Thermally Engineered Sodium‐Embedded Alumina with Programmable Synaptic Plasticity for Neuromorphic Transistors

ABSTRACT The growing demand for artificial intelligence (AI) has prompted the development of neuromorphic hardware capable of efficient, parallel, and low‐power computation. To meet the requirements for integration and environmental stability in AI systems, neuromorphic transistors based on robust solid‐state materials are essential. Here, we report an all‐metal‐oxide neuromorphic transistor that employs sodium‐embedded alumina (SEA) as a solid‐state electrolyte and indium‐gallium‐zinc oxide as the semiconducting channel. A thermal annealing process was used to tailor the chemical composition of SEA, enabling precise control over synaptic plasticity and the deterministic realization of both short‐term and long‐term plasticity. The long‐term devices exhibited stable excitatory/inhibitory postsynaptic responses, long‐term potentiation/depression, and paired‐pulse facilitation. Furthermore, we demonstrated neuromorphic circuits including a reconfigurable logic gate (AND and OR), an analog comparator, and a multiply–accumulate array that performed analog signal multiplication and summation using programmable synaptic weights. This study highlights the potential of all‐solid‐state neuromorphic transistors for neuromorphic and analog computing relevant to future AI systems.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-05-01
DOI
https://doi.org/10.1002/adfm.202600078
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Thermally Engineered Sodium‐Embedded Alumina with Programmable Synaptic Plasticity for Neuromorphic Transistors

Yonghyun Albert Kwon, Dong‐Hwan Kim, Seong-Jin Park, Dong Yeon Won et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

Thermally Engineered Sodium‐Embedded Alumina with Programmable Synaptic Plasticity for Neuromorphic Transistors

Yonghyun Albert Kwon, Dong‐Hwan Kim, Seong-Jin Park, Dong Yeon Won, Seongchan Kim, Jeong Ho Cho, Jaeyeon Kim, Youngjae Yoo
article en

Abstract

ABSTRACT The growing demand for artificial intelligence (AI) has prompted the development of neuromorphic hardware capable of efficient, parallel, and low‐power computation. To meet the requirements for integration and environmental stability in AI systems, neuromorphic transistors based on robust solid‐state materials are essential. Here, we report an all‐metal‐oxide neuromorphic transistor that employs sodium‐embedded alumina (SEA) as a solid‐state electrolyte and indium‐gallium‐zinc oxide as the semiconducting channel. A thermal annealing process was used to tailor the chemical composition of SEA, enabling precise control over synaptic plasticity and the deterministic realization of both short‐term and long‐term plasticity. The long‐term devices exhibited stable excitatory/inhibitory postsynaptic responses, long‐term potentiation/depression, and paired‐pulse facilitation. Furthermore, we demonstrated neuromorphic circuits including a reconfigurable logic gate (AND and OR), an analog comparator, and a multiply–accumulate array that performed analog signal multiplication and summation using programmable synaptic weights. This study highlights the potential of all‐solid‐state neuromorphic transistors for neuromorphic and analog computing relevant to future AI systems.

Advanced Functional Materials
Yonsei University (KR), Kyungpook National University (KR), Chung-Ang University (KR), Sungkyunkwan University (KR)
Life below water
Openalex Percentile: Top 11%
Advanced Memory and Neural Computing
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Thermally Engineered Sodium‐Embedded Alumina with Programmable Synaptic Plasticity for Neuromorphic Transistors — Yonghyun Albert Kwon, Dong‐Hwan Kim, et al. · Advanced Functional Materials (2026) | TGRS Research Map | TGRS