Laurent C. Tuo

Mask defect auto disposition based on aerial image in mask production

At the most advanced technology nodes, such as 45nm and below, aggressive OPC and Sub-Resolution Assist Features (SRAFs) are required. However, their use results in significantly increased mask complexity, making mask defect disposition more challenging than ever. In an attempt to mitigate such difficulties, new mask inspection technologies that rely on hardware emulation and software simulation to obtain aerial image at the wafer plane have been developed; however, automatic mask disposition based on aerial image is still problematic because aerial image does not give the final resist CD or contour, which are commonly used in lithography verification on post OPC masks. In this paper, an automated mask defect disposition system that remedies these shortcomings is described. The system, currently in use for mask production, works in both die-to-die and die-to-database modes, and can operate on aerial images from both AIMSTM and aerial-image-based inline mask inspection tools. The disposition criteria are primarily based on waferplane CD variance. The system also connects to a post-OPC lithography verification tool that can provide gauges and CD specs, which are then used in the mask defect disposition.

AIMS D2DB simulation for DUV and EUV mask inspection

AIMS™ Die-to-Die (D2D) is widely used in checking the wafer printability of mask defects for DUV lithography. Two AIMS images, a reference and a defect image, are captured and compared with differences larger than certain tolerances identified as real defects. Since two AIMS images are needed, and since AIMS system time is precious, it is desirable to save image search and capture time by simulating reference images from the OPC mask pattern and AIMS optics. This approach is called Die-to-Database (D2DB). Another reason that D2DB is desirable is in single die mask, where the reference image from another die does not exist. This paper presents our approach to simulate AIMS optics and mask 3D effects. Unlike OPC model, whose major concern is predicting printed CD, AIMS D2DB model must produce simulated images that match measured images across the image field. This requires a careful modeling of all effects that impact the final image quality. We present a vector-diffraction theory that is based on solid theoretical foundations and a general formulation of mask model that are applicable to both rigorous Maxwell solver and empirical model that can capture the mask 3D-effects. We demonstrated the validity of our approach by comparing our simulated image with AIMS machine measured images. We also briefly discuss the necessary changes needed to model EUV optics. Simulation is particularly useful while the industry waits for an actinic EUV-AIMS tool.

An agile mask data preparation and writer dispatching approach

An agile mask data preparation (MDP) approach is proposed to cut re-fracture cycle time as incurred by mask writer dispatching policy changes. Shorter re-fracture cycle time increases the flexibility of mask writer dispatching, as a result, mask writers capacity can be utilized to its optimum. Preliminary results demonstrate promising benefits in MDP cycle time reduction and writer dispatching flexibility improvement. The agile MDP can save up to 40% of re-fracture cycle time. OASIS (Open Artwork System Interchange Standard) was proposed to address the GDSII file size explosion problem. However, OASIS has yet to gain wide acceptance in the mask industry. The authors envision OASIS adoption by the mask industry as a three-phase process and identify key issues of each phase from the mask manufacturers perspective. As a long-term MDP flow reengineering project, an agile MDP and writer dispatching approach based on OASIS is proposed. The paper describes the results of an extensive evaluation on OASIS performance compared to that of GDSII, both original GDSII and post-OPC GDSII files. The file size of eighty percent of the original GDSII files is more than ten times larger compared to that of its OASIS counterpart.

Ta-Si-O absorptive shifter for the attenuated phase-shifting mask

Ta-Si-O composite films have been developed for the single-layer attenuated phase-shifting mask (A.PSM). The films were deposited in an reactive-sputtering system with separating Ta and Si guns. The refractive index and the extinction coefficient of films were tuned by changing the oxygen flow rate and gun power of each gun. At the optimum condition, films with the required optical properties for APSM has been obtained. The films obtained will produce π-shift transmittance around 7% for both i-line and DUV lithography, and less than 25% of transmittance at 488 nm which is important for defect inspection. In addition, the films appear to be inert to hot sulfuric acid which is also important in mask cleaning. Together, Ta-Si-O composite film is expected to be a promising material of DUV absorptive shifter.

(LaNiO3)x(Ta2O5)1-x oxide thin films for attenuated phase-shifting mask blank

A feasibility of optical proximity effect correction (OPC) mask manufacturing with a state of the art mask fabrication processing and systems is demonstrated focusing on the 0.25 micrometer devices and 4X reticle generation. For realistic OPC mask fabrication, electron beam (EB) resist processing in terms of CD accuracy, mask defect inspection thoroughness and mask defect repair accuracy are studied in detail. For the positive resist process, EB proximity effect correction is applied in order to improve the linearity to meet required CD specifications. Based on such evaluation, practical criteria for OPC pattern generation are applied into an automatic OPC software. It is verified that by using the software with the criteria given, 0.25 micrometer memory device patterns can be corrected with a sufficient optical lithography imaging performance and a reasonable data volume. It is concluded that manufacturing feasibility of sufficiently effective OPC masks is verified as a result of concurrent development on the mask fabrication and automatic OPC software. Engineering tasks in the future are also proposed.

