Recent Developments of Optoelectronic Synaptic Devices Based on Metal Halide Perovskites

Massive data processing with high computing efficiency and low operating power is required owing to the rapid development of artificial intelligence and information technology. However, the von Neumann structure computing system with the separated memory and processor can cause large energy consumption and a low running speed during massive data processing. Therefore, the brain-inspired neuromorphic computing system is developed, that can provide hardware support for emulating biological synaptic functions and realizing highly intensive data processing with low power consumption. As a neuromorphic device, the optoelectronic synaptic device (OSD) is regarded as an ideal device to replace the von Neumann-based computer because of its ultrafast signal transmission, large bandwidth, low energy consumption, and wireless communication. Owing to their unique optoelectronic property, metal halide perovskites (MHPs) have received growing attention as effective photosensitive materials in OSDs. Therefore, the review introduces the recent progress on OSDs based on MHPs (MHPs-OSDs) including the structures and properties of MHPs, and the architectures and performance characteristics of MHPs-OSDs. Furthermore, applications of MHPs-OSDs are presented. Finally, the outlook and opportunity of MHPs-OSDs are discussed.     

硫系非晶态半导体人工神经突触的可塑性

模拟大脑中的神经突触是实现下一代计算机——类脑神经形态计算的关键一步。为了利用光子模拟神经突触的可塑性进而发展全光人工神经突触器件,文章开展了基于可控光诱导抑制效应的硫系非晶态半导体人工神经突触的实验研究。分析了材料化学组分和抽运光功率对该人工神经突触的调控作用,描述了该人工神经突触的可塑性。结果表明掺入不同杂质的硫系非晶态半导体平面波导具有不同的可控光诱导抑制过程,且抑制深度受控于抽运光功率的变化。基于这些特性,该人工神经突触展现出了配对脉冲易化功能、短程抑制功能、长程抑制功能,具有良好的可塑性。     

自动交换光网络中光电子器件的进展

光网络正在向高速大容量、良好的扩展性和智能化的方向发展。自动交换光网络的出现是光传送网技术的重要突破,光电子器件功能的增强与性能的提高将对其实现与发展起决定性作用。本文介绍了自动交换光网络中一些光电子器件的重要特性和发展趋势。     

基于突触可塑性的SNN随钻陀螺仪漂移处理

针对随钻振动引起MEMS陀螺仪的数据漂移问题,文中提出了一种脉冲神经网络算法.首先根据陀螺仪漂移误差的时间特性,利用脉冲网络的脉冲时间编码陀螺仪的信息强度.然后利用Izhikevich神经元模型的突触可塑性,调节激发性突触电导并抑制性突触电导,增强网络的鲁棒性,从而提高陀螺仪信号对噪声的抗干扰能力.在不同振动频率下,分...     

基于低频电噪声的光电耦合器可靠性筛选方法研究

低频电噪声是表征电子器件质量和可靠性的敏感参数,通过测试低频噪声,可以快速、无损地实现光耦器件的可靠性评估。通过开展可靠性老化对光电耦合器低频噪声特性影响的试验研究,提出基于低频段宽频带噪声参数的光电耦合器可靠性筛选方法,并将可靠性筛选结果与点频噪声筛选方法结果进行对比分析。结果表明,与点频噪声参数等现有方法相比,宽频带噪声参数可以更灵敏和准确地表征器件可靠性,同时计算简便,基于宽频带噪声参数的光电耦合器可靠性筛选方法可以实现更为准确合理的可靠性分类筛选。     

An Array of Light-Stimulated Two-Terminal Synaptic Devices with the Modulation of Electric Polarity

Neuromorphic visual systems based on optoelectronic synaptic devices have been recently studied to simulate the retina and visual cortex of a human being. Now it is shown that an array of optoelectronic synaptic devices based on the two-terminal structure of Si/perovskite/Au may mimic the functionalities of lateral geniculate nucleus (LGN) cells. Benefiting from the photovoltaic effect, the devices can work under a self-powered mode. Diverse synaptic functionalities such as postsynaptic current, paired-pulse facilitation/depression, spike duration-dependent plasticity, spike number-dependent plasticity, and spike rate-dependent plasticity have been simulated. By modulating the electric bias of the devices in the array the simulation of the positional and orientational recognition of the LGN cells is demonstrated.     

