4.6 Article

Equivalent electric circuit model of accurate ion energy control with tailored waveform biasing

期刊

出版社

IOP Publishing Ltd
DOI: 10.1088/1361-6595/ac4c27

关键词

atomic layer etching; atomic layer deposition; equivalent electric circuit; ion energy distribution; switched-mode power converter; tailored waveform biasing

资金

  1. Prodrive Technologies BV [17124]
  2. Netherlands Organization for Scientific Research (NWO)

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This article proposes an improved equivalent electric circuit model for precise control of plasma ion energy, and introduces a parameter identification method based on electrical measurements. Experiments demonstrate the expected accuracy of the proposed model and method.
For atomic scale plasma processing involving precise, (an)isotropic and selective etching and deposition, it is required to precisely control the energy of the plasma ions. Tailored waveforms have been employed to bias the substrate table to accurately control this ion energy. Recent research has shown that switched-mode power converters can be used to generate this kind of waveform, with the benefit of increased energy efficiency and flexibility compared to the traditionally used linear amplifiers. In this article, an improved equivalent electric circuit model of the plasma reactor is proposed to allow simulation and bias waveform optimization. The equivalent electric circuit is analysed for different process phases, including the charge, discharge, and post-discharge phase. The proposed model is suitable for electric circuit simulation and can be used for predicting the electric waveforms and ion energy distributions. Plasma parameters are required as input for the model, thus an empirical parameter identification method based on the electrical measurements of the bias voltage and output current waveforms is introduced. Since these electrical measurements do not interact with the plasma process, the proposed parameter identification method is nonintrusive. Experiments have been carried out, which demonstrate that the proposed model and parameter identification method provide the expected accuracy.

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