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Long-Term Synaptic Plasticity Emulated in Modified Graphene Oxide Electrolyte Gated IZO-Based Thin-Film Transistors Yi Yang, Juan Wen, Liqiang Guo, Xiang Wan, Peifu Du, Ping Feng, Yi Shi, and Qing Wan ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.6b08515 • Publication Date (Web): 17 Oct 2016 Downloaded from http://pubs.acs.org on October 17, 2016
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ACS Applied Materials & Interfaces
Long-Term Synaptic Plasticity Emulated in Modified Graphene Oxide Electrolyte Gated IZO-Based Thin-Film Transistors Yi Yang,† Juan Wen,‡ Liqiang Guo,*, ‡ Xiang Wan,† Peifu Du,† Ping Feng,*, † Yi Shi,† and Qing Wan*, † †
School of Electronic Science & Engineering, and Collaborative Innovation Centre of
Advanced Microstructures, Nanjing University, Nanjing 210093, China ‡
Micro/Nano Science & Technology Centre, Jiangsu University, Zhenjiang 212013,
China ABSTRACT: Emulating neural behaviors at the synaptic level is of great significance for building neuromorphic computational systems and realizing artificial intelligence. Here, oxide-based electric-double-layer (EDL) thin-film transistors were fabricated by using 3-triethoxysilylpropylamine modified graphene oxide (KH550-GO) electrolyte as the gate dielectrics. Resulting from the EDL effect and electrochemical doping between mobile protons and the indium-zinc-oxide channel layer, long-term synaptic plasticity was emulated in our devices. Synaptic functions including long-term memory, synaptic temporal integration and dynamic filters were successfully reproduced. In particular, spike rate-dependent plasticity (SRDP), one of the basic learning rules of long-term plasticity in neural network, where the synaptic weight changes according to the rate of pre-synaptic spikes, was emulated in our devices. Our results might facilitate the development of neuromorphic computational systems. KEYWORDS: electric-double-layer, graphene oxide, oxide-based transistors, artificial synapses, spike rate-dependent plasticity, neuromorphic computing systems 1 / 25
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INTRODUCTION The idea of building brain-inspired information storage and processing systems can be traced back to 1970.1 Unlike conventional computational systems, neuromorphic systems integrate memory and computation at the architectural level, which gives full play to their advantages in processing not well defined problems.2–3 Neurons and synapses act as two basic units in neural networks. Long-term plasticity is considered to be a key mechanism of basic neuromorphic computation, where the long-lasting connection strength change between neurons can be influenced by the interaction between pre- and post-synaptic activities.4–6 Spike rate-dependent plasticity (SRDP) is one of the basic learning rules of long-term plasticity in human brains.7–10 It indicates that the frequency of pre-synaptic spikes determines the synaptic weight change.11 According to SRDP learning rules, pre-synaptic pulses with high frequency results in potentiation, while pre-synaptic pulses with low frequency results in depression.12–13 Utilizing electronic devices to mimic synaptic computational processes could lead to a way towards building neuromorphic computational systems. A variety of electronic devices have been attempted to realize neuromorphic computing, such as memristors, phase change memory, conductive bridge type memory and ferroelectric devices.14 Several synaptic functions including short-term and long-term memory, paired-pulse facilitation and spike timing-dependent plasticity have been mimicked by using these devices.15–18 Specially, three terminal synaptic devices have the advantage of compatibility and expandability, and has been utilized to reproduce synaptic functions including regulatable plasticity and paired-pulse depression.19-22 2 / 25
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Electric-double-layer (EDL) thin-film transistor (TFT), with an extremely strong electrostatic coupling between the mobile ions/protons in the gate dielectric and the carriers in the channel, has been found to be a good candidate for synaptic devices.23–25 Attributed to the strong capacitive coupling, the carrier density of the channel can be modulated effectively by voltage spikes applied on the gate electrode.26–27 Graphene oxide (GO) has many advantages including low cost, mass production, facile solution process and easy functionalization.28–29 Due to the condensation reaction between –NH2 groups in 3-triethoxysilylpropylamine (KH550) and –COOH groups in GO, GO can be easily modified by KH550 (Figure 1). The reaction product, KH550-GO, has a large amount of –SiOC2H5 on its surface, which could be hydrolyzed to –SiOH.30 These –SiOH groups are able to provide plenty of mobile protons, thus KH550-GO has a high proton conductivity of ~1.2×10−4 S/cm,31 which is an ideal gate dielectric material for EDL TFTs. In this letter, indium-zinc-oxide (IZO) TFTs gated by KH550-GO electrolyte film were fabricated. SRDP synaptic learning rules were successfully reproduced in our synaptic transistors. Furthermore, other important synaptic functions, including long-term memory, temporal integration and dynamic filters, were also demonstrated. Our results might facilitate the development of neuromorphic computing systems.
EXPERIMENTAL SECTION Materials preparation. ITO glass substrates were cut into pieces with an area of 25 mm × 25 mm and then cleaned thoroughly using acetone and ethanol. GO solution was made by dissolving GO powders in dimethyl formamide dispersion (2 mg ml–1). 3 / 25
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To make KH550 modified GO (KH550-GO) electrolyte, the GO solution and KH-550 solution was mixed at a proportion of 1:20 under a constant stirring speed of 120 rpm for 24 h at room temperature. The mixed solution was then hydrolyzed by deionized water and ethyl alcohol at a proportion of 1:1:1 for 30 min. The KH550-GO solution was drop-casted onto ITO glass substrates and dried in air overnight at ambient temperature to get the KH550-GO solid electrolyte film. Device fabrication. The schematic diagram of the fabricated process is shown in Figure 1. IZO patterns were deposited on the KH550-GO film by radio frequency magnetron sputtering using IZO ceramic target (In2O3: ZnO = 10 wt.% : 90 wt.%) in pure Ar ambient masked with a nickel shadow mask. The radio frequency power, the Ar flow rate and the pressure were 100 W, 30 sccm and 0.5 Pa, respectively. A thin IZO channel layer can be self-assembled between the IZO source and drain electrodes due to the reflection of IZO nanoparticles at the mask edge and lateral penetration of IZO nanoparticles with a low incident angle. The thickness of the self-assembled IZO channel layer could be controlled by the distance between the shadow mask and the substrate. The length (L) and width (W) of the IZO channel are ~80 µm and ~1000 µm respectively. The thickness of IZO channel layer and KH550-GO electrolyte film is ~30 nm and ~17.6 µm, respectively. Device characterization. Frequency-dependent specific capacitance and proton conductivity of the KH550-GO electrolyte film were characterized by a Solartron 1260A Impedance Analyzer. Electrical characteristics and synaptic functions of the synaptic transistors were measured by a semiconductor parameter characterization 4 / 25
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system (Keithley 4200 SCS) under a relative humidity of ~50% at room temperature.
RESULTS The leakage current and frequency-dependent capacitance of the KH550-GO electrolyte film were measured using an IZO/KH550-GO/ITO sandwich structure as shown in the inset of Figure 2(a). The absolute leakage current is below 5.1 nA/cm2 in the electric field range from –2.0 to 2.0 kV/cm, as shown in Figure 2(a). The low leakage current of KH550-GO electrolyte film ensures our device working in a field-effect mode. The specific capacitance increases with the decreasing frequency, as shown in Figure 2(b). When the frequency is
