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, Michael A. Purvis, Alexander Schafgans, Alexander Schafgans, Daniel J. W. Brown, Daniel J. W. Brown, Igor Fomenkov, Igor Fomenkov, Rob Rafac, Rob Rafac, Josh Brown, Josh Brown, Yezheng Tao, Yezheng Tao, Slava Rokitski, Slava Rokitski, Mathew Abraham, Mathew Abraham, Mike Vargas, Mike Vargas, Spencer Rich, Spencer Rich, Ted Taylor, Ted Taylor, David Brandt, David Brandt, Alberto Pirati, Alberto Pirati, Aaron Fisher, Aaron Fisher, Howard Scott, Howard Scott, Alice Koniges, Alice Koniges, David Eder, David Eder, Scott Wilks, Scott Wilks, Anthony Link, Anthony Link, Steven Langer, 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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