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通过介孔二氧化硅扩散忆阻器中的孔隙率控制实现可调谐神经形态开关动力学

Tunable Neuromorphic Switching Dynamics via Porosity Control in Mesoporous Silica Diffusive Memristors.

作者信息

Zhang Tongjun, Shao Li, Jaafar Ayoub, Zeimpekis Ioannis, de Groot Cornelis H, Bartlett Philip N, Hector Andrew L, Huang Ruomeng

机构信息

School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, United Kingdom.

School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom.

出版信息

ACS Appl Mater Interfaces. 2024 Apr 3;16(13):16641-16652. doi: 10.1021/acsami.3c19020. Epub 2024 Mar 17.

Abstract

In response to the growing need for efficient processing of temporal information, neuromorphic computing systems are placing increased emphasis on the switching dynamics of memristors. While the switching dynamics can be regulated by the properties of input signals, the ability of controlling it via electrolyte properties of a memristor is essential to further enrich the switching states and improve data processing capability. This study presents the synthesis of mesoporous silica (mSiO) films using a sol-gel process, which enables the creation of films with controllable porosities. These films can serve as electrolyte layers in the diffusive memristors and lead to tunable neuromorphic switching dynamics. The mSiO memristors demonstrate short-term plasticity, which is essential for temporal signal processing. As porosity increases, discernible changes in operating currents, facilitation ratios, and relaxation times are observed. The underlying mechanism of such systematic control was investigated and attributed to the modulation of hydrogen-bonded networks within the porous structure of the silica layer, which significantly influences both anodic oxidation and ion migration processes during switching events. The result of this work presents mesoporous silica as a unique platform for precise control of neuromorphic switching dynamics in diffusive memristors.

摘要

为了满足对时间信息进行高效处理的日益增长的需求,神经形态计算系统越来越重视忆阻器的开关动力学。虽然开关动力学可以由输入信号的特性来调节,但通过忆阻器的电解质特性来控制它的能力对于进一步丰富开关状态和提高数据处理能力至关重要。本研究展示了使用溶胶-凝胶工艺合成介孔二氧化硅(mSiO)薄膜,这使得能够制备具有可控孔隙率的薄膜。这些薄膜可以用作扩散型忆阻器中的电解质层,并导致可调谐的神经形态开关动力学。mSiO忆阻器表现出短期可塑性,这对于时间信号处理至关重要。随着孔隙率增加,观察到工作电流、易化率和弛豫时间有明显变化。研究了这种系统控制的潜在机制,并将其归因于二氧化硅层多孔结构内氢键网络的调制,这在开关事件期间对阳极氧化和离子迁移过程都有显著影响。这项工作的结果表明介孔二氧化硅是精确控制扩散型忆阻器中神经形态开关动力学的独特平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8981/10995907/474b8331ea61/am3c19020_0001.jpg

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