用于模拟深度学习的磷硅酸盐玻璃基纳秒质子可编程电阻器

M. Onen, Ju Li, B. Yildiz, Jesús A. del Alamo
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引用次数: 0

摘要

在这项工作中,我们展示了基于磷硅酸盐玻璃(PSG)电解质的硅兼容纳米级质子器件。我们的器件在快速运行(5ns /脉冲)、高能量效率(~fJ/脉冲)、大动态电导范围、线性、对称性、可逆性、保持性和高耐用性方面具有理想的电导调制特性。本文综述了这些器件的制作方法和特点,重点介绍了快速运行时的质子动力学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phosphosilicate Glass-Based Nanosecond Protonic Programmable Resistors for Analog Deep Learning
Programmable resistors are widely explored devices as building blocks for analog deep learning accelerators. In this work, we demonstrate Si-compatible nanoscale protonic devices based on phosphosilicate glass (PSG) electrolyte. The conductance modulation characteristics of our devices are ideal in terms of fast operation (5 ns/pulse), high energy efficiency (~fJ/pulse), large dynamic conductance range, linearity, symmetry, reversibility, retention, and high endurance. This paper summarizes the fabrication and characteristics of these devices with particular attention to the proton dynamics during fast operation.
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