质子辅助氧化基三终端memristor用于交感设备应用程序
Lingli Liu1, Putu Andhita Dananjaya1, Mun Yin Chee1
1School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore.
ACS applied materials & interfaces
|June 12, 2023
概括
这项研究介绍了一种用于神经形态计算的新型三终端记忆器 (3TM). 该设备具有线性重量更新和高耐久性,在手写数字识别中达到92%的准确性,非常适合人工神经网络.
科学领域:
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
- 计算机科学 计算机科学
背景情况:
- 神经形态计算系统利用新兴技术,如自旋电子,二维材料和记忆设备.
- 双终端的memristors在并发信号传输和内存操作方面面临着挑战.
研究的目的:
- 为了呈现一个互补的金属氧化物半导体兼容的三终端记忆器 (3TM).
- 证明其作为人工神经网络 (NN) 的突触装置的适用性.
主要方法:
- 制造3TM,兼容补充金属氧化物半导体技术.
- 研究涉及氧离子和质子迁移的切换机制.
- 对突触运作,耐力和动态范围的评估.
- 将3TM模拟并实现为MNIST识别的四层NN模型.
主要成果:
- 3TM显示了高度线性的重量更新特性和大约15的动态范围.
- 取得了优异的耐力表现,超过256,000个突触重量更新.
- 该设备在整个耐力测试中表现出稳定的动态范围.
- 结合3TM的NN模型在MNIST手写数字识别中实现了约92%的准确性.
结论:
- 拟议的3TM,具有其理想的导电量调制特性,是人工NN的硬件实现的有希望的候选者.
- 该设备的性能,包括线性,动态范围和耐力,支持其在神经形态计算中的应用.
- 受质子缺陷和湿度影响的开关机制为未来设备优化提供了洞察力.
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