在用于神经形态计算的基于氧化物的memristors中可光学调节的电动振荡
Shimul Kanti Nath1,2,3, Sujan Kumar Das2,4, Sanjoy Kumar Nandi2
1Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia.
Advanced materials (Deerfield Beach, Fla.)
|March 22, 2024
概括
这项研究证明了基于二氧化瓦纳 (V3O5) 的神经元对硬件神经网络的光学控制. 该V3O5材料显示了独特的光导和玻利米特征,使得高效的传感器内计算成为可能.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
背景情况:
- 基于硬件的神经网络需要高效的传感输入集成.
- 挥发性值切换材料为神经形态计算提供了潜力.
研究的目的:
- 用V3O5来研究振荡神经元的直接光学控制.
- 探索V3O5设备中光学调整的基本机制.
- 为了展示这些设备在神经形态计算中的应用.
主要方法:
- 基于V3O5的振荡神经元设备的制造和表征.
- 温度依赖的电测量,导电原子力显微镜 (C-AFM) 和现场热成像.
- 块元素建模以了解设备物理.
- 在传感器储存器计算和用于尖端神经网络 (SNN) 的光学编码的演示.
主要成果:
- 实现了V3O5振荡神经元的直接光学控制.
- 无电成型的操作,具有可光调的开关参数.
- V3O5表现出显著的光导和玻利米特征,增加导电性.
- 确定了V3O5作为一种新型的博洛米特材料,在423K时具有高TCR的-4.6%K-1.
- 成功演示了传感器内储计算和光学SNN编码.
结论:
- V3O5是光学控制的神经形态硬件的一个有希望的材料.
- 光导和波力学效应的相互作用决定了设备的行为和振荡动态.
- 这些设备为节能和紧的传感器内计算架构提供了一条途径.
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