MoO 具有可编程多层导电的突触记忆器,用于可靠的神经形态硬件
Xiaofei Dong1, Hao Sun1, Xinhua Lai1
1Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
The journal of physical chemistry letters
|March 27, 2024
概括
研究人员开发了用于神经形态计算的新型氧化物 (MoO) 记忆器. 这些设备展示了超快的交换和突触行为,使得超越传统架构的高效内存计算成为可能.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术纳米技术
- 计算机工程 计算机工程
背景情况:
- 记忆器对于下一代神经形态计算至关重要.
- 控制界面特征是突触行为复制的关键,但经常被忽视.
研究的目的:
- 通过直接的Mo电极氧化来设计MoO记忆电阻.
- 调查它们对先进计算应用的潜力.
主要方法:
- 通过在空气中氧化Mo电极来制造MoO记忆器.
- 电气开关特性,耐用性和功耗的表征.
- 在交叉条数组中实现图像处理任务.
主要成果:
- 实现非挥发性,超快速切换 (<1mV/十年) 具有高开/关比 (>104).
- 证明了长时间的耐用性 (>104s),低功耗 (17.9μW) 和出色的均性.
- 展示了突触行为和可编程的多层次模拟切换.
- 在使用memristor数组的随机图像上成功实现了边缘检测.
结论:
- 开发的MoO记忆器显示出对高效内存计算的重大承诺.
- 基于氧气空隙的导电丝是电阻切换的可能机制.
- 这些设备为神经系统硬件实现了巨大的并行性,超越了·诺伊曼架构的局限性.
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