Megasonic cleaning strategy for sub-10nm photomasks

One of the main challenges in photomask cleaning is balancing particle removal efficiency (PRE) with pattern damage control. To overcome this challenge, a high frequency megasonic cleaning strategy is implemented. Apart from megasonic frequency and power, photomask surface conditioning also influences cleaning performance. With improved wettability, cleanliness is enhanced while pattern damage risk is simultaneously reduced. Therefore, a particle removal process based on higher megasonic frequencies, combined with proper surface pre-treatment, provides improved cleanliness without the unintended side effects of pattern damage, thus supporting the extension of megasonic cleaning technology into 10nm half pitch (hp) device node and beyond.

Reticle decision center: a novel applications platform for enhancing reticle yield and productivity at 10nm technology and beyond

In the semiconductor IC manufacturing industry, challenges associated with producing defect-free photomasks have been dramatically increasing. At the 10nm technology node, since the 193nm immersion scanner numerical aperture has remained the same 1.35 as in previous nodes, more multi-patterning and aggressive SMO illumination sources are being used to effectively print smaller feature CDs and pitches. To accommodate such specialized sources, more model-based mask OPC and ILT have been used making mask designs very complicated. This in turn makes mask manufacturing very challenging especially for the defect inspection, repair, and metrology processes that need to guarantee defect-free masks. Over the past few years, considerable innovation have been made in the areas of defect inspection and disposition that has ensured continued predictability of mask quality to wafer and final chip yields. The accurate disposition of each mask defect before and after repair has been facilitated by a suite of automated applications such as ADC, LPR, RPG, AIA, etc. that work together with the inspection, repair, and metrology tools and effectively also provide the best possible utilization of the tool capability, capacity and operator resources. In this paper we introduce a new consolidated applications platform called the Reticle Decision Center (RDC) which hosts all these supporting software applications on a centralized server with direct connectivity to mask inspection, repair, metrology tools and more. The paper details how the RDC server is architected to host any application in its native operating system environment and provides for high availability with automatic failover and redundancy. The server along with its host of applications has been tightly integrated with KLA-Tencor’s Teron mask inspectors. The paper concludes with showing benefits realized in mask cycle-time and yield as a result of implementing RDC into a high-volume 10nm mask-shop production line.

Automated Defect Classification (ADC) and Progression Monitoring (DPM) in wafer fab reticle requalification

As optical lithography continues to extend into low-k1 regime, resolution of mask patterns continue to diminish, and so do mask defect requirements due to increasing MEEF. Post-inspection, mask defects have traditionally been classified by operators manually based on visual review. This approach may have worked down to 65/55nm node layers. However, starting 45nm and smaller nodes, visually reviewing 50 to sometimes 100s of defects on masks with complex modelbased OPC, SRAF, and ILT geometries, is error-prone and takes up valuable inspection tool capacity. Both these shortcomings in manual defect review are overcome by adoption of the computational solution called Automated Defect Classification (ADC) wherein mask defects are accurately classified within seconds and consistent to guidelines used by production technicians and engineers.

In-situ repair qualification by applying Computational Metrology and Inspection (CMI) technologies

Computational techniques have been widely adapted in furthering resolution of optical lithography. Now such techniques are expanded into inspection and metrology with many new applications in mask houses and wafer Fabs enabling process advancement, improving process cycle time, and eliminating operator errors. One area of those applications is mask repair. Many times defects repaired do not pass the AIMS check therefore, the mask has to be reloaded back to repair tool to perform another round of repair and verification. Adding more loops of repair and AIMS check significant increases the mask cycle time and effectively reduces the potential throughput of the AIMS and repair tools. Ideally, the mask should not be removed from repair tool until all defects are repaired successfully. Simulation based In-situ Repair Qualifier (IRQ) was developed to meet this goal. IRQ takes SEM image of a repaired site and then simulates the aerial image using the exact scanner optical and illumination conditions (including free form sources). If the CD on the aerial image does not meet spec, the defect has to be repaired again until it does. By doing so, the chance of having repaired defects not meeting the AIMS spec is dramatically reduced or eliminated. In this paper, we will discuss the technical challenges in detail and present results demonstrating the accuracy and benefits of IRQ. Results on both programmed defects and real defects from product masks will be presented. The repair cycle time improvements and effective tool capacity gains before and after using IRQ are presented.

Efficiency and throughput improvement on defect disposition through automated defect classification

The routine use of aggressive OPC at advanced technology nodes, i.e., 40nm and beyond, has made photomask patterns quite complex. The high-resolution inspection of such masks often result in more false and nuisance defect detections than ever before. Traditionally, each defect is manually examined and classified by the inspection operator based on defined production criteria. The significant increase in total number of detected defects has made manual classification costly and non-manufacturable. Moreover, such manual classification is also susceptible to human judgment and hence error-prone. Luminescents Automated Defect Classification (ADC) offers a complete and systematic approach to defect disposition and classification. The ADC engine retrieves the high resolution inspection images and uses a decision-tree flow based on the same criteria human operators use to classify a given defect. Some identification mechanisms adopted by ADC to characterize defects include defect color in transmitted and reflected images, as well as background pattern criticality based on pattern topology. In addition, defect severity is computed quantitatively in terms of its size, impacted CD error, transmission error, defective residue, and contact flux error. The final classification uses a matrix decision approach to reach the final disposition. In high volume manufacturing mask production, matching rates of greater than 90% have been achieved when compared to operator defect classifications, together with run-rates of 250+ defects classified per minute. Such automated, consistent and accurate classification scheme not only allows for faster throughput in defect review operations but also enables the use of higher inspection sensitivity and success rate for advanced mask productions with aggressive OPC features.