Various methods and systems for utilizing design data in combination with inspection data are provided. One computer-implemented method for binning defects detected on a wafer includes comparing portions of design data proximate positions of the defects in design data space. The method also includes determining if the design data in the portions is at least similar based on results of the comparing step. In addition, the method includes binning the defects in groups such that the portions of the design data proximate the positions of the defects in each of the groups are at least similar. The method further includes storing results of the binning step in a storage medium.

Methods and systems for utilizing design data in combination with inspection data

Various methods and systems for determining a position of inspection data in design data space are provided. One computer-implemented method includes determining a centroid of an alignment target formed on a wafer using an image of the alignment target acquired by imaging the wafer. The method also includes aligning the centroid to a centroid of a geometrical shape describing the alignment target. In addition, the method includes assigning a design data space position of the centroid of the alignment target as a position of the centroid of the geometrical shape in the design data space. The method further includes determining a position of inspection data acquired for the wafer in the design data space based on the design data space position of the centroid of the alignment target.

Methods and systems for determining a position of inspection data in design data space

Computer-implemented methods and systems for detecting defects in a reticle design pattern are provided. One computer-implemented method includes acquiring images of the reticle design pattern using a sensor disposed on a substrate arranged proximate to an image plane of an exposure system configured to perform a wafer printing process using the reticle design pattern. The images illustrate how the reticle design pattern will be projected on a wafer by the exposure system at different values of one or more parameters of the wafer printing process. The method also includes detecting defects in the reticle design pattern based on a comparison of two or more of the images corresponding to two or more of the different values.

Methods and systems for detecting defects in a reticle design pattern

Various computer-implemented methods are provided. One method for evaluating reticle layout data includes generating a simulated image using the reticle layout data as input to a model of a reticle manufacturing process. The simulated image illustrates how features of the reticle layout data will be formed on a reticle by the reticle manufacturing process. The method also includes determining manufacturability of the reticle layout data using the simulated image. The manufacturability is a measure of how accurately the features will be formed on the reticle. Also provided are various carrier media that include program instructions executable on a computer system for performing a method for evaluating reticle layout data as described herein. In addition, systems configured to evaluate reticle layout data are provided. The systems include a computer system and a carrier medium that includes program instructions executable on the computer system for performing method(s) described herein.

Methods, systems, and carrier media for evaluating reticle layout data

Systems and methods for creating inspection recipes are provided. One computer-implemented method for creating an inspection recipe includes acquiring a first design and one or more characteristics of output of an inspection system for a wafer on which the first design is printed using a manufacturing process. The method also includes creating an inspection recipe for a second design using the first design and the one or more characteristics of the output acquired for the wafer on which the first design is printed. The first and second designs are different. The inspection recipe will be used for inspecting wafers after the second design is printed on the wafers using the manufacturing process.

Systems and methods for creating inspection recipes

Progressive mask defect problem is an industry wide mask reliability issue. During the start of this problem when the defects on masks are just forming and are still non-critical, it is possible to continue to run such a problem mask in production with relatively low risk of yield impact. But when the defects approach more critical state, a decision needs to be made whether to pull the mask out of production to send for clean (repair). As this problem increases on the high-end masks running DUV lithography where masks are expensive, it is in the interest of the fab to sustain these problem masks in production as long as possible and take these out of production only when absolutely necessary; i.e., when the defects have reached such a critical condition on these masks that it will impact the process window. During the course of this technical work, investigation has been done towards understanding the impact of such small progressive defects on process window. It was seen that a small growing defect may not print at the best focus exposure condition, but it can still influence the process window and can shrink it significantly. With the help of a high-resolution direct reticle inspection, early detection of these defects is possible, but fabs are still searching for a way to disposition (make a go / no-go decision) on these defective masks. But it is not an easy task as the impact of these defects will depend on not only their size, but also on their transmission and MEEF. A lithographic detector has been evaluated to see if this can predict the criticality of such progressive mask defects.

Process window impact of progressive mask defects, its inspection and disposition techniques (go/no-go criteria) via a lithographic detector

As design rule continues to shrink towards ITRS roadmap requirements, reticle defect capture criteria are becoming ever more challenging. Pattern fidelity and reticle defects that were once perceived as insignificant or nuisance are now becoming a significant considerable yield impacting factor. More defects are also detectable and presented with increase in implementation of new generation reticle inspection systems. Therefore, how to review and characterize defects accurately and efficiently is becoming more significant. In particular, defect classification time often corresponds directly to the cost and the cycle time of mask manufacturing or new technology development. 

