DataVXSmallPaper
journal article·2026-05

Controllable and Cost‐Efficient Three‐Terminal GaN Nano‐Synapse for Brain‐Inspired Computing (Small 27/2026)

Xiushuo Gu, Zhiyang Liu, Jianya Zhang, Xing Huang, Yukun Zhao, Lifeng Bian

Small· Volume 22· Issue 27
Publisher page
Source abstract

Abstract

Neuromorphic Computing In the Research Article (e14447), Jianya Zhang, Xing Huang, Yukun Zhao, Lifeng Bian, and co-workers report a three-terminal synaptic nano-device based on GaN nanowire, which can mimic multiple functions of biological synapses for learning. The postsynaptic current can be enhanced over 1,000 % by modulating electrical gating, corresponding to the hand in cover image. This finding advances the development of controllable and cost-efficient three-terminal nano-devices.
Source: openalex_inverted_index · Quality: baseline

Research context

Nanomaterials

OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Ferroelectric and Negative Capacitance Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China

School of Nano‐Tech and Nano‐Bionics University of Science and Technology of China (USTC) Hefei China

Division of Nano‐Devices Research Suzhou Institute of Nano‐Tech and Nano‐Bionics (SINANO) Chinese Academy of Sciences (CAS) Suzhou China

Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions School of Physical Science and Technology Suzhou University of Science and Technology Suzhou China

School of Petroleum Engineering Xi'an Shiyou University Xi'an Shaanxi China

Guangdong Institute of Semiconductor Micro‐Nano Manufacturing Technology Foshan China

References

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