Flexible BaTiO <sub>3</sub> Ferroelectric Nonvolatile Memory for Neuromorphic Computation

The use of BaTiO<sub>3</sub> (BTO) ferroelectric thin films in flexible ferroelectric memory offers a promising pathway for next-generation nonvolatile memory applications, given BTO's excellent ferroelectric properties, stability, high dielectric constant, and strong fatigue resistance. However, the fabrication of BTO on flexible substrates presents a significant technical challenge. In this study, we achieved high-quality, single-crystalline (111)-oriented BTO films on mica substrates through the design of buffer layers. The BTO films exhibit strong polarization properties (remnant polarization, 2<i>P</i><sub>r</sub> ∼15.63 μC/cm<sup>2</sup>, and saturation polarization, 2<i>P</i><sub>s</sub> ∼36.61 μC/cm<sup>2</sup>), and the flexible BTO devices maintained exceptional stability under bending radii of 3.5 and 6 mm. After 10<sup>7</sup> bipolar switching cycles, polarization showed only minor changes, with a retention time exceeding 10<sup>4</sup> s. We further explored the application of flexible BTO ferroelectric memory in neuromorphic computing. The flexible BTO-based memory demonstrated adjustable synaptic behavior, effectively modulating EPSC (excitatory postsynaptic current) responses through pulse amplitude and width to simulate short-term memory. PPF (paired pulse facilitation) and LTP (long-term potentiation) behaviors verified its synaptic weight modulation capabilities, achieving 91.6% accuracy in neural network-based handwritten digit recognition after 10<sup>3</sup> training cycles. These findings underscore the potential of flexible BTO ferroelectric memory for memory devices and neuromorphic computing, offering promising applications for wearable AI systems.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-03-11
DOI
https://doi.org/10.1021/acsami.4c21545
Citations
10
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
7.30
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article

Flexible BaTiO 3 Ferroelectric Nonvolatile Memory for Neuromorphic Computation

Xingpeng Liu, Yan Cheng, Yiming Peng, Fabi Zhang et al.
10 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
7.30
article

Flexible BaTiO 3 Ferroelectric Nonvolatile Memory for Neuromorphic Computation

Xingpeng Liu, Yan Cheng, Yiming Peng, Fabi Zhang, Guojian Luo, Tangyou Sun, Haiou Li
article en
10 citations

Abstract

The use of BaTiO<sub>3</sub> (BTO) ferroelectric thin films in flexible ferroelectric memory offers a promising pathway for next-generation nonvolatile memory applications, given BTO's excellent ferroelectric properties, stability, high dielectric constant, and strong fatigue resistance. However, the fabrication of BTO on flexible substrates presents a significant technical challenge. In this study, we achieved high-quality, single-crystalline (111)-oriented BTO films on mica substrates through the design of buffer layers. The BTO films exhibit strong polarization properties (remnant polarization, 2<i>P</i><sub>r</sub> ∼15.63 μC/cm<sup>2</sup>, and saturation polarization, 2<i>P</i><sub>s</sub> ∼36.61 μC/cm<sup>2</sup>), and the flexible BTO devices maintained exceptional stability under bending radii of 3.5 and 6 mm. After 10<sup>7</sup> bipolar switching cycles, polarization showed only minor changes, with a retention time exceeding 10<sup>4</sup> s. We further explored the application of flexible BTO ferroelectric memory in neuromorphic computing. The flexible BTO-based memory demonstrated adjustable synaptic behavior, effectively modulating EPSC (excitatory postsynaptic current) responses through pulse amplitude and width to simulate short-term memory. PPF (paired pulse facilitation) and LTP (long-term potentiation) behaviors verified its synaptic weight modulation capabilities, achieving 91.6% accuracy in neural network-based handwritten digit recognition after 10<sup>3</sup> training cycles. These findings underscore the potential of flexible BTO ferroelectric memory for memory devices and neuromorphic computing, offering promising applications for wearable AI systems.

ACS Applied Materials & InterfacesVol. 17(12)
Advanced Materials and Devices (United States) (US), Institute of Navigation (US), Guilin University of Electronic Technology (CN), East China Normal University (CN)
Openalex Percentile: Top 3%
Advanced Memory and Neural Computing
7.30
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