ALD-Driven Ultra-Thin ZnO Channels for Flexible Electrolytic Neuromorphic Devices

Ultra-thin (4-nm) ZnO films, grown by atomic layer deposition (ALD) at 250 °C with a rate of 2 Å/cycle, enable stable electrical performance in corresponding devices. Low-frequency noise measurements combined with Kelvin probe force microscopy reveal that these ALD-ZnO channels possess the ability to trap carriers and couple ions with electrons. Integrating a sodium-ion electrolyte, the neuromorphic device successfully demonstrates essential synaptic plasticity while reducing the energy consumption per synaptic event by an order of magnitude. Consequently, 2-level encryption and a 5-bit reservoir computing system are experimentally implemented, achieving information concealment and pattern classification, respectively. Furthermore, an artificial nociceptor, constructed by cascading alarm units, exhibits sensitive responses to stimuli as short as 0.1 s. This study demonstrates the significant potential of ALD-fabricated ultra-thin channels for advanced neuromorphic applications.

Authors

Institutions

Publication Details

Journal
IEEE Electron Device Letters
Published
2025-10-13
DOI
https://doi.org/10.1109/led.2025.3620327
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

ALD-Driven Ultra-Thin ZnO Channels for Flexible Electrolytic Neuromorphic Devices

Zhenhai Li, Bingyan Wang, Yao Ni, Huanhuan Wei et al.
IEEE Electron Device Letters
Advanced Memory and Neural Computing
article

ALD-Driven Ultra-Thin ZnO Channels for Flexible Electrolytic Neuromorphic Devices

Zhenhai Li, Bingyan Wang, Yao Ni, Huanhuan Wei, Can Fu, Gang He, Shanshan Jiang, Jiawei Yang, Bo He
article en

Abstract

Ultra-thin (4-nm) ZnO films, grown by atomic layer deposition (ALD) at 250 °C with a rate of 2 Å/cycle, enable stable electrical performance in corresponding devices. Low-frequency noise measurements combined with Kelvin probe force microscopy reveal that these ALD-ZnO channels possess the ability to trap carriers and couple ions with electrons. Integrating a sodium-ion electrolyte, the neuromorphic device successfully demonstrates essential synaptic plasticity while reducing the energy consumption per synaptic event by an order of magnitude. Consequently, 2-level encryption and a 5-bit reservoir computing system are experimentally implemented, achieving information concealment and pattern classification, respectively. Furthermore, an artificial nociceptor, constructed by cascading alarm units, exhibits sensitive responses to stimuli as short as 0.1 s. This study demonstrates the significant potential of ALD-fabricated ultra-thin channels for advanced neuromorphic applications.

IEEE Electron Device LettersVol. 46(12)
Guangdong University of Technology (CN), Anhui University (CN)
Openalex Percentile: Top 71%
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.

ALD-Driven Ultra-Thin ZnO Channels for Flexible Electrolytic Neuromorphic Devices — Zhenhai Li, Bingyan Wang, et al. · IEEE Electron Device Letters (2025) | TGRS Research Map | TGRS