2D Material Based Synaptic Devices for Neuromorphic Computing

The demand for computing power has been increasing exponentially since the emergence of artificial intelligence (AI), internet of things (IoT), and machine learning (ML), where novel computing primitives are required. Brain inspired neuromorphic computing systems, capable of combining analog computing and data storage at the device level, have drawn great attention recently. In addition, the basic electronic devices mimicking the biological synapse have achieved significant progress. Owing to their atomic thickness and reduced screening effect, the physical properties of 2D materials could be easily modulated by various stimuli, which is quite beneficial for synaptic applications. In this article, aiming at high-performance and functional neuromorphic computing applications, a comprehensive review of synaptic devices based on 2D materials is provided, including the advantages of 2D materials and heterostructures, various robust multifunctional 2D synaptic devices, and associated neuromorphic applications. Challenges and strategies for the future development of 2D synaptic devices are also discussed. This review will provide an insight into the design and preparation of 2D synaptic devices and their applications in neuromorphic computing.     

Electrospun Nanofiber-Based Synaptic Transistor with Tunable Plasticity for Neuromorphic Computing

Biological synapses are the operational connection of the neurons for signal transmission in neuromorphic networks and hardware implementation combined with electrospun 1D nanofibers have realized its functionality for complicated computing tasks in basic three-terminal field-effect transistors with gate-controlled channel conductance. However, it still lacks the fundamental understanding that how the technological parameters influence the signal intensity of the information processing in the neural systems for the nanofiber-based synaptic transistors. Here, by tuning the electrospinning parameters and introducing the channel surface doping, an electrospun ZnO nanofiber-based transistor with tunable plasticity is presented to emulate the changing synaptic functions. The underlying mechanism of influence of carrier concentration and mobility on the device's electrical and synaptic performance is revealed as well. Short-term plasticity behaviors including paired-pulse facilitation, spike duration-dependent plasticity, and dynamic filtering are tuned in this fiber-based device. Furthermore, Perovskite-doped devices with ultralow energy consumption down to ≈0.2554 fJ and their handwritten recognition application show the great potential of synaptic transistors based on a 1D nanostructure active layer for building next-generation neuromorphic networks.     

光电器件薄膜附着力评价方法的研究进展

薄膜与衬底的结合性能一直备受关注.在各种情况下,薄膜的性能都依赖于其与衬底的附着力大小.为了提高附着强度,需要深刻理解附着力的机理和开发合适的附着力测试技术.从基准附着力、热力学附着能和实际附着力三个不同角度提供了附着力评价途径.作为广泛使用的附着力粘接测试技术,拉脱法和压带剥落法等方法在大量样品测试方面具有独特优势,...     

Redox MXene Artificial Synapse with Bidirectional Plasticity and Hypersensitive Responsibility

Artificial synapses are key elements for the nervous system which is an emulation of sensory and motor neuron signal transmission. Here, the design and fabrication of redox-behavior the metal carbide nanosheets, termed MXene artificial synapse, which uses a highly-conductive MXene electrode, are reported. Benefiting from the special working mechanism of ion migration with adsorption and insertion, the device achieves world-record power consumption (460 fW) of two-terminal synaptic devices, and so far, the bidirectionally functioned synaptic device could effectively respond to ultra-small stimuli at an amplitude of ±80 mV, even exceeding that of a biological synapse. Potential applications have also been demonstrated, such as dendritic integration and memory enhancement. The special strategy and superior electrical characteristics of the bidirectionally functioned electronic device pave the way to high-power-efficiency brain-inspired electronics and artificial peripheral systems.     

Advanced Optoelectronic Devices for Neuromorphic Analog Based on Low-Dimensional Semiconductors

Neuromorphic systems can parallelize the perception and computation of information, making it possible to break through the von Neumann bottleneck. Neuromorphic engineering has been developed over a long period of time based on Hebbian learning rules. The optoelectronic neuromorphic analog device combines the advantages of electricity and optics, and can simulate the biological visual system, which has a very strong development potential. Low-dimensional materials play a very important role in the field of optoelectronic neuromorphic devices due to their flexible bandgap tuning mechanism and strong light-matter coupling efficiency. This review introduces the basic synaptic plasticity of neuromorphic devices. According to the different number of terminals, two-terminal neuromorphic memristors, three-terminal neuromorphic transistors and artificial visual system are introduced from the aspects of the action mechanism and device structure. Finally, the development prospect of optoelectronic neuromorphic analog devices based on low-dimensional materials is prospected.     

测量噪声功率谱作为筛选光电耦合器件的方法研究（Ⅱ）

在文献「１」中作者曾提出用测量光电耦合器件噪声功能率谱的方法,筛选光电耦合器件。此 根据低频噪声的幅值。但在实验中发现,由于１／ｆ、ｇ－ｒ和爆裂噪声三者之间相关性较弱,在剔除掉１／ｆ噪声值较大的器件后,ｇ－ｒ噪声和爆裂噪声较大的器件却可能未被易除。     

Optoelectronic Synapses and Photodetectors Based on Organic Semiconductor/Halide Perovskite Heterojunctions: Materials,Devices, and Applications

