Relaxor Antiferroelectric Dynamics for Neuromorphic Computing

Relaxor antiferroelectric (AFE) materials display a gradual polarization response and high energy storage density with polarization slowly reverting after removing an external field. This distinctive polarization-switching behavior closely resembles synaptic plasticity in biological nervous systems, presenting substantial potential for neuromorphic computing applications. Especially, its 2D scenario exhibits unique physical properties and maintains stability at atomic thickness due to their antipolar alignment, which effectively eliminates the depolarization field effect. Such stable 2D relaxor AFE materials offer significant advantages for integrating these materials into modern electronic devices for neuromorphic computing. In this study, the potential of a novel quaternary layered AFE material, CuBiP₂Se₆ (CBPS), is explored for neuromorphic device applications. CBPS exhibits a broad range of light absorption and stable relaxor AFE behavior, rendering it an outstanding candidate for optoelectronic synaptic devices. High-quality CBPS is synthesized and its AFE properties through various characterization techniques are verified. CBPS-based synaptic devices demonstrate dual-mode tunable resistance plasticity stimulated by both electrical and optical inputs, demonstrating the capacity to perform in-sensor computing for image restoration tasks. These findings suggest that relaxor AFE materials like CBPS could provide a robust platform for various brain-inspired applications, particularly in neuromorphic computing, and artificial visual systems.

Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2025-04-24
DOI
https://doi.org/10.1002/adma.202419204
Citations
57
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
41.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relaxor Antiferroelectric Dynamics for Neuromorphic Computing

Dongliang Yang, Weiwei Meng, Ce Li, Fei Xue et al.
57 citations
Advanced Materials
Advanced Memory and Neural Computing
41.63
article

Relaxor Antiferroelectric Dynamics for Neuromorphic Computing

Dongliang Yang, Weiwei Meng, Ce Li, Fei Xue, Jieyu You, Linfeng Sun, Huihan Li, Ruixiang Fei, Yutao Li, Jiarui Wang, Zhongyi Wang, Wei Miao, Qianyu Zhang, Zirui Zhang, Tianze Yu, Weili Zhen, Yinan Lin
article en
57 citations

Abstract

Relaxor antiferroelectric (AFE) materials display a gradual polarization response and high energy storage density with polarization slowly reverting after removing an external field. This distinctive polarization-switching behavior closely resembles synaptic plasticity in biological nervous systems, presenting substantial potential for neuromorphic computing applications. Especially, its 2D scenario exhibits unique physical properties and maintains stability at atomic thickness due to their antipolar alignment, which effectively eliminates the depolarization field effect. Such stable 2D relaxor AFE materials offer significant advantages for integrating these materials into modern electronic devices for neuromorphic computing. In this study, the potential of a novel quaternary layered AFE material, CuBiP₂Se₆ (CBPS), is explored for neuromorphic device applications. CBPS exhibits a broad range of light absorption and stable relaxor AFE behavior, rendering it an outstanding candidate for optoelectronic synaptic devices. High-quality CBPS is synthesized and its AFE properties through various characterization techniques are verified. CBPS-based synaptic devices demonstrate dual-mode tunable resistance plasticity stimulated by both electrical and optical inputs, demonstrating the capacity to perform in-sensor computing for image restoration tasks. These findings suggest that relaxor AFE materials like CBPS could provide a robust platform for various brain-inspired applications, particularly in neuromorphic computing, and artificial visual systems.

Advanced MaterialsVol. 37(27)
Beijing Institute of Technology (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality
Affordable and clean energy
Openalex Percentile: Top 0%
Advanced Memory and Neural Computing
41.63
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.