Organic semiconductors have emerged as an attractive class of materials for neuromorphic computing applications, particularly in crossbar arrays for artificial neural network (ANN) accelerators. Here, one of the last persistent challenges facing organic materials for adoption in these applications is addressed by developing a fabrication process capable of lithographically patterning vertical, three‐terminal electrochemical random‐access memories (ECRAMs). Central to the realization of this device architecture is the development of a hybrid electrolyte system: a porous inorganic matrix permeated with an ionic liquid, which enables vertical stacking of the organic semiconductor channel and gate. The resulting stacked hybrid organic/inorganic ECRAMs (SHOEs) exhibit superior dynamic range to comparable lateral devices (>2×), exceptional cycling endurance (>109Write–Read Cycles), low energy switching (2.7 pJ), and can be fabricated with dimensions limited by lithographic resolution. The fabrication process developed allows for independent control over device channel, electrolyte, and gate dimensions, and by reducing channel lengths down to a single micron, the fabricated devices can operate (Write+Read) at >MHz speeds. Further, the hybrid electrolyte design provides an effective means to confine an ionic liquid for use in other electrolyte‐gated devices.
Recent breakthroughs in artificial neural networks (ANNs) have spurred interest in efficient computational paradigms where the energy and time costs for training and inference are reduced. One promising contender for efficient ANN implementation is crossbar arrays of resistive memory elements that emulate the synaptic strength between neurons within the ANN. Organic nonvolatile redox memory has recently been demonstrated as a promising device for neuromorphic computing, offering a continuous range of linearly programmable resistance states and tunable electronic and electrochemical properties, opening a path toward massively parallel and energy efficient ANN implementation. However, one of the key issues with implementations relying on electrochemical gating of organic materials is the state‐retention time and device stability. Here, revealed are the mechanisms leading to state loss and cycling instability in redox‐gated neuromorphic devices: parasitic redox reactions and out‐diffusion of reducing additives. The results of this study are used to design an encapsulation structure which shows an order of magnitude improvement in state retention and cycling stability for poly(3,4‐ethylenedioxythiophene)/polyethyleneimine:poly(styrene sulfonate) devices by tuning the concentration of additives, implementing a solid‐state electrolyte, and encapsulating devices in an inert environment. Finally, a comparison is made between programming range and state retention to optimize device operation.
more » « less- Award ID(s):
- 1739795
- NSF-PAR ID:
- 10462925
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Electronic Materials
- Volume:
- 5
- Issue:
- 2
- ISSN:
- 2199-160X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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 (>10 9 write-read operations at 90°C). Demonstration of these high-performance ECRAMs is a fundamental step toward their implementation in hardware ANNs.more » « less
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