Both photodetectors (PDs) and optoelectronic synaptic devices (OSDs) are optoelectronic devices converting light signals into electrical responses. Optoelectronic devices based on organic semiconductors and halide perovskites have aroused tremendous research interest owing to their exceptional optical/electrical characteristics and low-cost processability. The heterojunction formed between organic semiconductors and halide perovskites can modify the exciton dissociation/recombination efficiency and modulate the charge-trapping effect. Consequently, organic semiconductor/halide perovskite heterojunctions can endow PDs and OSDs with high photo responsivity and the ability to simulate synaptic functions respectively, making them appropriate for the development of energy-efficient artificial visual systems with sensory and recognition functions. This article summarizes the recent advances in this research field. The physical/chemical properties and preparation methods of organic semiconductor/halide perovskite heterojunctions are briefly introduced. Then the development of PDs and OSDs based on organic semiconductor/halide perovskite heterojunctions, as well as their innovative applications, are systematically presented. Finally, some prospective challenges and probable strategies for the future development of optoelectronic devices based on organic semiconductor/halide perovskite heterojunctions are discussed.     

碳纳米管光电器件光学特性的电磁模型研究

针对基于碳纳米管阵列构成的光电器件,建立基于场效应器件结构的电磁散射模型,对其光电吸收特性进行了仿真分析。模型仿真结果表明,当碳纳米管阵列间距为入射光波长的整数倍时,碳纳米管的吸收功率达到峰值,当在两个波长之间,吸收功率按线性衰减,对应于入射光的不同倍数波长的吸收功率的峰值随波长的增加而线性衰减。在吸收功率峰值附近,吸收功率随阵列周期间距的变化而敏感。     

光电耦合器件低频噪声特性与可靠性老化研究

在宽的输入偏置电流范围条件下,开展了光电耦合器件低频噪声特性测试与功率老化和高温老化的可靠性试验研究。结果表明,光电耦合器件的低频噪声主要是内部光敏晶体管1/f噪声,并随输入偏置电流的增大呈现先增大后减小的规律,这与器件的工作状态密切相关。功率老化试验后,高输入偏置电流条件下的低频噪声有所增大,这归因于电应力诱发的有源区缺陷。高温老化试验后,整个器件线性工作区条件下的低频噪声都明显增大,说明温度应力能够更多地激发器件内部的缺陷。相对于1/f噪声幅度参量,低频噪声宽带噪声电压参量可以更灵敏准确地进行器件可靠性表征。     

机载电子设备智能故障诊断技术研究

智能故障诊断在现代飞行器及先进的武器装备及其电子设备的设计、生产和维护过程中都起着关键的作用。介绍了现有电子设备智能故障诊断方法,包括基于规则的方法、故障树方法、模糊诊断方法、基于人工神经网络的方法和信息融合故障诊断方法,阐述各自的特点和局限性,讨论了航空电子设备智能故障诊断发展,提出了集成诊断技术、综合测试与诊断策略、机器学习方法和软件工具的开发等关键技术。     

基于低频噪声检测光耦器件可靠性的频域筛选方法?

针对光耦器件可靠性筛选,提出全频段阈值筛选方法检测光耦器件内部低频噪声。根据光耦器件内部的低频噪声完成光耦器件可靠性的筛选。实验中利用光耦器件测试系统检测200只光耦器件内部的低频噪声,计算这200只光耦器件全频段平均噪声谱,确定筛选的阈值,再根据光耦器件可靠性分类标准,判断被测器件可靠性等级。     

Tailoring Neuroplasticity in a Ferroelectric-Gated Multi-Terminal Synaptic Transistor by Bi-Directional Modulation for Improved Pattern Edge Recognition

The dynamic modulation of the plasticity of artificial neuromorphic devices facilitates a wide range of neuromorphic functions. However, integrating diverse plasticity modulation techniques into a single device presents a challenge due to limitations in the device structure design. Here, a multiterminal artificial synaptic device capable of bi-directional modulation on its plasticity is proposed. Significantly, the conversion of inhibitory and excitatory synaptic plasticity can be achieved not only by modifying the polarity of the presynaptic voltage spike but also by exchanging its input terminal between top and bottom gate while maintaining the same presynaptic stimuli. This unique bi-directional modulation of synaptic plasticity has been attributed to two distinct physical mechanisms: nonvolatile ferroelectric polarization and interface charge trap-induced memory characteristics. Additionally, the effective dynamic modulation of the synaptic behaviors is quantified under different back-gate bias and verified in the constructed neural network perceptron. Further, a visual simulation demonstrates the enhanced clarity and precision of edge recognition through the back-gate modulation in the artificial synapses. This study provides a strategy to fulfill diversified modulation on synaptic plasticity in ferroelectric-gated transistors, thereby prompting efficient and controllable neuromorphic visual systems.