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氧化物基忆阻型神经突触器件

刘益春 林亚 王中强 徐海阳

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氧化物基忆阻型神经突触器件

刘益春, 林亚, 王中强, 徐海阳

Oxide-based memristive neuromorphic synaptic devices

Liu Yi-Chun, Lin Ya, Wang Zhong-Qiang, Xu Hai-Yang
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  • 忆阻器具有高密度、低功耗和阻值能够连续可调的特性, 被认为是模拟神经突触最具潜力的候选者. 而金属氧化物, 因其氧离子可迁移, 组分易于调控, 与传统CMOS兼容等优点, 是发展高性能忆阻器件的理想材料. 本文首先介绍了氧化物基忆阻器件阻变行为及其运行机制, 包括数字型和模拟型忆阻器. 主要综述了基于模拟型忆阻器实现的突触器件认知功能模拟, 包括非线性传输特性、时域突触可塑性、经验式学习和联合式学习等. 然后进一步介绍了忆阻型突触器件在模式识别、声音定位、柔性可穿戴和光电神经突触方面的潜在应用. 最后总结展望氧化物基忆阻神经突触在相关领域的可能发展方向.
    Memristors are considered to be the potential candidate for simulating synapses due to their high density, low power consumption and continuously adjustable resistance. Metal oxide is an ideal choice for fabricating memristive devices with high performance due to its advantages of oxygen migration, easy adjustment of components and compatibility with traditional CMOS. In this review paper, the memristive behaviors and operation mechanism of oxide-based memristors including digital-type memristors and analog-type memristors are first introduced. We mainly summarize the cognitive functions simulated by analog-type memristive synapse, including nonlinear-transmission characteristic, synaptic plasticity, learning experience, and non-associative/associative learning. Then, the potential applications of memristive synapse in pattern recognition, sound localization, logic operation, flexibility/transferability and optoelectronic memristive synapse are introduced. Finally, we provide an outlook of the future possible studies of oxide-based memristive synapse in the relevant fields.
      通信作者: 刘益春, ycliu@nenu.edu.cn
      Corresponding author: Liu Yi-Chun, ycliu@nenu.edu.cn
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  • 图 1  (a) 基于Pt/TiO2/Pt结构的数字型忆阻变行为, 插图为器件结构示意图[2]; (b) 基于Pd/WOx/W结构的模拟型忆阻器忆阻行为, 插图为器件结构示意图[19]

    Fig. 1.  (a) The digital memristive hebavior obtained in Pt/TiO2/Pt memristor. The insert is the corresponding structure diagram of the device.[2] (b) the analog memristive habevior obtained in Pd/WOx/W memristor. The insert is the corresponding structure diagram of the device[19]

    图 2  (a, b) Ag/ZnO:Mn/Pt结构忆阻器原位透射电镜图; (c, d) 导电通道内部和外部的能谱图[20]

    Fig. 2.  (a, b) The in situ TEM images of Ag/ZnO:Mn/Pt memristor. (c, d) EDX spectrum collected inside and outside of conductive channels[20]

    图 3  (a-c) Pt/ZnO/Pt 结构忆阻器不同加电时间下的原位透射电镜图; (d-f) 不同扫描时间下的I -V曲线[22]

    Fig. 3.  (a-c) The in situ TEM images of Pt/ZnO/Pt memristor under the voltage sweep with differernt time. (d-f) the corresponding IV measurements of Pt/ZnO/Pt memristor under the voltage sweep with differernt time[22]

    图 4  左侧(a-b)Pt/TiO2-x/Ti器件结构示意图, 其中Pt/TiO2-x界面为肖特基接触, Ti/TiO2-x界面为欧姆接触; 右侧(a-d)电极与TiO2-x层势垒的变化[26]

    Fig. 4.  In the left: (a, b) Structure diagram of Pt/TiO2-x/Ti memristor, in which Pt/TiO2-x presents Schottky contact and Ti/TiO2-x is Ohmic contact. In the right: (a-d) the modulation of barrier between the electrode and TiO2-x layer[26]

    图 5  惠普实验室提出的忆阻模型 (a) 忆阻器结构示意图; (b, c) 计算机模拟忆阻器在电压作用下的电学响应[2]

    Fig. 5.  The memristive model proposed by HP’s lab: (a) Schematic diagram of memristor, (b, c) computer simulated the electrical response of memristor under voltage sweep[2]

