SPIE - Education Computational Basis for Advanced Lithography Techniques SC1132

This course provides attendees with a definition and underling concepts of Computational Lithography, which is comprised of lithographic modeling and advanced pattern correction techniques. It is designed to bridge the communication of exposure tool engineers, lithography process engineers and OPC/RET/SMO engineers to improve lithography process in an integrated sense. You will become familiar with the Computational Lithography framework and understand how the evolution of simple models and advanced pattern correction techniques to nowadays’ complicated yet powerful tools. An understanding of the fundamentals will allow lithographers to achieve optimum mask pattern for more robust lithography. This course will focus on both the imaging modeling and pattern correction methodology for novel patterning techniques such as Extreme UV (EUV), Directed Self-Assembly (DSA) and self-aligned multiple patterning. The unique computational features (Rigorous simulation, Mask decomposition, OPC, SMO) of these novel techniques will be contrasted with traditional DUV lithography. A review of the emergence of Machine Learning based computational Lithography techniques targeted to improve efficiency for full-chip application will be given. The course concentrates on the physics and working principles, as well as methodologies, to develop the new computational infrastructure. Some basic issues in Design Technology Co-Optimization with respect to EUV, DSA etc. are also discussed.