A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
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DOI：
10.1038/nmat4856
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发表时间：
2017-04-01
期刊：
影响因子：
41.2
通讯作者：
Salleo, Alberto
中科院分区：
文献类型：
--
作者：
van de Burgt, Yoeri;Lubberman, Ewout;Salleo, Alberto
大脑能够进行大规模并行信息处理，而每个突触事件仅消耗1-100 fJ（1，2）。受大脑效率的启发，基于CMOS的神经架构（3）和忆阻器（4，5）正在开发用于模式识别和机器学习。然而，CMOS架构的易失性、设计复杂性和高电源电压，以及忆阻器的随机和高能耗切换，使得使用任一方法实现大脑的互连性、信息密度和能效的路径变得复杂。在这里，我们描述了一种电化学神经形态有机设备（ENODe）与现有的忆阻器从根本上不同的机制。ENODe在低电压和低能量（500个不同的非易失性电导状态，在类似于1V的范围内）下切换，并且在神经网络模拟中实现时实现高分类精度。塑料ENOD也被制造在柔性基板上，使得能够在可拉伸电子系统中集成神经形态功能（6，7）。机械灵活性使ENODes与三维架构兼容，开辟了一条通往与人脑相媲美的极端互连性的道路。
The brain is capable of massively parallel information processing while consuming only similar to 1-100 fJ per synaptic event(1,2). Inspired by the efficiency of the brain, CMOS-based neural architectures(3) and memristors(4,5) are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (500 distinct, non-volatile conductance states within a similar to 1V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems(6,7). Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.