In the photomask manufacturing industry, producing defect-free photomasks is a significant challenge. The processes of defect inspection, repair, and metrology are employed to ensure masks are defect-free. Within this process flow, the Aerial Image Measurement System (AIMS) metrology tool is widely used as the industry’s benchmark for evaluating defect printing impact and determining if a suspected defect requires repair. However, in the mature node photomask manufacturing, the product quantity is large, and the AIMS 248™ loading is heavy, sometimes doing AIMS review for all defects is expensive and time consuming. Thus, a fast, accurate, and economical method is desired which can simulate defect printability on wafer from images captured by photomask inspection tools, as a valuable complementary or backup method for AIMS to reduce the loading and increase the production efficiency. In this paper, we introduce Lithography Printability Review (LPR) to mature technology node mask manufacturing. It can simulate aerial images of defect with low cost, and short cycle time. On the Programmed Defect Mask (PDM), LPR demonstrated obviously improved efficiency without missing critical defects. For the production masks, LPR proved that it can save much time and improve production capacity effectively.
For mature technology node IC manufacturing, a simple Tritone mask is widely adopted with chrome (Cr) layer remained in Scribe line and border region. The fabrication of a Tritone mask uses a dual step process with an e-beam writer for the 1st writing and a laser beam writer for the 2nd one, which induces process shift and possible Cr residual defects of the 2nd exposure writing. In this paper, NewRay Mask Technology Corporation (NRMTC) proposes a new process with adequate Cr shrinking, which can decrease residual Cr on Mosi/Qz edge when the mask is inspected and qualified on the KLA TeraScan™ 597XRS mask inspection system with Tritone Die-to-Database inspection mode. Furthermore, we have illustrated two main factors that contributed to Cr shrinking and figured out the optimal shrinking distance based on Cr line residue analysis and registration results. Production mask verification also conducted with optimal Cr shrink distance, demonstrates that optimal Cr shrinking distance can effectively improve the defect inspection process and have extra benefits on Tritone mask inspectability.
In modern advanced IC fabs, reticle management is essential for process control and yield management, since any reticle issue can potentially impact thousands of wafers, resulting in a huge economic loss. For reticle caused issues, the possibility of human mistakes made in defect disposition has dramatically increased as the defects on reticles become more complicated. The difficulty in defect disposition originates from smaller critical dimension (CD) and complex pattern designs like aggressive OPC and SRAF. Conventionally, defect disposition after reticle inspection is done by operators or engineers, and defects are evaluated based on engineers’ experience or AIMS tool, which are high risk and time-consuming methods. Use of automated defect disposition solutions has been reported in some photomask shops, but in DRAM fabs, an efficient and accurate defect disposition system is not yet present. In collaboration with KLA, Changxin Memory Technology (CXMT) accessed and utilized KLA’s Reticle Analyzer (RA), an intuitive web-based analysis interface that integrates Automatic Defect Classification (ADC), Lithographic Printability Review (LPR), and Defect Progress Monitor (DPM) to overcome reticle defect disposition difficulties. The comprehensive analytics tool systematically disposes all defects detected by KLA reticle inspection systems, eliminating human error in defect classification and providing 99.5% accuracy without under-classifying any defects. Furthermore, CXMT studied the LPR solution for multiple critical layers with programmed-defect masks, then verified the simulated LPR results in CD error (CDE). The correlation between LPR results and wafer printing results shows accurate CDE prediction in high volume production. Additionally, DPM was used to generate statistical process control like charts for reticle defectivity. This study shows that the integrated RA software offers a modern solution for wafer fabs that automates reticle defect management and shortens time to decision for engineers.
In an advanced IC fab, reticle inspection issues are critical as even one killer defect on the reticle can potentially affect thousands of wafers. Human errors such as defect mis-classification may lead to 70% of reticle issues that may affect production efficiency or even impact yield. With the adoption of RET techniques like aggressive OPC and SRAF combined with increasing MEEF and smaller defects, reticle dispositioning is becoming even harder and very time consuming in production. Even an experienced engineer may make a mistake especially when dealing with 40nm and below design nodes. The concept of automation to prevent mistakes in operation has been promoted for many years but a comprehensive solution which covers intelligent task assignment and auto reticle dispositioning in volume production has been missing. Working together with KLA, USCXM proposed a detailed methodology to overcome the above difficulties. From the very beginning, USCXM used Systematic Auto Recipe Creation (SARC) to create recipes for reticle inspections even before the reticles arrived in the fab. Also, an “OHT taxi mode” to improve pod utilization combined with the Reticle Management System (RMS) decision tree algorithm intelligently determined reticle inspection frequency based on wafer requirement and tool redundancy. Finally, USCXM automated final reticle dispositioning steps, such as, auto-releasing or auto-holding the reticle based on KLA’s Reticle Analyzer (RA) results. The overall implementation resulted in 25% improvement in inspection capacity and 50% reduction in operational cost compared to the traditional flow. Further, 92% accuracy for reticle auto-dispositioning was achieved with zero under-estimation. This integrated flow has proven to be invaluable for USCXM and is now deployed in full volume reticle manufacturing production.
Photomask contamination inspections, whether performed at maskshops as an outgoing
inspection or at wafer fabs for incoming shipping and handling or progressive defect monitoring,
have been performed by KLA-Tencor STARlight systems for a number of design nodes.