    图 6  (a) 非晶InGaZnO基忆阻器件与神经突触结构对应图; (b) 单一脉冲在忆阻器中诱导产生的兴奋性后电流; (c) 不同温度下突触权重的衰减行为, 实现为单e指数拟合曲线; (d) 基于方程3拟合$ -\ln(\tau'^{-1})$)与1000/T之间的关系[27]

    Fig. 6.  (a) The structural diagram of the bilayer α-InGaZnO memristor and a schematic illustration of the synapse between neurons. (b) the EPSC induced by a single pulse. (c) memory decay curves recorded after different numbers of stimuli (dots), the data was fitted by single exponential function. (d) plot of $ -\ln(\tau'^{-1})$ against 1000/T following equation 3[27]

    图 7  (a) 基于Pd/WOx/W结构忆阻器的电学特性; (b) 导电细丝数目模型机制图[31]

    Fig. 7.  (a) The I-V characteristic of Pd/WOx/W memristor. (b) memtistive mechanism diagram of modulating conductive filaments[31]

    图 8  (a) 界面肖特基势垒调制忆阻模型示意图; (b) 基于Pt/SrTiO3/Nb-SrTiO3结构忆阻器在脉冲模式下的阻变行为[29]

    Fig. 8.  (a) Schematic diagram of the memristive model by modulating Schottky barrier. (b) the potentiation and depression of Pt/SrTiO3/Nb-SrTiO3 memristor obtained under positive and negative pulses, respectively[29]

    图 9  忆阻器的非线性传输特性 (a), (b) 器件电流-电压特性曲线; (c) 在连续的增强/抑制脉冲下, 器件电导上升/下降[27]

    Fig. 9.  The nonlinear transmission characteristic of memtistor. (a), (b) I-V characteristic of the device measurement under positive and negative voltage sweep, respectively. (c) the continuously increase/decrease of device conductance under positive/negative pulse[27]

    图 10  (a) 在忆阻器中实现的PPF现象: PPF变化量和时间间隔的关系[31]; (b) 浦肯野细胞(Purkinje cell)和颗粒细胞(granule cell)之间神经突触的双脉冲易化行为; 插图为连续两个胞外刺激引起的兴奋性后电流变化[35]

    Fig. 10.  (a) PPF behaviors obtained in memristor: the change of PPF as the function of the time interval.[31] (b) the PPF measured in the synapse between Purkinje cell and granule cell. The insert is the EPSC induced by two extracellular stimuli[35]

    图 11  (a) 基于忆阻器模拟放电时间依赖可塑性(相对突触权重和相对刺激时间的依赖性)[27]; (b) 老鼠海马体神经元中相对刺激时间的依赖性[41]

    Fig. 11.  (a) STDP behaviors obtained by the memristor.[27] (b) STDP behaviors measured in hippocampal neurons of the rats[41]

    图 12  (a) 短时记忆向长时记忆转变示意图; (b) 艾宾浩斯遗忘曲线

    Fig. 12.  (a) Schematic diagram of the transition from short-term memory (STM) to long-term memory (LTM). (b) the Ebbinghaus Forgetting Curve.

    图 13  Lu研究组模拟短时可塑性向长时可塑性的转变 (a, b) 施加的脉冲信号和器件的响应电流; (c) 不同数量刺激后, 记忆的保持量; (d) 弛豫过程的初始电流及拟合时间参数随刺激次数的变化; (e) 长短时转变过程中, 器件内部结构变化示意图[19]

    Fig. 13.  STM-to-LTM transition obtained by Lu’s group. (a, b) the response current of the device under pulse stimulus. (c) memory retention data recorded after different numbers of identical stimuli (dots) and fitted curves using the SEF (solid lines). (d) characteristic relaxation time (τ) plotted with respect to the number of stimulations (N). (e) schematic of the structural change to the memristor during the transition[19]

    图 14  突触仿生器件的 “经验式行为”和器件运行动力学模型 (a) 突触权重随脉冲刺激近线性增加; (b) 电导自发弛豫过程; (c) 基于中间态的再次学习过程; 插图为器件运行的氧离子迁移扩散机制[27]

    Fig. 14.  The “learning-experience” behaviors, and the dynamic model of device operation. (a) Nearly linear increase of the synaptic weight with consecutive stimuli. (b) the spontaneous decay of the conductivity. (c) re-stimulation process from the mid-state. The inset illustrates an oxygen ion migration/diffusion model of device operation[27]

