基于pn结空间电荷区宽度调制的忆阻器：材料、忆阻行为调控与神经突触仿生研究

Memristor is considered as the fourth fundamental circuit element besides resistor, capacitor, and inductor, which has great potential applications in many areas, such as non-linear electric circuit, high-density memory, logical operation circuit, and artificial intelligence. However, the research on memristors is still at the preliminary stage presently, and the development is limited by the small number of available models for building memristors. This project aims at developing a new type of memristor based on the modulation of the space-charge region width in a p-n junction, and researching its application in synapse emulation. For this novel memristor, the performance of device can be tuned flexibly, because the properties of p-n junction can be easily adjusted. Metal oxides will be used as resistive switching materials, and their growth behaviors will be investigated. We plan to manufacture a series of memristors based on p-n heterojunctions with different carrier density; to study some factors affecting the memristive behavior, including material selection, device structure, microstructure and electrical properties of films; to study the capacitive memory effects present in the current memristor; to reveal the physical mechanism underlying the variation of the number of charged centers in p-n junction region and build the memristor model. The memristor will also be used to emulate several essential synaptic functions associated with learning and memory. The response of synaptic weight (resistance) to the spiking signal, including its amplitude, duration time, frequency, and temporal sequence, will be investigated. This project can provide an alternative model for building memristors with adjustable properties, which is cutting-edge research in the interdisciplinary field of materials science, physics and electronics.

忆阻器被认为是除电阻、电容、电感外的第四种电路基本元件，在非线性电路、新型存储、逻辑运算和人工智能等领域极具应用潜力。但其研究尚处起步阶段，构筑忆阻器的物理模型较为有限。本课题旨在发展一种基于pn结空间电荷区宽度调制的新型忆阻器，并用于神经突触的仿生；利用pn结物性易于调制的特点实现忆阻性能的调控。以金属氧化物为阻变材料，研究其生长规律，制备由载流子浓度不同的氧化物薄膜组成的pn异质结；研究材料选择、薄膜微结构和电学性质、器件结构对忆阻行为的影响；研究内建电场对电阻记忆及弛豫过程的调制作用；研究器件兼具的电容记忆行为；揭示pn结区内带电中心数量变化的机制，建立器件物理模型。利用忆阻器模拟生物神经突触与学习/记忆相关的多种基本功能。研究突触权重（电阻）对刺激信号幅度、时间、频率、时域顺序等因素的响应。本研究为构筑性能可调控的忆阻器件提供了备选方案，是材料、物理、电子交叉领域中的前沿方向。

忆阻器作为除电阻、电容、电感外的第四种电路基本元件，在非线性电路、新型信息存储、逻辑运算和人工智能等领域极具应用潜力。本课题围绕氧化钽、氧化石墨等氧化物构筑忆阻器件，从忆阻材料设计、忆阻机理探究、忆阻可靠性的提升以及忆阻器突触仿生功能/信息存储等方面开展了系列研究工作。取得主要结果如下: 通过氧浓度及氧迁移过程调节，揭示了p型氧化物阻变机理，优化了氧化物忆阻性能;揭示了导电通道不稳定原因，研究了导电通道自发弛豫动力学行为，发现了自发电导量子化效应;发展了多孔复合结构、尖端电极、粒子包埋、元素掺杂等方法,促进了忆阻器导电细丝局域化，有效提升了忆阻器件可靠性；开发了具有超低功耗氧化钽忆阻器件，单位功耗低至与人脑神经突触相当，有效解决了忆阻器功耗与保持矛盾; 发展了具有柔性、可转移特性的多功能忆阻器件。首次报道了氧化石墨烯互补型忆阻器，有效解决了串扰问题，为器件进一步集成应用奠定了基础。本项目对构筑高可靠性忆阻器件及其神经突触仿生/信息存储方面提供了科学依据和技术基础。相关结果发表在 Small, Nanoscale, Carbon, Appl. Phys. Lett., IEEE EDL 等杂志报道，发表SCI论文38篇, 申请发明专利9项，授权pn结忆阻器相关专利2项。在国内外学术会议上作报告10余次。申请人获得国家基金委优秀青年基金，获得国家自然科学二等奖（第三完成人）。