Abstract
TEM automation is dedicated to providing high-volume, fast and precise TEM data to enable semiconductor manufacturers to develop and control fabrication processes. It automates TEM operation and measurement procedures, and minimizes the requirements of user training. Traditionally, recipes are required for each specific structure, and Automatic TEM Imaging and Metrology had individual recipes for each structure, respectively and separately. TEM professionals review structures and TEM images and manually assign imaging and metrology recipes one by one. After metrology, it is tedious to manually check mis-measurement of hundreds of TEM images and Critical Dimensions (CDs). In this study, An Intelligent TEM automation process was developed by machine learning process that could “fully” automatically conduct TEM Analysis from Imaging to Metrology starting right after TEM holder insertion without human intervention. It is not limited to automatically prepared TEM samples and also works for manually prepared samples. TEM Auto Metrology is carried out automatically right after Auto Imaging in the background. After that, Auto capturing of mis-measurements can be carried out automatically to catch problematic metrology images and CDs as an invaluable complement. As a result, the whole workflow was streamlined, with better efficiency and accuracy achieved.
