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 (>10⁹ write-read operations at 90°C). Demonstration of these high-performance ECRAMs is a fundamental step toward their implementation in hardware ANNs.

对于神经形态计算，具有可调节电阻的设备非常受追捧。然而，传统的电阻式存储器遭受非线性和非对称电阻调整以及过多的写入噪声的影响，从而降低了人工神经网络（ANN）加速器的性能。新兴的电化学随机存取存储器（ECRAM）显示写入线性，通过并行进行数组编程，可以大大加快ANN的训练速度。但是，最新的ECRAM尚未证明在封装的电子设备所需的温度（〜90°C）下稳定有效的运行。在这里，我们表明，（半）导电聚合物与离子凝胶电解质薄膜的结合使固态ECRAM能够在高达90°C的温度下稳定且几乎不受温度影响。这些ECRAM在超过2倍的动态范围内显示出线性电阻调整，在90°C下进行⁹次读写操作）。这些高性能ECRAM的演示是在硬件ANN中实现它们的基本步骤。