Low- and mid-Z EUV spectroscopy of high temperature plasmas
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Authors
Wilcox, Penka Georgieva
Issue Date
2011
Type
Dissertation
Language
Keywords
EUV spectroscopy , Impurity plasmas , Laser plasmas , Low-Z plasmas , NSTX
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Abstract
Extreme ultraviolet (EUV) spectroscopy has proven to be an essential tool for plasma diagnostics, both of laboratory and astrophysical plasmas. Exploitation of the EUV and soft x-ray (SXR) spectral regions is very promising but a relatively recent and challenging area of study. While these ranges are more difficult to access, due to the harsh environment and the plentitude of atomic resonances and photoabsorption, they provide very sensitive tools for elemental and chemical identification, thus creating many scientific and technological opportunities. In this dissertation, a comprehensive spectroscopic study of EUV/SXR radiation from variety of low- and mid-Z plasmas was accomplished by the author. The emphasis was on application of the newly developed non-Local Thermodynamics Equilibrium (non-LTE) models of various elements (Li, C, B, N, O, F, Al, and Ni) for studying radiative properties of different high temperature plasmas. In addition, relativistic atomic data calculations, including dielectronic recombination and satellite lines of Ni ions, that implement several different codes and take into account a large number of configurations to assure accuracy, were performed.The applications of models to following experiments were considered: NSTX at Princeton, SSPX and EBIT at LLNL, and "Sparky" laser plasma and NTF Zebra Z-pinch experiments at UNR. As a result, the spectral features of EUV/SRX experimental radiation generated under various plasma conditions were compared and analyzed: from NSTX tokamak (at relatively low electron densities of 10[13]-10[14] 1/cc) to the laser-produced and Z-pinch plasma spectra at higher electron densities of 10[18]-10[20] 1/cc) and at various electron temperatures - from as low as 20 eV up to 300 eV. These investigated low- and mid-Z high resolution experimental data help to benchmark and improve our spectroscopic models and theory.
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