Advanced Exploration of Stochastic Variations in Lithography Scaling and Their Impact on Moore’s Law

Level: Intermediate Length: 7 hours Format: In-Person Lecture Intended Audience: Individuals with a foundational understanding of semiconductor devices and lithography processes seeking to enhance their knowledge and explore the challenges and future developments in the field. Description: This course delves into the profound impacts of advances in lithography on the evolution of Moore’s Law over five decades. It critically examines how the success of lithography scaling could paradoxically contribute to the potential disruption of Moore’s Law due to emerging susceptibilities to stochastic variations such as linewidth roughness and local critical dimension uniformity. We will discuss the following topics on stochastic variations:

1. Introduction to Line-Edge Roughness (LER) and Linewidth Roughness (LWR): LER Experimental Results, Device Effects, LER Trends.

2. Metrology for LER/LWR: Power Spectral Density Measurement, Low-frequency roughness and feature-to-feature variation, High-frequency roughness and within variation, Measuring roughness using SEM images, Simulating rough features.

3. Stochastic Lithography Modeling: Beyond Continuum: Discrete Random Variables, Binary Distribution, Poisson Distribution, Example: Chemical Concentration.

4. Development and use of a Stochastic Model of Lithography: Optical Imaging: Photon Shot Noise, EUV Resist Exposure and Photon Absorption, Diffusion Processes: A Random Walk, Reaction-Diffusion and Acid-Base Quenching, Development and Efficacy of LER post-process smoothing, The Comprehensive LER Model.

5. Future Directions in Stochastic Lithography Research: Exploring advancements and innovations in mitigating stochastic variations, Evaluating potential trajectories for the future of lithography scaling in relation to Moore’s Law. Learning Outcomes: This course will enable you to: - describe how stochastic variations in lithography impact semiconductor devices - explain methods to measure stochastic variations - read and interpret Power Spectral Density data - identify primary causes of stochastic defections - explore the implications of stochastics for the future of lithography scaling Instructor(s): John S. Petersen is the Advanced Patterning Scientific Director at imec and a co-founder of imec’s AttoLab, in addition to his role at imec, John holds a position as an Adjunct Professor of Physical Chemistry at the University of Maryland, College Park, and has earned prestigious recognitions as an SPIE Fellow and a SEMATECH Fellow. He has made considerable contributions to the field, including delivering over 20 invited talks, securing 12 patents, and authoring more than 90 papers, 46 of which he is the lead author. John is an experienced SPIE course instructor. He received the SEMI 2006 Innovation Award and was honored as Adams State University's 2018 Alumnus of the Year. Event: SPIE Advanced Lithography + Patterning 2025 Course Held: 23 February 2025