最近在基于氧化的memristors中取得的进展,用于神经形态计算
Sarfraz Ali1, Muhammad Abaid Ullah2, Ali Raza3
1Department of Physics, Riphah International University, Lahore Campus, 13-KM Raiwand Road, Lahore 54000, Pakistan.
Nanomaterials (Basel, Switzerland)
|September 9, 2023
概括
氧化 (CeO2) 由于其在神经形态计算中的稳定性和潜力,对电阻式随机访问记忆 (RRAM) 具有前景. 本综述详细介绍了用于高级突触应用的基于CeO2的memristor.
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:
- 氧化 (CeO2) 具有独特的特性,如多个氧化状态和出色的电阻切换 (RS) 特性.
- 这些特性使得CeO2成为电阻随机访问记忆 (RRAM) 和神经形态计算应用的强有力的候选者.
研究的目的:
- 综合审查基于CeO2的RRAM最近的进展.
- 探索CeO2记忆器的丝状机制,设备结构和神经形态应用.
主要方法:
- 对基于CeO2的memristors现有文献的审查.
- 对单极,双极和值记忆行为进行分析.
- 检查电极工程和设备结构 (单层,双层,合).
主要成果:
- CeO2表现出了显著的RS统一性,循环耐力和数据保留.
- 各种基于CeO2的memristor结构显示出作为突触装置的潜力.
- 神经形态应用,包括基于尖的学习和可塑性,得到了广泛的研究.
结论:
- 基于CeO2的memristors对先进的突触研究和神经形态计算非常有前途.
- 鼓励进一步研究使用高介电常数氧化物记忆器.
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