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.

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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

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article

Highly flexible vertical electrolyte-gated metal oxide transistors for neuromorphic electronics

Tobin Jay Marks, Litao Sun, Binghao Wang, Enbo Xue et al.
Proceedings of the National Academy of Sciences
Advanced Memory and Neural Computing
article

Highly flexible vertical electrolyte-gated metal oxide transistors for neuromorphic electronics

Tobin Jay Marks, Litao Sun, Binghao Wang, Enbo Xue, Giacomo Forti, A. Facchetti, Jae–Hyeok Cho, Chen Li, Xianyu Wang, Wei Huang, Shisheng Chen, Qing Ma, Haoyang Wang, Xuyang Feng, Yao Yao, Limei Liu, Lifeng Chi, Di Xue, Lizhen Huang
article en

Abstract

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.

Proceedings of the National Academy of SciencesVol. 123(32)
Georgia Institute of Technology (US), Southeast University (BD), Materials Research Center (IN), Yangzhou University (CN)
National Science Foundation, National Natural Science Foundation of China, National Key Research and Development Program of China, Air Force Office of Scientific Research
Openalex Percentile: Top 17%
Advanced Memory and Neural Computing
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