在近二维矿记忆器中利用双电阻切换来实现集成非挥发性记忆,突触模拟和储计算
Zhenwang Luo1, Weisheng Wang1, Junhui Wu1
1Department of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, Ningbo 315211, China.
ACS applied materials & interfaces
|March 19, 2025
概括
准二维矿记忆器表现出挥发性和非挥发性电阻切换,使先进的神经形态计算成为可能. 这些memristor显示出人工神经网络和储库计算应用的前景.
科学领域:
- 材料科学 材料科学 材料科学
- 计算机工程 计算机工程
- 神经科学是一个神经科学.
背景情况:
- 人工智能 (AI) 的计算需求挑战了传统的计算.
- 具有多种电阻开关 (RS) 的memristors提供了新的计算架构.
- 需要为下一代计算提供先进的材料.
研究的目的:
- 调查二维矿记忆体 (Q-2DPM) 中挥发性和非挥发性RS的共存情况.
- 评估Q-2DPM对非挥发性记忆和突触功能的性能.
- 证明Q-2DPM适用于神经形态和储库计算的适用性.
主要方法:
- 准二维矿记忆器的制造和表征.
- 模拟突触功能 (ePSC,PPF,LTP/LTD) 进行模拟.
- 在人工神经网络中实现MNIST分类和储计算实验.
主要成果:
- 在Q-2DPM中实现了挥发性和非挥发性RS行为的共存.
- Q-2DPM展示了具有竞争力的非易失性记忆性能.
- 成功模拟多个突触功能,并在MNIST分类中具有高准确性.
- 通过数字分类证明了Q-2DPM适用于储计算的适用性.
结论:
- 在Q-2DPM中阐明双 RS 机制提供了新的见解.
- 单个Q-2DPM设备可以实现多种不同的计算单元.
- 为物理神经形态硬件和先进的计算原体铺平了道路.
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