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Particle-in-cell simulations of the ionization process in microwave argon microplasmas

The importance of microwave device reliability and performance for microscale devices motivates a more fundamental understanding of breakdown mechanisms in this regime. Microwave breakdown theories predict breakdown when electron production balances electron loss. Electron production depends strongl...

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Bibliographic Details
Published in:Journal of applied physics 2023-09, Vol.134 (10)
Main Authors: Wang, Haoxuan, Venkattraman, Ayyaswamy, Loveless, Amanda M., Garner, Allen L.
Format: Article
Language:English
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Summary:The importance of microwave device reliability and performance for microscale devices motivates a more fundamental understanding of breakdown mechanisms in this regime. Microwave breakdown theories predict breakdown when electron production balances electron loss. Electron production depends strongly on the ionization rate ν i; however, previous studies either used the measured ν i in macroscale gaps or the empirical formula for DC voltage, inaccurately predicting ν i in microscale gaps. Alternatively, this work characterizes ν i in microwave microplasmas by using particle-in-cell simulations. We calculated ν i in argon gas at atmospheric pressure for 2–10 μm gaps under AC fields ranging from 1 to 1000 GHz. The behavior of ν i may be separated into two regimes by defining a critical frequency f c r that depends on the amplitude of the applied voltage, gap distance, and pressure. For frequency f < f c r, the electrodes collect the electrons during each cycle and the electron number oscillates with the electric field, causing ν i / f to roughly scale with the reduced effective field E e f f / p. For f > f c r, the phase-space plots indicate that the electrons are confined inside the gap, causing the electron number to grow exponentially and v i / p to become a function of E e f f / p. These results elucidate the ionization mechanism for AC fields at microscale gap distances and may be incorporated into field emission-driven microwave breakdown theories to improve their predictive capability.
ISSN:0021-8979
1089-7550
DOI:10.1063/5.0161880