inspection tools are capable of inspecting a 20-nm defect (on the mask), which corresponds to 5 nm on the wafer (MEEF=1) at a pixel size of 55 nm and sensitivity of 100 [3]. Hence, we take K c ≈ 9 for our experiments 8 as follows:…”

Section: A Resolutionmentioning

confidence: 99%

“…There are three potential methods of accounting for MEEF in criticality assignment, which we shall explore further in Section VI. 1) Rely on modern inspection tools that support adaptive thresholding, i.e., the threshold value is dynamically changed by the tool depending on online MEEF estimation [3]. In this case, we can choose MEEF=1 since the inspection tool can adjust for it.…”

Section: Criticality Assignmentmentioning

confidence: 99%

“…The inverse of this threshold is referred to as sensitivity. These tools can have a pixel size as low as 55 nm and can detect critical dimension (CD) defects as small as 20 nm on the mask at maximum sensitivity (minimum threshold) [3].…”

Section: A Mask Inspection Primermentioning

confidence: 99%

“…Now since CD and contamination defects are flagged using different algorithms whose sensitivity can be set independently [3], we calculate false defects reported by the two methods separately to get the overall false defect count of the inspection tool as follows:…”

Section: A Resolutionmentioning

confidence: 99%

“…Initially, the reticle is passed through an inspection tool such as KLA-Tencor's Terascan [3] or NEC's LM series [4] that takes an image of die on the mask and compares it to a reference database or another die (die-database or die-die modes). The difference between the two image intensities is found and if the difference exceeds a predefined threshold, the difference pattern is labeled a defect.…”

Section: A Mask Inspection Primermentioning

confidence: 99%

See 4 more Smart Citations

Design-Aware Mask Inspection

Kagalwalla

Gupta

Progler

et al. 2012

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

Abstract-Mask inspection has become a major bottleneck in the manufacturing flow taking up as much as 40% of the total mask manufacturing time. In this paper, we explore techniques to improve the reticle inspection flow by increasing its design awareness. We develop an algorithm to locate nonfunctional features in a postoptical proximity correction layout without using any design information. Using this, and the timing information of the design (if available), the smallest defect size that could cause the design to fail is assigned to each reticle feature. The criticality of various reticle features is then used to partition the reticle such that each partition is inspected at a different pixel size and sensitivity so that the false and nuisance defect count is reduced without missing any critical defect. We also develop an analytical model to estimate the false and nuisance defect count. Using those models, our simulation results show that this designaware mask inspection can reduce the false and nuisance defect count for a critical polysilicon layer from 80 defects down to 49 defects, leading to substantial reduction in defect review load. We also develop a model to estimate first pass yield (FPY) and show that our method can improve the FPY for a polysilicon layer from 11% to 30%. Apart from the polysilicon layer, the potential benefit of this approach is analyzed for active, contact and all the metal/via layers.Index Terms-Computer-aided design (CAD), design for manufacturability (DFM), mask inspection, mask manufacturing, reticle, semiconductor manufacturing.

show abstract

Section: A Resolutionmentioning

confidence: 99%

Section: Criticality Assignmentmentioning

confidence: 99%

Section: A Mask Inspection Primermentioning

confidence: 99%

Section: A Resolutionmentioning

confidence: 99%

Section: A Mask Inspection Primermentioning

confidence: 99%

See 3 more Smart Citations

Design-Aware Mask Inspection

Kagalwalla

Gupta

Progler

et al. 2012

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

show abstract

Critical dimension uniformity using reticle inspection tool

et al. 2009

View full text Add to dashboard Cite

An analysis of correlation between scanning direction and defect detection at ultra high resolution

et al. 2010

View full text Add to dashboard Cite

As the design rule of wafer has been shrinking, the patterns on the mask also need to be getting smaller and even smaller for some sub-resolution assist features, which makes mask inspection process need a high resolution (HR) inspection systems. For this HR mask inspection, most mask inspector makers adopt a TDI(Time Delay & Integration) sensor to enhance acquired image quality with the acceptable scan speed, thus, to minimize the inspection cost. However, even TDI sensor may not get a sufficient gray level of pattern image for the most advanced mask patterns. Furthermore, it might generate some false defects depending on the pattern shape and scan direction (in combination with pattern direction). We manufactured two programmed defect masks (PDM); one is a ArF EPSM and another is a EUV mask. By inspecting these masks with perpendicular scan directions, respectively, we evaluated the correlation between scan direction and defect size/shape experimentally. We found that the inspection with the parallel direction to pattern direction can increase the inspectability for the patterns and the defect sensitivity since this helps to enhance signal to noise ratio from the TDI sensor. Our analysis can increase sensitivity of TDI sensor effectively without any additional hardware modification.

show abstract

Results from the KLA-Tencor TeraScanXR reticle inspection tool

Cited by 3 publications

References 4 publications

Design-Aware Mask Inspection

Design-Aware Mask Inspection

Critical dimension uniformity using reticle inspection tool

An analysis of correlation between scanning direction and defect detection at ultra high resolution

Contact Info

Product

Resources

About