Controllable Transformation Matching Networks for Efficient RF Impedance Matching
Name
rafaislam-krafa-sm-eecs-2024-thesis.pdf
Description
Thesis PDF
Size
6.19 MB
Format
Adobe PDF
Checksum (MD5)
ae2f35f6b6877f445c110167a3a00997
Author(s)
Rafa Islam, Khandoker N
Advisor(s)
Perreault, David J.
Date Issued
February 2024
Publisher
Massachusetts Institute of Technology
Abstract
Efficient and controlled delivery of radio-frequency (rf) power for semiconductor plasma processing typically relies upon tunable matching networks to transform the variable plasma load impedance to a fixed impedance suitable for most rf power amplifiers. Plasma applications require fast tuning speed with precise control from the matching networks while operating at a high frequency range. However, it is difficult to meet the requirements for many semiconductor plasma applications with conventional impedance matching solutions due to their limited response speeds. This slow speed comes from the presence of mechanical components in the matching network, since they can be tuned only mechanically. This work introduces a novel controllable transformation matching network (CTMN) intended to address the need for high-speed, tunable impedance matching.
The design of the CTMN employs a two-port controllable switching network coupled with a high-Q passive network, enabling rapid voltage modulation and dynamic reactance tuning (dynamic frequency tuning) to swiftly accommodate both resistive and reactive load variations. Control strategies are introduced to maintain zero-voltage switching as needed to minimize switching losses. This approach is substantiated through simulations, which indicate the CTMN’s capability to achieve precise impedance matching with the potential for substantially faster response times (in the 𝜇 s range) than traditional systems. It is anticipated that the proposed approach will enable ultra-fast, high-efficiency tunable impedance matching to address the needs of modern plasma systems.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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