Scanning Tunneling Microscopy Investigation of Synaptic Behavior in AgInS2 Quantum Dots: Effect of Ion Transport in Neuromorphic Applications

神经形态工程学 扫描隧道显微镜 量子点 量子隧道 光电子学 离子 材料科学 纳米技术 物理 人工神经网络 计算机科学 量子力学 人工智能
作者
Atanu Betal,Anupam Chetia,Jayanta Bera,Dibyajyoti Saikia,Ashish Sharma,Arup K. Rath,Satyajit Sahu
出处
期刊:ACS applied nano materials [American Chemical Society]
卷期号:7 (7): 7226-7236 被引量:3
标识
DOI:10.1021/acsanm.3c06272
摘要

Scanning tunneling microscopy (STM) is a powerful technique for investigating the nanoscale properties of functional materials. Additionally, scanning tunneling spectroscopy (STS) facilitates the determination of the local density of states (LDOS) within the material. In this study, we present an exploration of the resistive switching (RS) properties and neuromorphic computing capabilities of individual AgInS2 quantum dots, utilizing STM and STS techniques. By examining the material's bandgap and its temperature dependence, we uncover a nonlinear variation below the Debye temperature and a linear trend at higher temperatures. Moreover, STS measurements demonstrate changes in the conducting states induced by localized pulses, further confirming the unique characteristics of the quantum dots. The experimental devices constructed by using these quantum dots effectively replicate the RS properties observed at the nanoscale. To assess the neuromorphic application of the devices, pulse transient measurements simulating the learning and forgetting processes were conducted. The gradual set and reset processes successfully mimic the information retention and erasure capabilities essential for neuromorphic computing. Notably, the resistive switching mechanism in these devices is attributed to localized ionic transport, which highlights the significant involvement of ionic species in the observed RS behavior. The outcomes of this study contribute to the fundamental understanding of RS properties in single AgInS2 quantum dots and offer valuable insights into their potential applications in neuromorphic computing.
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