18 March 2016 Advancements in predictive plasma formation modeling
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Abstract
We present highlights from plasma simulations performed in collaboration with Lawrence Livermore National Labs. This modeling is performed to advance the rate of learning about optimal EUV generation for laser produced plasmas and to provide insights where experimental results are not currently available. The goal is to identify key physical processes necessary for an accurate and predictive model capable of simulating a wide range of conditions. This modeling will help to drive source performance scaling in support of the EUV Lithography roadmap. The model simulates pre-pulse laser interaction with the tin droplet and follows the droplet expansion into the main pulse target zone. Next, the interaction of the expanded droplet with the main laser pulse is simulated. We demonstrate the predictive nature of the code and provide comparison with experimental results.
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Michael A. Purvis, Alexander Schafgans, Daniel J. W. Brown, Igor Fomenkov, Rob Rafac, Josh Brown, Yezheng Tao, Slava Rokitski, Mathew Abraham, Mike Vargas, Spencer Rich, Ted Taylor, David Brandt, Alberto Pirati, Aaron Fisher, Howard Scott, Alice Koniges, David Eder, Scott Wilks, Anthony Link, Steven Langer, "Advancements in predictive plasma formation modeling", Proc. SPIE 9776, Extreme Ultraviolet (EUV) Lithography VII, 97760K (18 March 2016); doi: 10.1117/12.2221991; https://doi.org/10.1117/12.2221991
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