Abstract
Hybrid metrology is a promising approach to access to the critical dimensions of line gratings with precisions. The objective of this work is about using artificial intelligence (AI), mainly artificial neural network (ANN) to improve metrology at nanoscale characterization by hybridization of several techniques. Namely, optical critical dimension (OCD) or scatterometry, CD–Scanning electron microscopy (CDSEM), CD–Atomic force microscopy (CDAFM) and CD–Small angle x-rays scattering (CDSAXS). With virtual data of tabular–type generated by modelling, the ANN is able to predict the geometrical parameters compared to true measured values with high accuracies and detect irregularities in input data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
