Dr. Tracy W. Huang Profile

Dr. Tracy W. Huang

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Publications (4)

Proceedings Article | 19 May 2008 Paper

Wafer plane inspection for advanced reticle defects

Rajesh Nagpal, Firoz Ghadiali, Jun Kim, Tracy Huang, Song Pang

Proceedings Volume 7028, 70281H (2008) https://doi.org/10.1117/12.793058

KEYWORDS: Inspection, Photomasks, Semiconducting wafers, Reticles, Defect inspection, Wafer inspection, Defect detection, Lithography, Critical dimension metrology, Contamination

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Proceedings Article | 19 May 2008 Paper

Printability impact of progressive defects: ammonium sulfate emulation study

Brian Grenon, Tracy Huang, Aditya Dayal, Kaustuve Bhattacharyya

Proceedings Volume 7028, 702817 (2008) https://doi.org/10.1117/12.793048

KEYWORDS: Crystals, Reticles, Magnesium, Inspection, Quartz, Air contamination, Photomasks, Crystallography, Contamination, Semiconducting wafers

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Proceedings Article | 25 October 2007 Paper

Automatic optimization of MEEF-driven defect disposition for contamination inspection challenges

Tracy Huang, Aditya Dayal, Kaustuve Bhattacharyya, Joe Huang, William Chou, Yung-Feng Cheng, Shih-Ming Yen, James Cheng, Peter Peng

Proceedings Volume 6730, 67302B (2007) https://doi.org/10.1117/12.748226

KEYWORDS: Crystals, Reticles, Contamination, Inspection, Quartz, Lithography, Semiconducting wafers, Photomasks, Sensors, Defect detection

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Ever-tightened design rules and ensuing aggressive OPC features pose significant challenges for wafer fabs in the pursuit of compelling yield and productivity. The introduction of advanced reticles considerably augments the mask error enhancement factor (MEEF) where progressive defects or haze, induced by repeated laser exposure, continue to be a source of reticle degradation threatening device yield. High resolution reticle inspection now emerges as a rescue venue for wafer fabs to assure their photomask integrity during intensive deep UV exposure. Integrated in the high resolution reticle inspection, a MEEF-driven lithographic detector "Litho3" can be used run-time to group critical defects into a single bin. Previous investigations evinced that critical defects identified by such detector were directly correlated with defects printed on wafer, upon which fab users can make cogent decisions towards reticle disposition and cleaning therefore reduce cycle time. One of the challenges of implementing such detector resides in the lengthy set up of user-defined parameters, from practitioner standpoint, can considerably extend reticle inspection time and inevitably delay production. To overcome this, an automatic simulation program has been written to optimize Litho3 settings based off a pre-inspection in which only default Litho3 values are needed. Upon completion of the pre-inspection, the images are then scanned and processed to extract the optimal Litho3 parameters that are largely dependent upon the feature size characteristics and local MEEF. Thus optimized Litho3 parameters can then be input into the recipe set up to enable a real-time inspection, as such fab user can timely access the defect criticality information for subsequent defect disposition. In the interest of printability validation, such defect information and associated coordinates can be passed onto defect review via XLINK for further analysis. Corresponding MEEF values are also available for all identified critical defects. Through this automatic program the set up time for Litho3 can be reduced by up to 90%. For high capacity production fabs running a pre-inspection is deemed infeasible; this automatic optimization program can also serve as a direct interpretation of any regular reticle inspection even without invoking Litho3 set up, yet in the end provide output in the context of defect criticality. Results acquired from this program were found in good accordance with those from the real-time Litho3 inspection, for both critical and non-critical layers of 90 nm design node. Such capability allows detailed study of defect criticality in relation to its size, defect optical transmittance, residing surface, its proximity to a printing pattern as well as lithography parameters such as NA and sigma. Furthermore, coupling this automatic program with high resolution inspection also assists in determining lithography process window and an indepth comprehension of defect progression mechanism.

Proceedings Article | 29 May 2007 Paper

A novel run-time MEEF-driven defect disposition extending high resolution contamination inspection to next generation photomask

William Chou, Yung-Feng Cheng, Shih-Ming Yen, James Cheng, Peter Peng, Joe Huang, Tracy Huang, Den Wang, Ellison Chen, Ching Yun Hsiang, Kaustuve Bhattacharyya, Aditya Dayal

Proceedings Volume 6607, 66072F (2007) https://doi.org/10.1117/12.728998

KEYWORDS: Reticles, Inspection, Semiconducting wafers, Photomasks, Lithography, Defect detection, Sensors, Contamination, Air contamination, Transmittance

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The advent of device miniaturization necessitates sub-half-micron features delineated on reticles where photomask quality, more so than ever, exerts remarkable yield impact on 65 nm node and below. The introduction of advanced reticles considerably augments the mask error enhancement factor (MEEF) in the non-linear regime ensuing aggressive OPC features. The increased MEEF leads to tightened defect capture criteria, in which many of the previously insignificant defects become of interest and may have substantial yield impact. To provide desired sensitivity, a high resolution inspection is a must; it also effectively monitors mask reliability. However, the productivity of such inspection greatly depends on defect disposition efficacy in sorting out critical defects from the large population detected on contaminated masks [1-3]. Anchoring high resolution reticle inspection, wafer fabs are in a relentless pursuit of optimal defect disposition method to meet the throughput demand. In particular, progressive defects or haze, induced by repeated laser exposure, continue to be a source of reticle degradation threatening device yield. Early detection of these defects to circumvent the printability impact becomes vitally important yet challenging. In addition to its size, the defect criticality also largely depends upon defect optical transmittance, residing surface, its proximity to a printing pattern as well as lithography parameters such as NA and sigma [4-6]. A MEEF-driven lithographic detector named "Litho3" has been designed that can be used run-time during mask inspection to effectively group the critical defects into a single bin based on their potential yield impact. The coordinates of these critical defects, identified by the above Litho3 detector, can then be transferred from reticle to wafer and subsequently subject to printability validation, upon which defective sites can be analyzed thoroughly on reticle or wafer review tools. Such capability reduces inspection cycle time by improving defect disposition efficacy, also assists in determining lithography process window and a further comprehension of defect progression mechanism.

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