Deeply-scaled GaN high electron mobility transistors for RF applications
Author(s)
Lee, Dong Seup
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Alternative title
Deeply-scaled GaN high electron mobility transistors for radio frequency applications
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Tomás Palacios.
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Due to the unique combination of large critical breakdown field and high electron velocity, GaN-based high electron mobility transistors (HEMTs) have great potential for next generation high power RF amplifiers. The performance of GaN devices has increased continuously in the last two decades. However, in spite of the improvements, there are still several critical issues limiting the high frequency operation of these devices. One of the key challenges is the lower-than-expected maximum current gain cutoff frequency (fT) of deeply-scaled GaN HEMTs. The fT of the short channel devices is well below both projections from maximum frequency in the long channel devices and theoretical expectations based on material properties. Another important issue is a roll-off of the device frequency performance under wide bias range, which limits the large-signal high speed operation in the deeply-scaled devices. This thesis focuses on these two important problems and investigates them both analytically and experimentally. First, through systematic study of the transistor delay, the critical factors limiting intrinsic and extrinsic device speed are clarified and several technologies are demonstrated to overcome these limits. This has allowed the demonstration of state-of-the-art high frequency performance GaN HEMTs. Second, in order to understand the origin of the decrease in device speed at high drain and gate bias, a new extraction method and novel transistor structure have been developed, which provide an excellent guide for future device optimization.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. Cataloged from PDF version of thesis. Includes bibliographical references (pages 173-186).
Date issued
2014Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.