电子回旋共振
原子物理学
等离子体
电子
温度电子
激发
微波食品加热
电离
化学
物理
离子
核物理学
量子力学
有机化学
作者
Jiarui Liu,Yong-Xin Liu,You‐Nian Wang
标识
DOI:10.1088/1361-6595/acc685
摘要
Abstract The electron cyclotron resonance (ECR) effect in a weakly magnetized capacitively coupled radio frequency (RF) plasma was previously observed with optical emission spectroscopy (OES) in experiments and analyzed by particle-in-cell/Monte Carlo collision (PIC/MCC) simulations (Zhang et al 2022 Plasma Sources Sci. Technol. 31 07LT01). When the electron cyclotron frequency equals the RF driving frequency, the electron can gyrate in phase with the RF electric field inside the plasma bulk, being continuously accelerated like microwave ECR, leading to prominent increases in the electron temperature and the excitation or ionization rate in the bulk region. Here, we study further the basic features of the RF ECR and the effects of the driving frequency and the gas pressure on the RF ECR effect by OES and via PIC/MCC simulations. Additionally, a single electron model is employed to aid in understanding the ECR effect. It is found that the maximum of the measured plasma emission intensity caused by ECR is suppressed by either decreasing the driving frequency from 60 MHz to 13.56 MHz or increasing the gas pressure from 0.5 Pa to 5 Pa, which shows a qualitative agreement with the change of the excitation rate obtained in the simulations. Besides, the simulation results show that by decreasing the driving frequency the electron energy probability function (EEPF) changes from a convex to a concave shape, accompanied by a decreased electron temperature in the bulk region. By increasing the gas pressure, the EEPF and the electron temperature show a reduced dependence on the magnitude of the magnetic field. These results suggest that the ECR effect is more pronounced at a higher frequency and a lower gas pressure, primarily due to a stronger bulk electric field, together wih a shorter gyration radius and lower frequency of electron–neutral collisions.
科研通智能强力驱动
Strongly Powered by AbleSci AI