对于神经形态计算的相关氧化物中质子合的莫特过渡的空间演变
Xing Deng1, Yu-Xiang Liu1, Zhen-Zhong Yang1
1Key Laboratory of Polar Materials and Devices (Ministry of Education), Shanghai Center of Brain-Inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai 200241, China.
Science advances
|May 31, 2024
概括
研究人员将质子引入甲 (SmNiO3) 装置,使可逆Mott转换和巨大的电阻变化成为可能. 这一突破为低功耗记忆设备和人工神经网络提供了新的途径.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 设备工程 设备工程
背景情况:
- 在相关氧化物中的质子电子合提供了通往新型电子状态和设备功能的途径.
- 尼基酸盐 (SmNiO3) 是一种相关的氧化物,具有有趣的电子特性.
研究的目的:
- 研究质子兴奋剂对SmNiO3.3电子和结构性质的影响.
- 探索以质子控制的SmNiO3对记忆器件和人工神经网络的潜力.
主要方法:
- 在室温下Pt辅助的溢出将质子引入SmNiO3.
- 在现场进行结构性表征和第一原则计算.
- 电脉冲用于空间控制质子度.
主要成果:
- 由质子迁移和再分配引起的可逆局部Mott过渡.
- 在超低电场下,巨大的电阻变化导致了优秀的记忆行为.
- 实现层次树状记忆状态的实现,模仿生物突触.
结论:
- 质子工程提供了一种有效的方法来控制相关氧化物的功能.
- 开发的基于SmNiO3的设备显示出低功耗智能设备和神经网络电路的前景.
- 这项研究为设计下一代电子设备提供了替代途径.
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