The ongoing trend to smaller structures and an increasing number of high MEEF patterns in mask design makes defect disposition and repair verification more critical than ever. For AIMS™ as the standard method for defect disposition and repair verification, the requirements are getting tighter. Additionally, the efforts required for defect analysis are steadily increasing. As a result, mask manufacturers are forced to continually find methods to increase productivity and optimize the cost of defect disposition. <p> </p>Smart solutions for automated defect treatment together with a high degree of tool integration play an increasing role in this challenge. With AIMS™ AutoAnalysis, which provides fully automated analysis capability of AIMS™ aerial images, ZEISS addresses this challenge. Due to direct connection and communication of AutoAnalysis with the AIMS™ system via the FAVOR® platform, the image analysis process runs in parallel to the measurement process. A high degree of automation reduces the influence of human error and provides highly reliable results. <p> </p>In the following paper a study is presented demonstrating the benefits of the implementation of AutoAnalysis in the production environment at Photronics, Inc. The study was carried out by analyzing defects on pattern sets, varying from simple to very complex patterns. Furthermore, the analysis capabilities of AutoAnalysis have been compared with the capability of operators and engineers. <p> </p>The performance of AutoAnalysis is presented showing significant time saving in the defect disposition process as well as an overall increase in reliability of analysis results.
The ZEISS AIMS™ platform is well established as the industry standard for qualifying the printability of mask
features based on the aerial image. Typically the critical dimension (CD) and intensity at a certain through-focus
range are the parameters which are monitored in order to verify printability or to ensure a successful
repair. This information is essential in determining if a feature will pass printability, but in the case that the
feature does fail, other methods are often required in order to isolate the reason why the failure occurred,
e.g., quartz level deviation from nominal.
Atomic force microscopy (AFM) is typically used to determine physical dimensions such as the quartz etch
depth and sidewall profile. In addition the AFM is a useful tool in monitoring and providing feedback to the
repair engineer, as the depth of the repair is one of the many critical parameters which must be controlled in
order to have a robust repair process.
Carl Zeiss, in collaboration with Photronics-nanoFab, demonstrate the ability to use AIMS<sup>TM</sup> to provide
quantitative feedback on a given repair process; beyond simple pass/fail of the repair. Using the ZEISS MeRiT<sup>®</sup>
repair tool as the example, the AIMS<sup>TM</sup> technique is used in lieu of an AFM to determine if repaired regions are
over-etched or under-etched; and further to predict the amount of MeRiT<sup>®</sup> recipe change required in order to
bring subsequent repairs to a passing state.