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通过激光处理和ALD被动化进行增强的2D MoTe₂模拟切换,用于双功能神经形态设备

Mohamed Radwan¹, Seyed Hossein Hosseini-Shokouh¹, Abde Mayeen Shafi¹

¹Department of Electronics and Nanoengineering Aalto University, Tietotie 3 FI-02150, Finland.

|December 15, 2025

概括

研究人员为基于神经的计算增强了二维二甲 (MoTe2) 设备. 激光处理和Al2O3沉积显著改善了memristor和memtransistor的性能,提高了模式识别的准确性.

科学领域:

材料科学材料科学材料科学
纳米技术纳米技术
神经工程是神经工程.

背景情况:

记忆器和记忆晶体管是基于神经系统的计算的关键.
两维二化物 (MoTe2) 由于其低相变能量和可调节的电气特性而具有前景.
纯MoTe2设备的内存窗口有限,阻碍了神经形态应用程序.

研究的目的:

为了增强横向MoTe2设备的模拟开关特性.
为了提高基于MoTe2的memristors和memtransistors用于神经形态计算的性能.
为了研究连续激光处理和Al2O3原子层沉积的协同效应.

主要方法:

激光处理和Al2O3的原子层沉积 (ALD) 在侧面MoTe2装置上的顺序应用.
作为memristors和memtransistors的设备性能的表征.
模拟人工神经网络以评估模式识别准确度.

主要成果:

对memristor操作的动态范围进行了70倍的改进.
在memtransistor操作的动态范围的20倍增强.
在人工神经网络模拟中,模式识别精度增加了10倍.

结论:

联合激光处理和Al2O3ALD有效地提高了MoTe2设备在神经形态应用中的性能.
双重的memristor/memtransistor功能可以模拟突触可塑性 (同突触和异突触).
这种方法显著提高了二维材料在下一代计算架构中的潜力.

关键词:

两维材料是二维材料.模拟开关模拟开关模拟开关原子层的沉积方式激光图案设计激光图案设计记忆力记忆力记忆力这是一个Memtransistor.神经形态的神经形态

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