Dr. Chris A. Mack
CTO at Fractilia LLC
SPIE Involvement:
| Awards Committee | Board of Directors | Nominating Committee | Publications Committee | Fellow status | Symposium Committee | Conference Chair | Conference Program Committee | Journal Editor-in-Chief | Author | Instructor
Area of Expertise:
Photolithography , Modeling , Microlithography , Stochastic Modeling
Profile Summary

Chris A. Mack received Bachelor of Science degrees in physics, chemistry, electrical engineering, and chemical engineering from Rose-Hulman Institute of Technology in 1982, a Master of Science degree in electrical engineering from the University of Maryland in 1989, and a Ph.D. in chemical engineering from the University of Texas at Austin in 1998. Mr. Mack founded FINLE Technologies, the developer of the lithography simulation software PROLITH, in 1990, serving as President and Chief Technical Officer until the acquisition of FINLE by KLA-Tencor in 2000. For the next five years he served as Vice President of Lithography Technology for KLA-Tencor. In 2003 he received the SEMI Award for North America for his efforts in lithography simulation and education. He became a fellow of SPIE in 2006, and a fellow of IEEE in 2010. In 2009 he received the SPIE Frits Zernike Award for Microlithography. He is also an adjunct faculty member at the University of Texas at Austin and spent the Fall 2006 semester as a visiting professor at the University of Notre Dame. He has recently completed a comprehensive graduate-level textbook on optical lithography, Fundamental Principles of Optical Lithography, published in late 2007. In 2012 he became Editor-In-Chief of the Journal of Micro/Nanolithography, MEMS, and MOEMS (JM3). In 2017 he cofounded Fractilia, where he now works as Chief Technical Officer developing metrology solutions for the measurement of roughness.
Publications (212)

SPIE Journal Paper | November 10, 2018
JM3 Vol. 17 Issue 04
KEYWORDS: Scanning electron microscopy, Line edge roughness, Materials processing, Extreme ultraviolet, Line width roughness, Etching, Lithography, Image filtering, Material characterization, Image acquisition

PROCEEDINGS ARTICLE | November 7, 2018
Proc. SPIE. 10809, International Conference on Extreme Ultraviolet Lithography 2018
KEYWORDS: Lithography, Metrology, Etching, Surface roughness, Photoresist materials, Speckle pattern, Photomasks, Extreme ultraviolet lithography, Line edge roughness, Mass attenuation coefficient

SPIE Journal Paper | September 12, 2018
JM3 Vol. 17 Issue 04
KEYWORDS: Metrology, Line width roughness, Scanning electron microscopy, Digital filtering, Atomic force microscopy, Standards development, Semiconductors, Image acquisition, Image quality, Electron microscopes

SPIE Journal Paper | August 10, 2018
JM3 Vol. 17 Issue 03
KEYWORDS: Monte Carlo methods, Stochastic processes, Photoresist developing, Physical sciences, Lead, Calibration, Lithography, Photoresist materials

SPIE Journal Paper | August 7, 2018
JM3 Vol. 17 Issue 04
KEYWORDS: Lithography, Etching, Line edge roughness, Extreme ultraviolet lithography, Scanning electron microscopy, Line width roughness, Image filtering, Critical dimension metrology, Line scan image sensors, Photons

SPIE Journal Paper | July 11, 2018
JM3 Vol. 17 Issue 04
KEYWORDS: Particles, Lithography, Stochastic processes, Molecules, Failure analysis, Extreme ultraviolet lithography, Photoresist materials, Chemical species, Extreme ultraviolet, Vacuum tubes

Showing 5 of 212 publications
Conference Committee Involvement (17)
SPIE Advanced Lithography
21 February 2016 | San Jose, United States
SPIE Advanced Lithography
23 February 2014 | San Jose, United States
SPIE Advanced Lithography
24 February 2013 | San Jose, United States
SPIE Advanced Lithography
12 February 2012 | San Jose, United States
SPIE Advanced Lithography
27 February 2011 | San Jose, United States
Showing 5 of 17 published special sections
Course Instructor
SC116: Lithographic Optimization: A Theoretical Approach
This course discusses the techniques required to characterize and optimize an optical lithography process. The lithographic process is made up of a series of basic steps: the formation of an aerial image, the transfer of the aerial image into the photoresist during exposure, and the development of this latent image into the final photoresist profile. In order to characterize and optimize this process one must understand the principles and interactions of each step of the process.
SC1173: How and Why: The big ideas in semiconductor lithography
Moore’s Law has been changing the world for over 50 years, and advances in lithography have been a (the) major factor in its success. This course will review several major conceptual and technical underpinnings of lithography for semiconductor manufacturing, providing a large, holistic view of where we are, how we got here, and where we are going next. Topics include Moore’s Law, resolution and depth of focus, the components of optical resolution, chemically amplified resists, lithography impacts on design, and next generation lithography. 1. Moore’s Law – History, components, meaning, Dennard scaling, impact on lithography 2. The focus-exposure matrix, depth of focus, and the Normalized Image Log-Slope (NILS) 3. Chemically amplified resists, acid and quencher diffusion, and isofocal bias 4. Imaging, resolution, and the change from three-beam to two-beam imaging 5. Design – WYSIWYG, design rules, litho-friendly design 6. The Future – what will be the next generation of lithography? How will it impact Moore’s Law?
SC1263: Stochastic Lithography
Moore’s Law has been changing the world for over 50 years, and advances in lithography have been a (the) major factor in its success. The success of lithography scaling, however, may cause the undoing of Moore’s Law as smaller features become susceptible to stochastics variations such as linewidth roughness, local critical dimension uniformity, and stochastic defects. This course will look at how stochastic variation during lithography affects semiconductor devices, how to measure stochastic variations, the major causes of stochastic variation, and what stochastics will mean for the future of lithography scaling. 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 Modeling Fundamentals – No Longer a Continuum: Discrete Random Variables, Binary Distribution, Poisson Distribution, Example – Chemical Concentration 4. A Stochastic Model of Lithography: Optical Imaging – Photon Shot Noise, Photon Absorption and Exposure, EUV Resist Exposure, Diffusion – A Random Walk, Reaction-Diffusion, Acid-Base Quenching, Development, The LER Model, Efficacy of LER post-process smoothing 5. Future Work
SC102: Optical Lithography Modeling
This course presents the theory and applications of optical lithography simulation tools. Using examples, practical applications to typical material and image problems will be discussed.
SC268: Introduction to Optical Lithography
This course discusses the basic principles and techniques of an optical lithography process. The course gives a general overview of optical lithography and goes into some depth on important topics.
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