Memristive synapses with high reproducibility for flexible neuromorphic networks based on biological nanocomposites
Memristive synapses with high reproducibility for flexible neuromorphic networks based on biological nanocomposites
复制标题
基于生物纳米复合材料的灵活神经形态网络具有高重现性的忆阻突触
DOI：
10.1039/c9nr08001e
复制
发表时间：
2020-01-14
期刊：
影响因子：
6.7
通讯作者：
Pan, Shusheng
中科院分区：
文献类型：
--
作者：
Ge, Jun;Li, Dongyuan;Pan, Shusheng
基于生物材料的忆阻突触具有良好的力学和生物学特性，有望用于构建柔性的、可植入的人工神经形态系统。然而，这些生物器件具有相对较差的忆阻开关特性，因此无法满足神经形态网络对高学习精度的要求。在这里，基于卡拉胶纳米复合材料的忆阻突触，具有理想的特性被证明。这些器件显示出具有250个电导状态的高度可再现的模拟阻变行为、低写入噪声、良好的写入线性度、超过10（4）s的高保持力和至少10（6）个脉冲的耐久性。由于自组装银纳米团簇掺杂和纳米锥形电极接触的协同作用，增强的开关性能归因于可控和受限的导电丝生长。此外，器件在1000次弯曲循环后表现出优异的可靠性。包括非理想因素的仿真证明，突触设备阵列可以运行的在线学习的准确率为94.3%。这些发现使生物材料在柔性忆阻器件和神经形态系统中得到更广泛的应用。
Memristive synapses from biomaterials are promising for building flexible and implantable artificial neuromorphic systems due to their remarkable mechanical and biological properties. However, these biological devices have relatively poor memristive switching characteristics, and thus fail to meet the requirement of neuromorphic networks for high learning accuracy. Here, memristive synapses based on carrageenan nanocomposites that possess desirable characteristics are demonstrated. These devices show highly reproducible analog resistive switching behaviors with 250 conductance states, low write noise, good write linearity, high retention of more than 10(4) s and endurance for at least 10(6) pulses. The enhanced switching properties are attributed to controllable and confined conductive filament growth, owing to the synergistic effect of self-assembled silver nanocluster doping and nanocone-shaped electrode contact. Moreover, the devices exhibit excellent reliability after 1000 bending cycles. Simulations including the non-ideal factors prove that the synaptic device array can operate with an online learning accuracy of 94.3%. These findings enable broader applications of biomaterials in flexible memristive devices and neuromorphic systems.