STARlight has evolved since it first appeared on the 3xx generation of KLA-Tencor mask
inspection tools. It was improved with the TeraStar (also known as SLF) based tools with the
SL1 algorithm. SL2 first appeared on the TeraScan systems (also known as 5xx) and has been
widely adopted in both mask shops and wafer fabs.
Design rules continue to advance as do inspection challenges. Advances in computer processing
power have enabled more complex and powerful algorithms to be developed and applied to the
STARlight technology. The current generation of STARlight, which is known as SL2+,
implements improved modeling fidelity as well as a completely new paradigm to the existing
STARlight technology known as HiRes5, or simply "H5". H5 is integrated seamlessly within
SL2+ and provides die-to-die-like performance in both transmitted and reflected light, in addition
to the STARlight detection, in unit time. It achieves this by automatically identifying repeating
structures in both X and Y directions and applying image alignment and difference threshold.
A leading mask shop partnered with KLA-Tencor in order to evaluate SL2+ at its facility. SL2+
demonstrated a high level of sensitivity on all test reticles, with good inspectability on advanced
production reticles. High sensitivity settings were used for 45 nm HP and smaller design rule
masks and low false detections were achieved. H5 provided additional sensitivity on production
plates, demonstrating the ability to extend the use of SL2+ to cover 32 nm DR plate inspections.
This paper reports the findings and results of this evaluation.
Progressive and haze defects continue to be the primary cause of mask degradation and
mask re-clean due mainly to intensified density of photon energy involved with ArF
exposure. To monitor and prevent haze in production, the methodology of direct reticle
inspection has been widely implemented in wafer fabs to provide early warning of haze
defects before they reach a critical level. With the continuous shrinkage of IC design rules
for scaling devices, reticle inspection systems are increasingly challenged by aggressive
OPC and high sensitivity requirements to detect printable defects. In this paper, two new
reticle inspection technologies: STARlight2+TM (SL2+) and Thin-line De-sense (TLD) on
Die-to-Die (D2D) mode have been studied and evaluated on ArF production test reticles.
The haze defect capture rate, defect residue modulation, and rendering on SL2+ mode
have been compared with STARlight2 (SL2); the false defect count and usable sensitivity
for D2D with TLD have been compared with D2D mode without TLD. The results of the
two new technologies revealed significant improvement on sensitivity, inspectability.
This paper discusses the most efficient mask re-qualification inspection mode for 7Xnm
half pitch design node production memory reticles in advanced memory wafer fab. By
comparing overall performance including inspectability, sensitivity, and throughput for 8
different inspection modes, P150 Pixel Die-to-Die Reflected Light (P150 DDR) was
identified to be the most desirable inspection mode for the specific use case where only
one inspection mode is available. The evaluation was executed on the most critical
layers - active, gate and contact layer. P150 DDR demonstrates the capability of
providing early warning for the crystal growth type defects on both quartz and MoSi
surfaces. It also showed good sensitivity for capturing small contamination defects in the
dense Line/Space or Contact/Hole pattern areas. With a fast inspection scan speed and
easy to use set up, TeraScanHR P150 DDR offers the best cost of ownership among all
inspection modes. To gain higher sensitivity for smaller design nodes, TeraScanHR P150
DDR can be easily extended to smaller inspection pixels with minimum impact on
productivity.
In photomask production environments, increasing productivity of defect inspection and improving fidelity of defect
classification are important for mask makers to improve capacity of defect inspection tools and to enhance quality of
production. In particular, defect classification time corresponds directly to the cost and the cycle time of mask
manufacturing and new product development. KLA-Tencor has introduced an automatic defect grouping tool
"ReviewSmart" which automatically bins defects with high fidelity. ReviewSmart has been reported in engineering R&D
and evaluation. In this paper, we focus on implementation of ReviewSmart in photomask production. 592 plates
were processed during the evaluation period. Those plates are for products of logic, memory and flash. Technology
nodes are from 65nm to 180nm. With optimized production setting, the automatic defect grouping tool - ReviewSmart
improves productivity of defect inspection by 7% with 100% fidelity. In addition to improve productivity, ReviewSmart
is helpful to classify aggressive OPC caused nuisance, troubleshoot process issues and expedite product development and
improve usable inspection sensitivity as well.
Resolution limitations in the mask making process can cause differences between the features that appear in a database
and those printed to a reticle. These differences may result from intentional or unintentional features in the database
exceeding the resolution limit of the mask making process such as small gaps or lines in the data, line end shortening on
small sub-resolution assist features etc creating challenges to both mask writing and mask inspection. Areas with high
variance from design to mask, often referred to as high MEEF areas (mask error enhancement factor), become highly
problematic and can directly impact mask and device yield, mask manufacturing cycle time and ultimately mask costs.
Specific to mask inspection it may be desirable to inspect certain non-critical or non-relevant features at reduced
sensitivity so as not to detect real, but less significant process defects. In contrast there may also be times where
increased sensitivity is required for critical mask features or areas. Until recently, this process was extremely manual,
creating added time and cost to the mask inspection cycle. Shifting to more intelligent and automated inspection flows is
the key focus of this paper. A novel approach to importing design data directly into the mask inspection to include both
MDP generated MRC errors files and LRC generated MEEF files.
The results of recently developed inspection and review capability based upon controlling defect inspection using design
aware data base control layers on a pixel basis are discussed. Typical mask shop applications and implementations will
be shown.
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