Oxide‐Based Electrolyte‐Gated Transistors for Spatiotemporal Information Processing,Advanced Materials

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Oxide‐Based Electrolyte‐Gated Transistors for Spatiotemporal Information Processing
Advanced Materials ( IF 27.4 ) Pub Date : 2020-10-20 , DOI: 10.1002/adma.202003018
Yue Li _{1,

2} , Jikai Lu _{1,

3} , Dashan Shang _{1,

2} , Qi Liu _{1,

2} , Shuyu Wu _{1,

2} , Zuheng Wu _{1,

2} , Xumeng Zhang _{1,

2} , Jianguo Yang _{1,

2} , Zhongrui Wang _{4,

5} , Hangbing Lv _{1,

2} , Ming Liu _{1,

2}

Affiliation

Spiking neural networks (SNNs) sharing large similarity with biological nervous systems are promising to process spatiotemporal information and can provide highly time‐ and energy‐efficient computational paradigms for the Internet‐of‐Things and edge computing. Nonvolatile electrolyte‐gated transistors (EGTs) provide prominent analog switching performance, the most critical feature of synaptic element, and have been recently demonstrated as a promising synaptic device. However, high performance, large‐scale EGT arrays, and EGT application for spatiotemporal information processing in an SNN are yet to be demonstrated. Here, an oxide‐based EGT employing amorphous Nb₂O₅ and Li_xSiO₂ is introduced as the channel and electrolyte gate materials, respectively, and integrated into a 32 × 32 EGT array. The engineered EGTs show a quasi‐linear update, good endurance (10⁶) and retention, a high switching speed of 100 ns, ultralow readout conductance (<100 nS), and ultralow areal switching energy density (20 fJ µm⁻²). The prominent analog switching performance is leveraged for hardware implementation of an SNN with the capability of spatiotemporal information processing, where spike sequences with different timings are able to be efficiently learned and recognized by the EGT array. Finally, this EGT‐based spatiotemporal information processing is deployed to detect moving orientation in a tactile sensing system. These results provide an insight into oxide‐based EGT devices for energy‐efficient neuromorphic computing to support edge application.

中文翻译：

用于时空信息处理的氧化物基电解质门控晶体管

与生物神经系统具有很大相似性的尖峰神经网络 (SNN) 有望处理时空信息，并且可以为物联网和边缘计算提供高度省时省力的计算范式。非易失性电解质门控晶体管（EGT）提供突出的模拟开关性能，这是突触元件最关键的特征，并且最近被证明是一种很有前途的突触装置。然而，用于 SNN 中时空信息处理的高性能、大规模 EGT 阵列和 EGT 应用尚待证明。在这里，使用非晶 Nb ₂ O ₅和 Li _x SiO ₂的氧化物基 EGT分别作为沟道和电解质栅极材料引入，并集成到 32 × 32 EGT 阵列中。该工程化EGTS示出了准线性更新，良好的耐力（10 ⁶）和保留，100ns的高开关速度，超低读出电导（< 100纳秒），和超低面开关能量密度（20 FJ μ米^-2）。突出的模拟切换性能被用于具有时空信息处理能力的 SNN 的硬件实现，其中 EGT 阵列能够有效地学习和识别具有不同时序的尖峰序列。最后，这种基于 EGT 的时空信息处理被用于检测触觉传感系统中的移动方向。这些结果提供了对基于氧化物的 EGT 设备的深入了解，用于节能神经形态计算以支持边缘应用。

更新日期：2020-11-25

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