    图 15  (a) 生物系统中的习惯化和去习惯化行为; (b) 基于HfOx忆阻器实现的习惯化和去习惯化行为[54]

    Fig. 15.  (a) Habituation and dishabituation behaviors in biological systems. (b) schematic of stimulus trains used for the measurement of habituation/dishabituation and the measured device current changes under the application of stimulus trains[54]

    图 16  (a) 巴普洛夫条件反射的原型; (b) 基于忆阻器构建的巴普洛夫条件反射模拟电路; (c) 在不同时序关系的条件和非条件刺激下实验测量结果[58]

    Fig. 16.  (a) Prototype of the Pavlovian conditioning. (b) memristive circuit with electrical US and CS to mimic the Pavlovian conditioning. (c) the experimental results under the conditions of different intervals between conditioned and unconditioned stimulus[58]

    图 17  (a) 分别基于数字型和模拟型行为的图像演变过程; (b) 由数字型和模拟型忆阻器构成的混合人工神经网络; (c) 人工神经网络中数字型比例对图像识别准确性的影响[63]

    Fig. 17.  (a) Evolution of images during the learning process for the initial, intermediate, and final states based on Digital resistive switching (D-RS) and analog resistive switching (A-RS) behaviors, respectively. (b) hybrid ANN composed of A-RS memristors and D-RS memristors. (c) accuracy as a function of number of epochs for the hybrid ANN at four different A-RS proportions[63]

    图 18  基于时空处理的声音定位 (a) 双耳效应示意图; (b) 2 × 2神经网络通过双耳时差进行声音定位; (c) 实验用到的左右耳声音波形; (d) 对应突触前神经元的轴突电位; (e) 不同时差信号引起的突触后神经元电位; (f) 不同声音方位下突触后神经元电位的测量和计算结果[67]

    Fig. 18.  Sound localization based on space-time processing. (a) Schematic illustration of binaural effect. (b) schematic structure of a 2 × 2 SNN to detect the sound direction from the ITD. (c) experimental sound waveforms of left and right ears, (d) corresponding axon potential of the two PREs, and (e) vint for the two POSTs with their corresponding difference. (f) measured and calculated Vint as a function of sound azimuth revealing analog information about the sound propagation direction[67]

    图 19  (a) 实现逻辑电路的交叉阵列; (b) IMP逻辑运算电路; (c) NAND逻辑运算电路[8]

    Fig. 19.  (a) The memristors crossbar for logical circuit. (b) IMP logical circuit. (c) NAND logical circuit[8]

    图 20  (a) 利用水溶方法制备可转移的Pt/WOx/Ti忆阻神经突触器件示意图; (b) 转移至打印纸、3D玻璃半球、果胶和PDMS衬底上的器件实物图; (c) 转移至不同衬底上的忆阻器件STDP学习功能[73]

    Fig. 20.  (a) Schematic diagrams of the fabrication process for the transferable Pt/WOx/Ti synaptic devices using water-dissolution method. (b) the pictures of devices that are transferred on flexible printing paper, glass dome hemisphere with 3D surface, pectin and PDMS substrate. (c) the obtained STDP behaviors of the devices on different substrates[73]

    图 21  (a) 光激励下ITO/Nb:SrTiO3基光电神经突触器件运行机理示意图; (b) 在光脉冲对下异质结的典型光响应特性; (c) 对脉冲易化度随脉冲间隔变化规律[77]

    Fig. 21.  (a) Photoresponsive characteristics of the ITO/Nb:SrTiO3 heterojunction artificial optoelectronic synapse under pulsed light stimuli. (b) photoresponsive characteristic of the heterojunction under a light pulse pair. (c) the variation of PPF index with the interval of light pulse pairs[77]

    图 22  基于ITO/Nb:SrTiO3异质结人工光电神经突触模拟视觉神经系统 (a) 用波长编码输入图像的感知和记忆过程. (b) 用强度编码输入图像的感知和记忆过程. (c) 低频率刺激下的图像感知和记忆过程[77]

    Fig. 22.  Mimicry of human visual memory using the ITO/Nb:SrTiO3 heterojunction artificial optoelectronic synapse. (a) The detection and memory process of image encoded by light wavelength. (b) the detection and memory process of image encoded by light intensity. (c) the detection and memory process of image with low stimulating frequency.

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出版历程
  • 收稿日期:  2019-08-15
  • 修回日期:  2019-08-19
  • 上网日期:  2019-08-19
  • 刊出日期:  2019-08-20

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