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Determination of state-to-state electron-impact rate coefficients between Ar excited states: a review of combined diagnostic experiments in afterglow plasmas

期刊

出版社

IOP PUBLISHING LTD
DOI: 10.1088/0963-0252/25/4/043003

关键词

combined diagnostics; low-temperature plasma; collisional-radiative model; electron-impact rate coefficient

资金

  1. Alexander-von-Humboldt Foundation
  2. Ministry of Science and Technology of China [2011ZX02403]

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Electron-impact excitation processes play an important role in low-temperature plasma physics. Cross section and rate coefficient data for electron-impact processes from the ground state to excited states or between two excited states are required for both diagnostics and modeling works. However, the collisional processes between excited states are much less investigated than the ones involving the ground state due to various experimental challenges. Recently, a method for determining electron excitation rate coefficients between Ar excited states in afterglow plasmas was successfully implemented and further developed to obtain large sets of collisional data. This method combines diagnostics for electron temperature, electron density, and excited species densities and kinetic modeling of excited species, from which the electron excitation rate coefficients from one of the 1s states to the other 1s states or to one of 2p or 3p states are determined (states are in Paschen's notation). This paper reviews the above method-namely the combined diagnostics and modeling in afterglow plasmas. The results from other important approaches, including electron-beam measurement of cross sections, laser pump-probe technique for measuring rate coefficients, and theoretical calculations by R-matrix and distorted-wave models are also discussed. From a comparative study of these results, a fitted mathematical expression of excitation rate coefficients is obtained for the electron temperature range of 1-5 eV, which can be used for the collisional-radiative modeling of low-temperature Ar plasmas. At last, we report the limitations in the present dataset and give some suggestions for future work in this area.

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