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大面积多态 In₂Se₃铁电晶体管阵列用于稳定的非挥发性存储和高精度神经形态计算

Yuhuan Li¹, Xiaodong Zheng², Wen Zhang¹

¹Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.

Small (Weinheim an der Bergstrasse, Germany)

|December 31, 2025

概括

这项研究展示了用于高级内存计算的化 (In2Se3) 薄膜. 这些二维铁电场效应晶体管 (FeFET) 为神经形态应用提供了高性能和潜力.

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
电气工程电气工程

背景情况:

新兴的二维材料对于克服计算机中的·诺伊曼瓶至关重要.
化 (In2Se3) 具有独特的特性,包括室温铁电性和高载体流动性.
化学蒸汽沉积 (CVD) 能够合成用于设备制造的大面积二维材料.

研究的目的:

为了研究印化物 (In2Se3) 薄膜铁电场效应晶体管 (FeFET) 阵列的性能.
评估这些2D FeFETs在内存和神经形态计算应用中的潜力.
为了证明In2Se3 FeFET阵列的稳定性和非挥发性特性.

主要方法:

使用化学蒸汽沉积 (CVD) 制造In2Se3薄膜FeFET阵列.
设备性能的表征,包括场效应移动性 (μFE) 和开关比.
测试FeFET阵列的稳定性和非挥发性内存特征.
在神经形态计算的机器学习任务中应用In2Se3 FeFET阵列.

主要成果:

In2Se3 FeFET 阵列实现了 151.7 cm2 V-1 s-1.1 的高场效移动性 (μFE).
记录了高达106的令人印象深刻的开关比率.
观察到稳定,非挥发性特征,阻力状态窗口>102维持超过1800秒.
在机器学习任务中,识别准确度始终超过90%.

结论:

In2Se3薄膜FeFET阵列是下一代内存计算的有希望的解决方案.
展示的高性能和稳定性突出显示了它们在神经形态计算方面的潜力.
CVD合成促进了用于实际应用的大面积2D FeFET阵列的开发.

关键词:

两维材料是二维材料.铁电机电机电机电机电机电机这是一个神经形态神经形态的神经形态.它们是多态多态的.晶体管是一个晶体管.

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