神经形态工程学
材料科学
纳米技术
仿真
纳米尺度
记忆电阻器
长时程增强
计算机科学
电子工程
人工神经网络
化学
人工智能
工程类
经济
经济增长
生物化学
受体
作者
Dilruba Hasina,Mahesh Saini,Mohit Kumar,Aparajita Mandal,Nilanjan Basu,Paramita Maiti,Sanjeev Kumar Srivastava,T. Som
出处
期刊:Small
[Wiley]
日期:2023-10-06
卷期号:20 (7)
被引量:2
标识
DOI:10.1002/smll.202305605
摘要
Neuromorphic computing is a potential approach for imitating massive parallel processing capabilities of a bio-synapse. To date, memristors have emerged as the most appropriate device for designing artificial synapses for this purpose due to their excellent analog switching capacities with high endurance and retention. However, to build an operational neuromorphic platform capable of processing high-density information, memristive synapses with nanoscale footprint are important, albeit with device size scaled down, retaining analog plasticity and low power requirement often become a challenge. This paper demonstrates site-selective self-assembly of Au nanoparticles on a patterned TiOx layer formed as a result of ion-induced self-organization, resulting in site-specific resistive switching and emulation of bio-synaptic behavior (e.g., potentiation, depression, spike rate-dependent and spike timing-dependent plasticity, paired pulse facilitation, and post tetanic potentiation) at nanoscale. The use of local probe-based methods enables nanoscale probing on the anisotropic films. With the help of various microscopic and spectroscopic analytical tools, the observed results are attributed to defect migration and self-assembly of implanted Au atoms on self-organized TiOx surfaces. By leveraging the site-selective evolution of gold-nanostructures, the functionalized TiOx surface holds significant potential in a multitude of fields for developing cutting-edge neuromorphic computing platforms and Au-based biosensors with high-density integration.
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