A Controllable Method to Integrate Single GaN/Ga <sub>2</sub> O <sub>3</sub> Nanowire into Ultralow‐Energy‐Consumption Synaptic Nano‐Device for Neuromorphic Computing (Advanced Optical Materials 35/2025)

Controllable Method for Synaptic Nano-Device In the Research Article (DOI: 10.1002/adom.202502484), Jianya Zhang, Yonglin Huang, Yukun Zhao, and co-workers report a controllable method to integrate single nanowire into synaptic nano-device with ultralow power consumption. It can mimic multiple functions of biological synapses for learning, corresponding to those in cover image. Due to the advantages of simplicity and cost-efficiency, this method has a promising prospect.

Authors

Institutions

Publication Details

Journal
Advanced Optical Materials
Published
2025-12-01
DOI
https://doi.org/10.1002/adom.70678
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Controllable Method to Integrate Single GaN/Ga 2 O 3 Nanowire into Ultralow‐Energy‐Consumption Synaptic Nano‐Device for Neuromorphic Computing (Advanced Optical Materials 35/2025)

Liubin Yang, Yonglin Huang, Yukun Zhao, Yibin Wang et al.
Advanced Optical Materials
Advanced Memory and Neural Computing
article

A Controllable Method to Integrate Single GaN/Ga 2 O 3 Nanowire into Ultralow‐Energy‐Consumption Synaptic Nano‐Device for Neuromorphic Computing (Advanced Optical Materials 35/2025)

Liubin Yang, Yonglin Huang, Yukun Zhao, Yibin Wang, Cheng Lu, Jianya Zhang, Qiyu Xu
article en

Abstract

Controllable Method for Synaptic Nano-Device In the Research Article (DOI: 10.1002/adom.202502484), Jianya Zhang, Yonglin Huang, Yukun Zhao, and co-workers report a controllable method to integrate single nanowire into synaptic nano-device with ultralow power consumption. It can mimic multiple functions of biological synapses for learning, corresponding to those in cover image. Due to the advantages of simplicity and cost-efficiency, this method has a promising prospect.

Advanced Optical MaterialsVol. 13(35)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Suzhou University of Science and Technology (CN), Nanjing University of Posts and Telecommunications (CN), Suzhou Institute of Nano-tech and Nano-bionics (CN), Guangdong Institute of Intelligent Manufacturing (CN)
Openalex Percentile: Top 60%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Controllable Method to Integrate Single GaN/Ga <sub>2</sub> O <sub>3</sub> Nanowire into Ultralow‐Energy‐Consumption Synaptic Nano‐Device for Neuromorphic Computing (Advanced Optical Materials 35/2025) — Liubin Yang, Yonglin Huang, et al. · Advanced Optical Materials (2025) | TGRS Research Map | TGRS