编程脉冲宽度取决于低功耗突触薄膜晶体管的电荷保留特性
Danyoung Cha1, Jeongseok Pi2, Sungsik Lee3
1The Semiconductor-Specialized University, Pusan National University, Busan, 46241, Republic of Korea. wdwn9277@pusan.ac.kr.
Scientific reports
|November 11, 2025
概括
本研究探讨了用于记忆应用的氧化物薄膜晶体管 (Hf-ZnO TFTs). 研究人员在这些突触器件中发现了编程速度和保留时间之间的权衡.
科学领域:
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
- 神经科学是一个神经科学.
背景情况:
- 薄膜晶体管 (TFT) 对于电子设备至关重要.
- 氧化 (Hf-ZnO) 提供了新的电子应用的潜力.
- 突触晶体管模仿生物突触用于神经形态计算.
研究的目的:
- 为了研究Hf-ZnO TFTs的编程脉冲宽度依赖的突触特征.
- 探索Hf-ZnO TFT用于神经形态应用的记忆能力.
- 分析编程速度和保留时间之间的权衡.
主要方法:
- 使用低温原子层沉积制造Hf-ZnO TFT.
- 监测TFT的静态和脉冲特征.
- 在门氧化物 (Al2O3,HfOx) 中利用陷状态来捕捉/解锁电子.
- 用拉伸指数函数进行数学建模,用于保留分析.
- 使用设备级数据模拟模拟模拟加速器的横杆模拟.
主要成果:
- 减少编程脉冲宽度导致了更慢的编程速度.
- 通过数学建模证实了更长的保留时间.
- 建立了编程速度和保留时间之间的权衡关系.
- 监测了突触功能,如体重更新,保持,偶合脉冲抑制/促进以及体重线性.
- 交叉杆模拟证明了设备的性能,包括分类准确性.
结论:
- 对于神经形态计算,Hf-ZnO TFT 显示出有前途的突触特征.
- 该研究突出了影响内存应用的设备设计的关键权衡.
- 这些发现有助于开发先进的模拟加速器和人工智能硬件.
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