Imitating neuro-plasticity in SrTiO3 based synaptic optoelectronic memristor for in-memory computing applications

Recently, perovskite oxide-based synaptic optoelectronic memristors (SOMs) present a favorable path toward the advancement of neuromorphic (or in-memory) computing. In this study, we propose a SrTiO3 (STO) functional layer-based simple and transparent two-terminal memristor device stacked with ITO/STO/ITO/glass, which shows improved resistive switching behavior after post-oxide nitrogen annealing treatment at 300 °C. The annealed device shows more stable resistive switching characteristics compared to the unannealed device, with a low set voltage (+0.9 V) and an enhanced memory window (∼35). The presence of nitrogen in the STO layer assists in confining the conductive filament path, which helps to enhance the device's uniformity and stability. The device successfully imitates key biological synaptic behaviors, such as long-term potentiation/depression, paired pulse facilitaion (PPF), and spike timing-dependent plasticity. In addition, artificial neural network models with convolutional layers and vision transformer architectures are simulated for image classification tasks on the extended- and fashion-modified National Institute of Standards and Technology datasets with ∼88% and ∼83% accuracy, respectively. The same device was illuminated with violet light (wavelength: 405 nm) at 40 mW/cm2 and produced the excitatory postsynaptic current response that gradually decayed under a dark environment. The exposure conditions are adjusted to simulate short- to long-term memory transition, optical PPF, and image sharpening functions. Along with the learning phase, the impact of illumination is also analyzed on the forgetting (or memory) phase of the current response, which is further utilized for simulating the image memory function. These findings emphasize the remarkable potential of the STO-based SOM for use in in-memory computing applications.

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Journal
Journal of Applied Physics
Published
2026-03-09
DOI
https://doi.org/10.1063/5.0306671
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Imitating neuro-plasticity in SrTiO3 based synaptic optoelectronic memristor for in-memory computing applications

T. -Y. Tseng, Saransh Shrivastava, Hans Juliano, Stephen Ekaputra Limantoro et al.
Journal of Applied Physics
Advanced Memory and Neural Computing
article

Imitating neuro-plasticity in SrTiO3 based synaptic optoelectronic memristor for in-memory computing applications

T. -Y. Tseng, Saransh Shrivastava, Hans Juliano, Stephen Ekaputra Limantoro, Phan Ai Linh Uong
article en

Abstract

Recently, perovskite oxide-based synaptic optoelectronic memristors (SOMs) present a favorable path toward the advancement of neuromorphic (or in-memory) computing. In this study, we propose a SrTiO3 (STO) functional layer-based simple and transparent two-terminal memristor device stacked with ITO/STO/ITO/glass, which shows improved resistive switching behavior after post-oxide nitrogen annealing treatment at 300 °C. The annealed device shows more stable resistive switching characteristics compared to the unannealed device, with a low set voltage (+0.9 V) and an enhanced memory window (∼35). The presence of nitrogen in the STO layer assists in confining the conductive filament path, which helps to enhance the device's uniformity and stability. The device successfully imitates key biological synaptic behaviors, such as long-term potentiation/depression, paired pulse facilitaion (PPF), and spike timing-dependent plasticity. In addition, artificial neural network models with convolutional layers and vision transformer architectures are simulated for image classification tasks on the extended- and fashion-modified National Institute of Standards and Technology datasets with ∼88% and ∼83% accuracy, respectively. The same device was illuminated with violet light (wavelength: 405 nm) at 40 mW/cm2 and produced the excitatory postsynaptic current response that gradually decayed under a dark environment. The exposure conditions are adjusted to simulate short- to long-term memory transition, optical PPF, and image sharpening functions. Along with the learning phase, the impact of illumination is also analyzed on the forgetting (or memory) phase of the current response, which is further utilized for simulating the image memory function. These findings emphasize the remarkable potential of the STO-based SOM for use in in-memory computing applications.

Journal of Applied PhysicsVol. 139(10)
National Yang Ming Chiao Tung University (TW)
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
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