2D Material‐Based Memristor Arrays for Flexible and Thermally Stable Neuromorphic Applications

The practical implementation of 2D material-based memristors for various applications, such as neuromorphic computing and flexible electronics, faces several challenges in scalability and thermal durability. Here, a large-area, flexible, and thermally durable electrochemical metallization memristor array is demonstrated based on an engineered Al<sub>2</sub>O<sub>3</sub>/MoS<sub>2</sub>/graphene heterostructure. A thin Al<sub>2</sub>O<sub>3</sub> layer and graphene serve as dual barriers, effectively suppressing the unintentional metal ion diffusion that typically degrades device reliability under thermal and electrical stress. The fabricated device exhibits excellent uniformity across a 2-inch wafer and maintains stable switching characteristics under mechanical bending down to a 1 mm radius. Finally, simulations based on the device's experimental characteristics confirm its high potential for neuromorphic computing systems, achieving high pattern recognition accuracy. This study provides a comprehensive design strategy for realizing highly reliable, multifunctional memristors for future brain-inspired and flexible electronics.

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Publication Details

Journal
Small
Published
2025-11-27
DOI
https://doi.org/10.1002/smll.202507845
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

2D Material‐Based Memristor Arrays for Flexible and Thermally Stable Neuromorphic Applications

Seunghyeon Ji, Juyeong Hong, Ajit Kumar Katiyar, Jong‐Hyun Ahn et al.
2 citations
Small
Advanced Memory and Neural Computing
1.46
article

2D Material‐Based Memristor Arrays for Flexible and Thermally Stable Neuromorphic Applications

Seunghyeon Ji, Juyeong Hong, Ajit Kumar Katiyar, Jong‐Hyun Ahn, Frank Niklaus, Jong‐Woo Kim, Jonggyu Choi, Seoyeon Yun
article en
2 citations

Abstract

The practical implementation of 2D material-based memristors for various applications, such as neuromorphic computing and flexible electronics, faces several challenges in scalability and thermal durability. Here, a large-area, flexible, and thermally durable electrochemical metallization memristor array is demonstrated based on an engineered Al<sub>2</sub>O<sub>3</sub>/MoS<sub>2</sub>/graphene heterostructure. A thin Al<sub>2</sub>O<sub>3</sub> layer and graphene serve as dual barriers, effectively suppressing the unintentional metal ion diffusion that typically degrades device reliability under thermal and electrical stress. The fabricated device exhibits excellent uniformity across a 2-inch wafer and maintains stable switching characteristics under mechanical bending down to a 1 mm radius. Finally, simulations based on the device's experimental characteristics confirm its high potential for neuromorphic computing systems, achieving high pattern recognition accuracy. This study provides a comprehensive design strategy for realizing highly reliable, multifunctional memristors for future brain-inspired and flexible electronics.

Small
Yonsei University (KR), KTH Royal Institute of Technology (SE)
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.46
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