基于薄膜硅纳米片的神经形态组件

IF 8.2 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Rana Biswas*, , , Moneim Elshobaki, , , Jeremy B. Essner, , , Owen Comiskey, , , Shweta Shweta, , , Jaeyoun Kim, , and , Matthew G. Panthani, 
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引用次数: 0

摘要

我们展示了硅纳米片(NS)组件的神经形态行为。我们使用了Cl-和h -钝化的Si-NSs,它们是在- 35°C下用浓HCl对CaSi2的Zintl相进行拓扑脱嵌合成的。我们利用硅基平台,通过光刻技术在SiO2/Si晶圆上制造Au源漏极(S-D)电极。我们采用溶液加工方法在金S-D电极之间以介观通道长度(30-80 μm)制备了Si-NS封装组件。Si-NS组件表现出新的神经形态特征,其中尖峰电压输入导致衰减尖峰电流输出,类似于已知的神经元突触系统的可塑性。衰减的尖峰电流输出遵循β ~ 0.7-1.1的幂律衰减(~ t -β)。DFT和电子捕获模拟表明,这种神经塑性特性可能来自于NS表面si悬空键的电荷充电和释放。更高频率的测量也揭示了一个初始学习阶段,在这个阶段,尖峰电压输出逐渐建立到最大值,类似于神经元-突触系统中的增强过程。这些观察到的神经形态特征表明,Si-NSs是下一代神经形态网络的一种有前途的材料,在节能、脑启发计算方面具有巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Thin-Film Silicon Nanosheet-Based Neuromorphic Assemblies

Thin-Film Silicon Nanosheet-Based Neuromorphic Assemblies

We demonstrate neuromorphic behavior in silicon nanosheet (NS) assemblies. We utilized Cl- and H-passivated Si-NSs that were synthesized through topotactic deintercalation of the Zintl phase of CaSi2 with concentrated HCl at −35 °C. We utilize a silicon-based platform in which we fabricated Au source-drain (S-D) electrodes on SiO2/Si wafers by photolithography. We fabricated encapsulated assemblies of Si-NS between gold S-D electrodes at mesoscopic channel lengths (30–80 μm) using solution processing methods. The Si-NS assemblies exhibit novel neuromorphic characteristics in which spiking voltage inputs lead to decaying spiking current outputs, analogous to plasticity known for neuron-synapse systems. Decaying spiking current outputs follow a power-law decay (∼t–β) with β ∼ 0.7–1.1. DFT and electron-trapping simulations suggest that such neuroplastic characteristics may arise from the charging and release of charge from Si-dangling bonds at the NS surfaces. Higher-frequency measurements also reveal an initial learning phase, where the spiking voltage outputs gradually build up to a maximum value, analogous to the potentiation process in neuron-synapse systems. These observed neuromorphic characteristics indicate that Si-NSs are a promising material for next-generation neuromorphic networks with immense potential for energy-efficient, brain-inspired computing.

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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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