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

IF 5.3 2区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY Advanced Electronic Materials Pub Date : 2025-03-20 DOI:10.1002/aelm.202400807
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
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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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wo3基离子门控晶体管突触可塑性的仿真
受人脑启发的神经形态系统,通过整合处理和记忆功能,有望在计算效率和功耗方面取得重大进步,从而解决冯·诺伊曼瓶颈。本文探讨了[EMIM][TFSI]中wo3基离子门控晶体管()和[EMIM][TFSI]中0.1 mol L−1 LiTFSI在神经形态计算中的突触可塑性。循环伏安法(CV)、晶体管特性和原子力显微镜(AFM)力距(FD)分析表明,Li+带来了离子嵌入,同时具有更高的迁移率和电导率,以及更慢的响应时间(τ)。WO3 IGT表现出峰值振幅依赖性可塑性(SADP)、峰值数量依赖性可塑性(SNDP)、峰值持续依赖性可塑性(SDDP)、频率依赖性可塑性(FDP)和配对脉冲促进性(PPF),这些都是模拟生物突触功能和理解如何在同一IGT中实现不同类型可塑性的关键。研究结果强调了选择合适的离子介质来优化突触晶体管性能的重要性,从而使能够自适应学习和实时处理的神经形态系统的发展成为可能,这对于人工智能(AI)的应用至关重要。
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来源期刊
Advanced Electronic Materials
Advanced Electronic Materials NANOSCIENCE & NANOTECHNOLOGYMATERIALS SCIE-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
11.00
自引率
3.20%
发文量
433
期刊介绍: Advanced Electronic Materials is an interdisciplinary forum for peer-reviewed, high-quality, high-impact research in the fields of materials science, physics, and engineering of electronic and magnetic materials. It includes research on physics and physical properties of electronic and magnetic materials, spintronics, electronics, device physics and engineering, micro- and nano-electromechanical systems, and organic electronics, in addition to fundamental research.
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