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首页> 外文期刊>Science Advances >Temperature-resilient solid-state organic artificial synapses for neuromorphic computing
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Temperature-resilient solid-state organic artificial synapses for neuromorphic computing

机译:温度 - 弹性固态有机人工突触的神经形态计算

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Devices with tunable resistance are highly sought after for neuromorphic computing. Conventional resistive memories, however, suffer from nonlinear and asymmetric resistance tuning and excessive write noise, degrading artificial neural network (ANN) accelerator performance. Emerging electrochemical random-access memories (ECRAMs) display write linearity, which enables substantially faster ANN training by array programing in parallel. However, state-of-the-art ECRAMs have not yet demonstrated stable and efficient operation at temperatures required for packaged electronic devices (~90°C). Here, we show that (semi)conducting polymers combined with ion gel electrolyte films enable solid-state ECRAMs with stable and nearly temperature-independent operation up to 90°C. These ECRAMs show linear resistance tuning over a 2× dynamic range, 20-nanosecond switching, submicrosecond write-read cycling, low noise, and low-voltage (±1 volt) and low-energy (~80 femtojoules per write) operation combined with excellent endurance (10sup9/sup write-read operations at 90°C). Demonstration of these high-performance ECRAMs is a fundamental step toward their implementation in hardware ANNs.
机译:具有可调谐电阻的器件是由于神经形态计算的高度追捧。然而,传统的电阻存储器遭受非线性和不对称性调谐和过度写入噪声,降低人工神经网络(ANN)加速器性能。新出现的电化学随机接入存储器(ECRAMS)显示线性度,其通过阵列并行地进行大致更快的ANN训练。然而,最先进的ECRAM在包装电子设备(〜90°C)所需的温度下尚未证明稳定和有效的操作。在此,我们表明(半)导电聚合物与离子凝胶电解质膜联合,使固态肌炎具有稳定且近乎温度无关的操作,可达90℃。这些ECRAMS显示线性电阻调谐在> 2×动态范围内,20纳秒切换,亚微米的写入读取循环,低噪声和低电压(±1伏)和低能量(每次写入时〜80毫毫秒j)具有优异的耐久性(> 10 9 写入读取操作,在90°C)。这些高性能Ecrams的示范是他们在硬件Anns中实施的基本步骤。

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