Integration of Computer-Aided Design (CAD) Information into a Defect-Review SEM Platform and Design Based Automatic Defect Classification : DI: Defect Inspection and Reduction

Defect metrology for advanced FinFET devices faces a variety of challenges in terms of accurate classification of Defect Review Scanning Electron Microscopy (DR-SEM) images. As the Defect of Interest (DOI) size shrinks in proportion to the printed feature dimension, it is critical that these platforms adjust to continue to provide the best possible defect classification. This can be achieved most efficiently by introducing Computer-Aided Design (CAD) information into these platforms. In order to improve imaging of defects in DR-SEM, CAD data is used to enhance the alignment step, providing more accurate navigation to defects and allowing the magnification to scale according to the smaller defect size. We present a streamlined method to introduce this CAD based alignment step into the existing recipe management system on the DR-SEM platform. While decreasing image FOV is beneficial, the introduction of CAD information into Automatic Defect Classification (ADC) can provide valuable information on the defect's location. Design Based ADC (DBA) achieves this by providing the means to differentiate the defect's impact on device performance based on CAD data such as mask or process step. We present two case studies of DBA on multi- patterning and epi layers in the sub-1x FinFET process.