论文标题
密度对碰撞等离子体中氧离子化平衡的影响
Effects of density on the oxygen ionisation equilibrium in collisional plasmas
论文作者
论文摘要
碰撞等离子体中最常用的离子种群来自密度无关的冠状近似。在较高的密度,温度条件较低的情况下,一旦稳定水平占人群,电离率就会提高,如果离子重组为rydberg水平,则抑制重组率。结果,离子的形成温度转移,改变了血浆的诊断。为了准确地模拟来自亚稳态水平的电离的效果,新的电子影响,已经计算了电离横截面的氧气,用于直接电离和激发 - 地面的自动离世和亚肌水平。该结果已纳入碰撞辐射建模中,以显示一旦可稳定水平的人群,氧气变化的电离平衡如何变化。已经估计了介电重组的抑制,并且还包括在建模中,与冠状近似相比,密度的变化与密度相比。电离平衡的最终结果用于差分发射测量模型中,以预测O II-VI在太阳过渡区域发出的许多线的线强度。与冠状近似模型的结果相比,O II,O VI和O III-V的O II,O VI和O III-V的组合线的一致性提高了15-40%。尽管仍然存在观察到这些线路的差异,但在很大程度上,这可能是通过观测值的可变性来解释的。
The ion populations most frequently adopted for diagnostics in collisional plasmas are derived from the density independent, coronal approximation. In higher density, lower temperature conditions, ionisation rates are enhanced once metastable levels become populated, and recombination rates are suppressed if ions recombine into Rydberg levels. As a result, the formation temperatures of ions shift, altering the diagnostics of the plasma. To accurately model the effect of ionisation from metastable levels, new electron impact, ionisation cross sections have been calculated for oxygen, both for direct ionisation and excitation--auto-ionisation of the ground and metastable levels. The results have been incorporated into collisional radiative modelling to show how the ionisation equilibrium of oxygen changes once metastable levels become populated. Suppression of dielectronic recombination has been estimated and also included in the modelling, demonstrating the shifts with density in comparison to the coronal approximation. The final results for the ionisation equilibrium are used in differential emission measure modelling to predict line intensities for many lines emitted by O II-VI in the solar transition region. The predictions show improved agreement by 15-40% for O II, O VI and the inter-combination lines of O III-V, when compared to results from coronal approximation modelling. While there are still discrepancies with observations of these lines, this could, to a large part, be explained by variability in the observations.