Highly flexible vertical electrolyte-gated metal oxide transistors for neuromorphic electronics
Metal oxide-based electrolyte-gated transistors (EGTs) are attractive for low-power biosensors and neuromorphic systems, but their electrical characteristics has been constrained by a fundamental trade-off between channel downscaling and electrical double layer (EDL) capacitance, resulting in limited transconductance and metrics inferior to that of organic counterparts. Here, we report high-performance and ultraflexible indium gallium zinc oxide (IGZO) EGTs enabled by a vertical device architecture and a nanoscale channel length. We systematically examined how device geometries—including the IGZO-electrode contact area, IGZO thickness, and semiconductor-electrode interface—affect the electrical properties and EDL capacitance, thereby revealing how the vertical structure decouples the channel length from the EDL formation area. Optimized vertical EGTs (vEGTs) exhibit a transconductance of up to 22.5 mS, an on/off current ratio of ~10 5 , ultralow operating voltages below 0.5 V, and pronounced ultraflexibility, maintaining stable performance when bent to a radius of 0.3 mm. Furthermore, vEGTs were integrated into inverter, NOR, and NAND logic circuits operating at voltages as low as 0.1 V. Finally, we demonstrate a closed-loop neuromorphic system in which the slow attenuation of the paired-pulse facilitation index enables adaptive and wireless control of a wearable display in response to a skin-interfaced sensor.
Authors
- Tobin Jay Marks (ORCID: https://orcid.org/0000-0001-8771-0141)
- Litao Sun (ORCID: https://orcid.org/0000-0002-2750-5004)
- Binghao Wang (ORCID: https://orcid.org/0000-0002-9631-6901)
- Enbo Xue (ORCID: https://orcid.org/0009-0006-6955-1806)
- Giacomo Forti
- A. Facchetti
- Jae–Hyeok Cho
- Chen Li (ORCID: https://orcid.org/0000-0002-8438-259X)
- Xianyu Wang (ORCID: https://orcid.org/0000-0001-8001-0740)
- Wei Huang (ORCID: https://orcid.org/0000-0002-0973-8015)
- Shisheng Chen (ORCID: https://orcid.org/0000-0002-8617-4356)
- Qing Ma
- Haoyang Wang
- Xuyang Feng (ORCID: https://orcid.org/0000-0003-4402-4226)
- Yao Yao
- Limei Liu
- Lifeng Chi
- Di Xue
- Lizhen Huang
Institutions
- Georgia Institute of Technology (US)
- Southeast University (BD)
- Materials Research Center (IN)
- Yangzhou University (CN)
Publication Details
- Journal
- Proceedings of the National Academy of Sciences
- Published
- 2026-08-03
- DOI
- https://doi.org/10.1073/pnas.2606103123
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Air Force Office of Scientific Research