In this study we introduce a new mask defect review tool called ReviewSmart, which retrieves and processes defect images reported from KLA-Tencor's high sensitivity TeraScan inspection tool. Compared to the traditional defect review method, ReviewSmart provides a much better method to manage defects efficiently by utilizing the concept of defect grouping disposition. 

Through the application and qualification results with respectable reticle production cases, the implementation of ReviewSmart has been proven to be effective for reducing defect classification loading and improving defect characterizing efficiency. Moreover, the new review tool is helpful to categorically identify tool or process variations thus allowing users to expedite the learning process for developing production worthy leading node processes.

Implementation of an efficient defect classification methodology for advanced reticle inspection

Progressive mask defect problems such as crystal growth or haze are key yield limiters for DUV lithography, especially in 300mm fabs. Even if the incoming mask quality is good, there is no guarantee that the mask will remain clean during its production usage in the wafer fab. These progressive defects must be caught in advance during production in the fabs. The ideal reticle quality control goal should be to detect any nascent progressive defects before they become yield limiting. So, a high-resolution mask inspection is absolutely needed, but the big question is: “how often do fabs need to re-inspect their masks”? This re-inspection frequency should ideally be the most cost-effective frequency at which there is minimum threat for a yield loss.

Previous work towards finding a cost effective mask re-qualification frequency was done prior to the above mentioned progressive defect problem that industry started to see at a much higher rate during just the last few years. Other related recent work was done 2004 BACUS conference which is dedicated to DRAM fab data. 

In this paper a realistic mask re-qualification frequency model has been developed based on a large volume of data from an advanced logic fab. This work will compliment previous work in this area done with the data from a DRAM fab. Statistical methods are used to analyze mask inspection and product data, which are combined in a stochastic model.

A reticle quality management strategy in wafer fabs addressing progressive mask defect growth problem at low k1 lithography

As design rule continues to shrink towards ITRS roadmap requirements, reticle defect capture criteria are becoming ever more challenging. Pattern fidelity and reticle defects that were once perceived as insignificant or nuisance are now becoming a significant considerable yield impacting factor. More defects are also detectable and presented with increase in implementation of new generation reticle inspection systems. Therefore, how to review and characterize defects accurately and efficiently is becoming more significant. In particular, defect classification time often corresponds directly to the cost and the cycle time of mask manufacturing or new technology development. In this study we introduce a new mask defect review tool called ReviewSmart, which retrieves and processes defect images reported from KLA-Tencor's high sensitivity TeraScan inspection tool. Compared to the traditional defect review method, ReviewSmart provides a much better method to manage defects efficiently by utilizing the concept of defect grouping disposition. Through the application and qualification results with respectable reticle production cases, the implementation of ReviewSmart has been proven to be effective for reducing defect classification loading and improving defect characterizing efficiency. Moreover, the new review tool is helpful to categorically identify tool or process variations thus allowing users to expedite the learning process for developing production worthy leading node processes.

High-resolution contamination inspection for advanced reticles remains crucial in light of the increasing trend of progressive defects such as crystal growth, haze, fungus, precipitate etc., introduced with DUV lithography, especially for low k1 processes. In most fab environments, routine incoming and re-qualification inspections for photomasks have been implemented. But although this high-resolution inspection provides necessary high-sensitivity, on advanced photomasks it often introduces inspection challenges. Aggressive OPCs and dense primary and secondary geometries are some of the many factors that can result in false-defect problems for the inspection systems. Thus, inspection needs to be desensitized. As an effort to identify a methodology to provide the inspectability while maintaining the necessary high-sensitivity, a characterization has been performed to evaluate a new combination-mode inspection. This technical paper will list the details of this special contamination inspection technique that will allow users to maintain the same high inspection throughput while providing similar or higher resolution inspection for these advanced reticles with superior inspectability.

Kong Son

Papers

Process window impact of progressive mask defects, its inspection and disposition techniques (go/no-go criteria) via a lithographic detector

Implementation of an efficient defect classification methodology for advanced reticle inspection

A reticle quality management strategy in wafer fabs addressing progressive mask defect growth problem at low k1 lithography

Implementation of an efficient defect classification methodology for advanced reticle inspection

A high-resolution contamination-mode inspection method providing a complete solution to the inspection challenges for advanced photomasks