接口工程Gd2O3/ZrO2双层记忆器,用于模拟神经形态系统中的突触可塑性.
Hammad Ghazanfar1, Muhammad Rabeel2, Sobia Nisar2
1Department of Semiconductor Systems Engineering, Sejong University, Seoul 05006, Republic of Korea; Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea.
Journal of colloid and interface science
|January 24, 2026
概括
稀土氧化物记忆器显示出大脑启发的计算的前景. 一种新的双层设备实现了高性能和准确识别模式,为节能神经突触系统铺平了道路.
科学领域:
- 材料科学 材料科学 材料科学
- 神经技术的神经技术
- 设备物理 设备物理
背景情况:
- 稀土材料对于开发节能神经形态设备至关重要.
- 记忆式切换行为对于大脑启发的计算是必不可少的.
研究的目的:
- 为了演示具有强大的电阻切换和突触功能的双层记忆器.
- 探索稀土氧化物在神经形态应用中的潜力.
主要方法:
- 制造一个双层Ag/Gd2O3/ZrO2/Pt记忆器.
- 电阻切换行为,耐久性和数据保留的表征.
- 使用多层感知子网络模拟生物突触功能和模式识别.
主要成果:
- 记忆器表现出低工作电压 (<0.5V),高的开启/关闭比率 (∼108),以及出色的耐用性 (>5000循环).
- 该设备成功模拟了突触可塑性,并在MNIST数据集上实现了97.5%的准确性.
- 已证明长期保留数据 (>5000秒).
结论:
- 双叶氧化物架构为可扩展,节能的神经突触系统提供了一个有前途的途径.
- 基于稀土的memristors适合在硬件层面实现人工智能.
- 开发的memristor显示了高级计算应用的潜力.
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