基于化膜的无转移模拟和数字灵活记忆器
Sibo Wang1, Xiuhuan Liu2, Han Yu1
1State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, China.
Nanomaterials (Basel, Switzerland)
|February 23, 2024
概括
灵活的六角化记忆器可以实现高效的神经形态和记忆计算. 这些设备克服了传统计算机的局限性,为模拟应用提供突触行为,为灵活的电子产品提供可靠的数字切换.
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
- 纳米技术纳米技术
背景情况:
- 传统的·诺伊曼建筑面临着像记忆墙这样的局限性.
- 神经形态和内存计算为提高计算效率提供了解决方案.
- 六角化 (hBN) 是先进电子设备的一个有前途的材料.
研究的目的:
- 提出和开发基于六角化薄膜的无转移柔性记忆器.
- 调查它们对模拟神经形态和数字记忆计算应用的潜力.
- 描述设备性能和电阻开关机制.
主要方法:
- 使用六角化薄膜制造柔性记忆器.
- 模拟记忆器对突触行为 (配对脉冲促进,LTP/LTD) 的表征.
- 使用传输电子显微镜对电阻开关机制的研究.
- 用各种电极材料制造数字记忆器.
- 评估数字记忆器的性能 (开启/关闭比,耐久性,非挥发性,曲稳定性).
主要成果:
- 模拟记忆器展示了神经形态计算所必不可少的关键突触行为.
- 通过TEM分析阐明了电阻切换机制.
- 数字记忆器表现出高的启/关比 (高达10^6) 和可靠的切换耐久性 (>100个周期).
- 设备显示非易失性 (>60分钟) 和在曲条件下 (>100周期) 强大的性能.
结论:
- 无转移的灵活hBN记忆器适用于模拟神经形态和数字记忆计算.
- 这些设备提供了一条克服·诺伊曼架构局限性的途径.
- 开发的memristors显示出对高效,灵活和先进的计算应用有希望.
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