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Study of ac magnetically enhanced capacitively coupled plasma argon discharges using particle-in-cell simulations

ORAL

Abstract

Magnetically enhanced capacitively coupled plasma (CCP) sources such as magnetically enhanced reactive ion etching (MERIE) reactors have been developed for the high plasma density etching and sputtering of materials for microelectronics fabrication. In a typical MERIE reactor, a static or dc magnetic field is applied parallel to the electrodes to increase the plasma density by trapping more electrons, similar to the mechanism of magnetron sputtering. The operating gas pressure is at tens to hundreds mTorr and the radio frequency (RF) excitation is driven from a few to tens MHz. In this work, an ac magnetically enhanced CCP or MERIE is constructed by applying a transverse ac magnetic field to the low-pressure RF CCP argon discharge. The effects of time-varying magnetic field on the plasma density enhancement and electron energy distribution function (EEDF) are investigated and compared to those of a static or dc magnetic field. The simulations have been conducted with a modified version of the particle-in-cell Monte Carlo collision (PIC-MCC) code, XPDP1, developed by Plasma Theory and Simulation Group (PTSG) formerly at UC Berkeley now at Michigan State University which is a bounded electrostatic code for simulating 1-D plasma devices. The PIC-MCC simulation results show that the enhancement of plasma density by ac magnetic fields could be comparable with while lower than that by a static magnetic field at normal operating pressures. However, the time-varying magnetic field is most effective when its frequency is resonant with that of the applied RF field. In addition, it is found that the ac magnetic field exhibits a higher enhancement than the static one in the lower pressure regime and this crossover can be understood with the analysis of EEDF which provides more physical insight.

Presenters

  • Ming-Chieh Lin

    Multidisciplinary Computational Laboratory, Department of Electrical and Biomedical Engineering, Hanyang University

Authors

  • Kaviya Aranganadin

    Multidisciplinary Computational Laboratory, Department of Electrical and Biomedical Engineering, Hanyang University

  • Guoning Wang

    Multidisciplinary Computational Laboratory, Department of Electrical and Biomedical Engineering, Hanyang University

  • Hua-Yi Hsu

    Department of Mechanical Engineering, National Taipei University of Technology

  • John P. Verboncoeur

    Michigan State University, Department of Electrical and Computer Engineering, Michigan State University

  • Ming-Chieh Lin

    Multidisciplinary Computational Laboratory, Department of Electrical and Biomedical Engineering, Hanyang University