Temperature-resilient solid-state organic artificial synapses for neuromorphic computing

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 (similar to 90 degrees 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 degrees C. These ECRAMs show linear resistance tuning over a >2x dynamic range, 20-nanosecond switching, submicrosecond write-read cycling, low noise, and low-voltage (+/- 1 volt) and low-energy (similar to 80 femtojoules per write) operation combined with excellent endurance (>10(9) write-read operations at 90 degrees C). Demonstration of these high-performance ECRAMs is a fundamental step toward their implementation in hardware ANNs.