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Monolithic 3D-Integrated All-Solid Ion-Gated Carbon Nanotube Transistors With Tunable Ionic Conductance for
Haksoon Jung1,2,3, Hanbin Cho4, Yongwoo Lee1,2
1School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, Republic of Korea.
Advanced Materials (Deerfield Beach, Fla.)
|June 30, 2026
Summary
We developed carbon nanotube solid-ion-gated transistors (sIGTs) with tunable ionic dynamics for neuromorphic computing. These devices enable precise control over ion movement, paving the way for advanced electronic applications.
Area of Science:
- Materials Science
- Nanotechnology
- Electronics Engineering
Background:
- Ion-gated transistors (IGTs) show time-dependent behavior due to ion motion, but practical use is hindered by poor control over ion dynamics and integration challenges.
- Existing IGTs lack compatibility with scalable thin-film processing, limiting their widespread application.
Purpose of the Study:
- To present novel carbon nanotube (CNT) solid-ion-gated transistors (sIGTs) with tunable ionic dynamics.
- To demonstrate compatibility with wafer-scale thin-film processing and explore their potential in neuromorphic computing.
Main Methods:
- Engineered tunable ionic conductance through ionic content and thickness scaling (sub-micron regime).
- Fabricated wafer-scale CNT sIGTs on flexible substrates and demonstrated robust DC operation.
- Investigated frequency-dependent gate modulation using electrical impedance spectroscopy and small-signal analysis.
Main Results:
- Achieved tunable ionic time constants ranging from microseconds to milliseconds.
- Demonstrated robust DC operation and wafer-scale fabrication of CNT sIGTs.
- Established a clear relationship between ionic conductance and frequency-dependent device response.
Conclusions:
- CNT sIGTs offer wide-range engineering of ionic dynamics, overcoming limitations of traditional IGTs.
- The developed devices are compatible with scalable thin-film processing and flexible substrates.
- Monolithic 3D integration of CNT sIGTs enables compact dual-timescale physical reservoirs for neuromorphic computing applications.
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