Emulation of Synaptic Plasticity in WO3-Based Ion-Gated Transistors

Ramin Karimi Azari; Luan Pereira Camargo; José Ramón Herrera Garza; Liam Collins; Wan− Yu Tsai; Lariel Chagas da Silva Neres; Patrick Dang; Martin Schwellberger Barbosa; Clara Santato

doi:10.1002/aelm.202400807

Emulation of Synaptic Plasticity in WO₃-Based Ion-Gated Transistors

Ramin Karimi Azari, Luan Pereira Camargo, José Ramón Herrera Garza, Liam Collins, Wan− Yu Tsai, Lariel Chagas da Silva Neres, Patrick Dang, Martin Schwellberger Barbosa, Clara Santato

Functional Atomic Force Microscopy Group

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Neuromorphic systems, inspired by the human brain, promise significant advancements in computational efficiency and power consumption by integrating processing and memory functions, thereby addressing the von Neumann bottleneck. This paper explores the synaptic plasticity of a WO₃-based ion-gated transistor (IGT) in [EMIM][TFSI] and a 0.1 mol L⁻¹ LiTFSI in [EMIM][TFSI] for neuromorphic computing applications. Cyclic voltammetry (CV), transistor characteristics, and atomic force microscopy (AFM) force–distance (FD) profiling analyses reveal that Li⁺ brings about ion intercalation, together with higher mobility and conductance, and slower response time (τ). WO₃ IGTs exhibit spike amplitude-dependent plasticity (SADP), spike number-dependent plasticity (SNDP), spike duration-dependent plasticity (SDDP), frequency-dependent plasticity (FDP), and paired-pulse facilitation (PPF), which are all crucial for mimicking biological synaptic functions and understanding how to achieve different types of plasticity in the same IGT. The findings underscore the importance of selecting the appropriate ionic medium to optimize the performance of synaptic transistors, enabling the development of neuromorphic systems capable of adaptive learning and real-time processing, which are essential for applications in artificial intelligence (AI).

Original language	English
Article number	2400807
Journal	Advanced Electronic Materials
Volume	11
Issue number	8
DOIs	https://doi.org/10.1002/aelm.202400807
State	Published - Jun 2025

Funding

Research funded by Air Force Office of Scientific Research (AFOSR/SOARD, USA) under award number FA9550-23-1-0575. AFM was conducted as part of a user project at the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory (User project CNMS2023-A-01765). C.S. acknowledges NSERC (Discovery Grant) and the Canada Research Chairs for financial support. LCdSN acknowledges the financial support of FAPESP (2022/03553-0), CAPES-PROEX and CNPq (304899/2023-2). LPC thanks to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the Doctorate scholarship and Emerging Leaders of Americas Program (ELAP), support of Global Affairs Canada. Research funded by Air Force Office of Scientific Research (AFOSR/SOARD, USA) under award number FA9550‐23‐1‐0575. AFM was conducted as part of a user project at the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory (User project CNMS2023‐A‐01765). C.S. acknowledges NSERC (Discovery Grant) and the Canada Research Chairs for financial support. LCdSN acknowledges the financial support of FAPESP (2022/03553‐0), CAPES‐PROEX and CNPq (304899/2023‐2). LPC thanks to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the Doctorate scholarship and Emerging Leaders of Americas Program (ELAP), support of Global Affairs Canada.

Keywords

WO films
ion gated transistors
ion gating media
ion intercalation
neuromorphic computing
synaptic plasticity
synaptic transistors

Access to Document

10.1002/aelm.202400807

Cite this

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abstract = "Neuromorphic systems, inspired by the human brain, promise significant advancements in computational efficiency and power consumption by integrating processing and memory functions, thereby addressing the von Neumann bottleneck. This paper explores the synaptic plasticity of a WO3-based ion-gated transistor (IGT) in [EMIM][TFSI] and a 0.1 mol L−1 LiTFSI in [EMIM][TFSI] for neuromorphic computing applications. Cyclic voltammetry (CV), transistor characteristics, and atomic force microscopy (AFM) force–distance (FD) profiling analyses reveal that Li+ brings about ion intercalation, together with higher mobility and conductance, and slower response time (τ). WO3 IGTs exhibit spike amplitude-dependent plasticity (SADP), spike number-dependent plasticity (SNDP), spike duration-dependent plasticity (SDDP), frequency-dependent plasticity (FDP), and paired-pulse facilitation (PPF), which are all crucial for mimicking biological synaptic functions and understanding how to achieve different types of plasticity in the same IGT. The findings underscore the importance of selecting the appropriate ionic medium to optimize the performance of synaptic transistors, enabling the development of neuromorphic systems capable of adaptive learning and real-time processing, which are essential for applications in artificial intelligence (AI).",

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