Unified Physical Modeling of Optical Synaptic Transistors Based on Trap and Ionic Dynamics in Polymer Dielectrics

Optical synaptic transistors employing polymer dielectrics have emerged as promising building blocks for neuromorphic computing due to their low power consumption and rich photo-induced memory behaviors. While extensive experimental studies have demonstrated various synaptic functions, a unified physical understanding of the coupled charge trapping and ionic polarization processes governing device dynamics remains incomplete. In this work, we develop a unified physical model to investigate optical synaptic behaviors in polymer-based transistors with oxide interlayers. The model explicitly describes the time-dependent evolution of photo-induced charge trapping at the semiconductor–dielectric interface and ionic polarization within the polymer dielectric, which jointly modulate the effective threshold voltage of the transistor channel. Based on this framework, key synaptic functions including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and pulse-dependent potentiation are quantitatively reproduced. The model further reveals how dielectric structure and trapping strength govern the transition between short-term and long-term plasticity. This study provides a physically intuitive and experimentally relevant modeling framework for understanding optical synaptic transistors, offering guidance for the rational design and optimization of polymer-based neuromorphic devices. Although simplified, the proposed model captures the essential physics governing optical synaptic behaviors and provides a general framework applicable to a wide class of ion–electronic neuromorphic devices. Experimental measurements are used as physically motivated proxies to validate the multi-timescale structure of the model rather than direct numerical fitting.

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Publication Details

Journal
J — Multidisciplinary Scientific Journal
Published
2026-02-03
DOI
https://doi.org/10.3390/j9010005
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Unified Physical Modeling of Optical Synaptic Transistors Based on Trap and Ionic Dynamics in Polymer Dielectrics

Yuheng Wang, Jun Huang
J — Multidisciplinary Scientific Journal
Advanced Memory and Neural Computing
article

Unified Physical Modeling of Optical Synaptic Transistors Based on Trap and Ionic Dynamics in Polymer Dielectrics

Yuheng Wang, Jun Huang
article en

Abstract

Optical synaptic transistors employing polymer dielectrics have emerged as promising building blocks for neuromorphic computing due to their low power consumption and rich photo-induced memory behaviors. While extensive experimental studies have demonstrated various synaptic functions, a unified physical understanding of the coupled charge trapping and ionic polarization processes governing device dynamics remains incomplete. In this work, we develop a unified physical model to investigate optical synaptic behaviors in polymer-based transistors with oxide interlayers. The model explicitly describes the time-dependent evolution of photo-induced charge trapping at the semiconductor–dielectric interface and ionic polarization within the polymer dielectric, which jointly modulate the effective threshold voltage of the transistor channel. Based on this framework, key synaptic functions including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and pulse-dependent potentiation are quantitatively reproduced. The model further reveals how dielectric structure and trapping strength govern the transition between short-term and long-term plasticity. This study provides a physically intuitive and experimentally relevant modeling framework for understanding optical synaptic transistors, offering guidance for the rational design and optimization of polymer-based neuromorphic devices. Although simplified, the proposed model captures the essential physics governing optical synaptic behaviors and provides a general framework applicable to a wide class of ion–electronic neuromorphic devices. Experimental measurements are used as physically motivated proxies to validate the multi-timescale structure of the model rather than direct numerical fitting.

J — Multidisciplinary Scientific JournalVol. 9(1)
Army Medical University (CN), Xinqiao Hospital (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 68%
Advanced Memory and Neural Computing
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Unified Physical Modeling of Optical Synaptic Transistors Based on Trap and Ionic Dynamics in Polymer Dielectrics — Yuheng Wang, Jun Huang · J — Multidisciplinary Scientific Journal (2026) | TGRS Research Map | TGRS