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Capacitively coupled plasmas (CCPs) are widely used in plasma processing applications, where efficient power coupling between the radio frequency (RF) source and the plasma is crucial. In practical CCP systems, impedance matching networks (IMNs) are employed to minimize power reflection. However, the presence of coaxial cables can significantly impact plasma impedance and matching performance. We develop a comprehensive simulation framework for the IMN design of CCPs, fully considering the effects of RF coaxial cables. The model self-consistently couples a distributed transmission line (TL) model, a lumped-element circuit model, and an electrostatic particle-in-cell model. This coupled model is used to investigate the impact of coaxial cables on matching performance under various discharge conditions and cable configurations. The simulation results indicate that the optimal power transmission efficiency was achieved after 6 matching iterations. The power coupled to the CCP increased from 2.7 W before matching to 180.9 W, and the reflection coefficient ultimately decreased to 0.003. The results also reveal that neglecting the cables will lead to a decrease in the power dissipated in the CCP. The proposed method demonstrates effectiveness in achieving impedance matching for different gas pressures (75–300 mTorr) and cable lengths. It can be concluded that the matching speed is faster for an appropriate cable length. This work provides valuable insights into the role of TLs in CCP impedance matching and offers a practical tool for optimizing power delivery in realistic CCP systems with RF coaxial cables. [ABSTRACT FROM AUTHOR]

This paper establishes a fully self‐consistent coupled model of fluid and external circuits. The Kirchhoff equation, the charge conservation equation, and Poisson equation are coupled via boundary conditions and integrated into the fluid model for iterative parameter solution. On the basis of this model, we investigate the influence of impedance matching on single‐frequency capacitively coupled plasma characteristics under different parameters and topological structures. The findings suggest that after several iterations the matching parameters converge. Using different initial circuit parameters, the adjustable capacitance and inductance are eventually adjusted to approximately equal values, resulting in the same optimal matching state, whereas diverse discharge parameters led to different outcomes. Under fixed parameters for two topologies, the power absorption efficiency increases, and the reflection coefficient approaches zero, and the best matching is found. This model can be extended to different fluid programs to investigate the impact of complex external circuits with impedance matching network on plasma discharge while simultaneously seeking best impedance matching. [ABSTRACT FROM AUTHOR]

Impedance matching can maximize the absorbed power transferred to the plasma load and minimize the reflected power, making it critical and indispensable for capacitively coupled plasmas (CCPs). The external circuit usually interacts with the plasma nonlinearly, so the global simulation of the external circuit and plasma and the matching design is very challenging. In this work, an a priori model was proposed to match the plasma impedance and the external circuit impedance for single-frequency CCPs. By calculating the plasma impedance and the matching network, the matching parameters were iteratively updated to find the best matching parameters. By adjusting the capacitance and the inductance of the circuit by numerical simulations, the reflection coefficient can be significantly reduced. At the same time, the plasma power absorption efficiency will be significantly improved. The universality of the method was demonstrated by choosing different initial circuit, discharge, and plasma parameters. The proposed method provides an effective matching design reference for CCPs. [ABSTRACT FROM AUTHOR]

Impedance matching plays a critical role in achieving stable and controllable plasma conditions in capacitive coupled plasma (CCP) systems. However, due to the complex circuit system, the nonlinear relationships between components, and the extensive parameter space of the matching network, finding optimal component values pose significant challenges. To address this, we employ an artificial neural network as a surrogate model for the matching system, leveraging its powerful pattern learning capability for a reliable and efficient search for matching parameters. In this paper, we designed four different parameters as optimization objectives and took the modulus of the reflection coefficient as an example to demonstrate the impedance matching optimization process of a CCP in detail using a particle-in-cell/Monte Carlo collision model. Our approach not only provides an effective optimization direction but also furnishes an entire parameter space that aligns with expectations, rather than just a single point. Moreover, the method presented in this paper is applicable to both numerical simulations and experimental matching parameter optimization. [ABSTRACT FROM AUTHOR]