Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.

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

cost-effectively processed at room temperature, and to volumetrically uptake large amounts of electrolytes, OEDs have recently garnered much interest for applications in bioelectronics. [1][2][3] These include biosensing, energy storage, neural recording, and stimulation, [4,5] drug delivery, [6] and electroceuticals [7] to name a few. Out of the many available architectures, a device of choice that has been heavily investigated in recent years is the organic electrochemical transistor (OECT). In a typical OECT device, the conductivity of a polymer channel, which is probed by a set of source and drain electrodes, is actively controlled by varying the voltage applied between the channel and a third gate electrode both of which reside in the same electrolyte solution. The choice for gate materials, channel materials, electrolyte solutions, and device dimensions can all be designed to obtain desired device characteristics. Thin photolithographically defined devices, for instance, are favored for high speed (>1 kHz) operation whereas large devices with thick polymer channels are more often chosen for their high transconductance. [8][9][10] In general, OECTs operate at relatively low voltages (<1 V) that are suitable for aqueous environments and biological tissues, and have been successfully used to monitor the integrity of barrier tissues, [11,12] in vitro glucose concentrations [13,14] and in vivo neural activities. [15] In OECTs, ions penetrate the whole polymer film, as facilitated by the swelling processes induced by the solvent. While such process is not strictly necessary, as ionic liquids have been shown to also induce transistor-like behavior in conjugated polymers, [16,17] compared to ionic liquid-gated devices, OECTs provide the opportunity to decouple ionic transport, through swelling caused by the electrolyte solvent, from the ability of the ions to generate mobile charges in the polymer.Despite recent advances in device fabrication and materials development, however, only a select few polymers have been found to stably operate as active OECT channels in aqueous environments. Current state-of-the-art OECTs are fabricated using the highly conductive mixture of poly(3,4ethylenedioythiophene) doped with poly(styrene sulphonate) (PEDOT:PSS). [8] While this materials blend exhibits high transconductance and good stability, the details of the chemical composition are often unknown due to the proprietary nature A general method and accompanying guidelines for fabricating both nonaqueous and aqueous based organic electrochemical devices (OECTs) using water-insoluble hydrophobic semiconducting polymers are presented. By taking advantage of the interactions of semiconducting polymers in certain organic solvents and the formation of a stable liquid-liquid interface between such solvents and water, OECTs with high transconductance, ON/OFF ratios of up to 10 6 , and enhancements in stability are successfully fabricated. Additionally, key fundamental properties are extracted of both the device and the active channel ma...

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and read out of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10nA read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array [1] based upon a polymer redox transistor connected to a volatile conductive-bridge memory (CBM). Selective and linear programming of a transistor array is executed in parallel by overcoming the bridging threshold of the CBMs. Synaptic weight readout with currents <10nA is achieved by diluting the conductive polymer in an insulating channel to decrease the conductance. The redox transistors endure > 109 ‘read-write’ operations and support > 1MHz ‘read-write’ frequencies. [1] Fuller et. al. Science, 2019 (in press)