AI 中文总结
本研究报道了基于AgBiS2的无铅忆阻器，具有超低开关电压和高开关比，通过工程调控实现数字与模拟开关模式，并揭示细丝演化机制，为神经形态计算提供可持续器件设计原则。
AI 中文摘要
忆阻器因其能够集成数据存储与处理，已成为神经形态计算架构的关键构建模块。金属卤化物钙钛矿因其混合电子-离子传导和低成本溶液加工性，近期展现出显著前景，但其对有毒铅的依赖和有限的稳定性构成了关键挑战。在此，我们报道了环境友好、低毒性的基于AgBiS2的溶液可加工忆阻器，其展现出约0.08 V的超低SET电压和大于10^4的高开关比。第一性原理计算确定银间隙原子是能量上最有利的本征缺陷，并揭示了银亚晶格内间隙原子和空位的低迁移势垒，促进了AgBiS2晶格中的离子输运。通过界面和厚度工程，电阻开关行为可以从突变数字模式系统地调节到渐变模拟模式。值得注意的是，较厚的开关层通过中间亚稳态促进了稳定导电通路的演化，揭示了可控的细丝演化过程。电化学阻抗谱在低偏压下揭示了显著的负电容（感性）行为，该行为源于电子-离子耦合动力学。与此行为一致，脉冲测量展示了在脉冲序列下电导的渐变调制，模拟了与神经形态计算相关的突触响应。最后，操作后结构分析揭示了由重复细丝形成和断裂驱动的开关层的显著形态演化。将结构动力学与开关变异性联系起来，为实现可靠且耐用的可持续忆阻器提供了重要的设计原则。
英文摘要
Memristors have emerged as key building blocks of neuromorphic computing architectures due to their ability to integrate data storage and processing. While metal halide perovskites have recently shown significant promise owing to their mixed electronic-ionic conduction and low-cost solution processability, their reliance on toxic lead and limited stability presents critical challenges. Here, we report environmentally friendly, low-toxicity AgBiS2-based solution-processable memristors exhibiting an ultra-low SET voltage of ~0.08 V and a high ON/OFF ratio of >104. First-principles calculations identify Ag interstitials as the energetically most favourable native defect and reveal low migration barriers within the Ag sublattice, for both interstitials and vacancies, facilitating ionic transport in the AgBiS2 lattice. Through interface and thickness engineering, the resistive switching behaviour can be systematically tuned from abrupt digital to gradual analog modes. Notably, thicker switching layers promote the evolution of stable conductive pathways through intermediate metastable states, revealing a controllable filament evolution process. Electrochemical impedance spectroscopy reveals pronounced negative capacitance (inductive) behaviour at low bias voltages, arising from coupled electronic-ionic dynamics. Consistent with this behaviour, pulse measurements demonstrate gradual conductance modulation under pulse trains, emulating synaptic responses relevant for neuromorphic computing. Finally, post-operando structural analysis reveals substantial morphological evolution of the switching layer driven by repeated filament formation and rupture. Linking structural dynamics to switching variability provides important design principles for achieving reliable and durable sustainable memristors.
